Monitor your Linux servers with Middleware. This guide covers installation, key metrics, alert setup, and best practices to prevent downtime and catch issues early.

How to Monitor Linux Infrastructure with Middleware


<p>The promise of modern <a href="https://middleware.io/blog/observability/">observability</a> was simple: &#8220;Collect everything, and you&#8217;ll know everything.&#8221; But for most teams, that promise has turned into a nightmare of skyrocketing storage costs and &#8220;needle-in-a-haystack&#8221; troubleshooting. When you&#8217;re drowning in data, you aren&#8217;t observing, you’re just hoarding. </p>



<p>As teams grow, they collect more <a href="https://middleware.io/blog/what-is-log-monitoring/">logs</a>, traces, metrics, and frontend telemetry. The problem is not just volume. The bigger problem is relevance. When everything is stored, teams spend more money, search through more noise, and still take longer to find what matters.</p>



<p>Today, we’re handing you the remote control. The <strong>Middleware Observability Pipeline</strong> is officially here to help you filter the noise, protect your budget, and ensure that only the most actionable <a href="https://middleware.io/blog/what-is-opentelemetry/">telemetry</a> makes it to your platform.</p>



<figure class="wp-block-pullquote"><blockquote><p>Modern observability isn&#8217;t just about collecting data; it&#8217;s about making that data actionable. Our goal with the Observability Pipeline is to bridge the gap between IT and business goals by ensuring every byte stored serves a purpose.</p><cite>Laduram Vishnoi, Founder and&nbsp;CEO at <a href="https://middleware.io/">Middleware</a></cite></blockquote></figure>



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<h2 class="wp-block-heading" id="h-the-problem-why-you-need-an-observability-pipeline">The Problem: Why You Need an Observability Pipeline</h2>



<p>As environments scale with more clusters, serverless, and <a href="https://middleware.io/blog/microservices-architecture/">microservices</a>, the volume of logs and <a href="https://middleware.io/blog/what-is-distributed-tracing/">traces</a> grows exponentially. Without a dedicated <strong>observability pipeline</strong>, the relevance of that data declines as costs rise.</p>



<ul class="wp-block-list">
<li><strong>The Economic Drain:</strong> You’re paying to store thousands of &#8220;200 OK&#8221; health checks that no one will ever read. Most companies allocate 20–30% of their infrastructure budget to observability.</li>



<li><strong>The Cognitive Fatigue:</strong> Engineers wade through 50 pages of logs to find a critical error because the <strong>observability pipeline</strong> isn&#8217;t yet filtering out noise.</li>



<li><strong>The Security Risk:</strong> PII and secrets accidentally leak into storage, creating a compliance ticking time bomb under GDPR, HIPAA, or SOC 2.</li>
</ul>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>⚡ Stop paying for data you don&#8217;t use. [<a href="https://app.middleware.io/auth/register/">Start your free 14-day trial</a>] and see how much noise you can cut from your clusters in the next 10 minutes.</p>
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<p>See the Pipeline in Action</p>



<p>Before we dive into the technical layers, see the Middleware Observability Pipeline in action:</p>



<div style="position: relative; padding-bottom: 56.25%; height: 0;"><iframe src="https://www.loom.com/embed/7e45d182134e4c6cbfd75bb01b38054d" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>



<h2 class="wp-block-heading" id="h-how-middleware-observability-pipeline-works">How Middleware Observability Pipeline Works</h2>



<p>The Middleware <strong>observability pipeline</strong> is designed as a multi-stage journey. Instead of treating all data as a single stream, we provide four distinct layers of control. This allows you to act on data at the most efficient moment possible.</p>



<h3 class="wp-block-heading" id="h-1-source-aware-selection">1. Source-Aware Selection</h3>



<p>A great observability pipeline starts at the source. Middleware allows you to create specific pipelines based on your environment: Host, Cluster, or <a href="https://middleware.io/blog/serverless-architecture/">Serverless</a>. This distinction is vital because a <a href="https://middleware.io/blog/kubernetes-monitoring/">Kubernetes</a> cluster requires different handling than a standalone Linux host.&nbsp;</p>



<p>By selecting the source first, the <strong>observability pipeline</strong> tailors the available tools to that specific architecture, ensuring you have the right &#8220;hooks&#8221; to grab the data you need.</p>



<h3 class="wp-block-heading" id="h-2-ingestion-control">2. Ingestion Control</h3>



<p>Once the data begins to move, it hits the <strong>Ingestion Control</strong> layer. Think of this as the &#8220;sorting hat&#8221; of your <strong>observability pipeline</strong>. Here, you can:</p>



<ul class="wp-block-list">
<li><strong>Parse and Format:</strong> Transform messy, unstructured logs into clean, JSON-ready attributes.</li>



<li><strong>Enrichment:</strong> Automatically add metadata (like geographic location or department IDs) to your traces so they are easier to query later.</li>



<li><strong>Toggle Control:</strong> Turn <a href="https://middleware.io/product/metrics/">metrics</a> and traces on or off with a single click. If you’re undergoing a heavy migration and don’t need traces for a specific service for 24 hours, you can kill the flow instantly without touching a line of code.</li>
</ul>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="840" src="https://middleware.io/backend/wp-content/uploads/2026/02/Ingestion-Control-in-Observabillty-pipeline.webp" alt="Ingestion Control in Observabillty pipeline" class="wp-image-14759"/></figure>



<h3 class="wp-block-heading" id="h-3-otel-native-filtering">3. OTEL-Native Filtering</h3>



<p>This is the &#8220;secret sauce&#8221; for advanced users. For cluster-based sources, Middleware utilizes <a href="https://middleware.io/blog/opentelemetry-collector/">OpenTelemetry (OTEL) collectors</a>. Our <strong>observability pipeline</strong> allows you to run <a href="https://docs.middleware.io/workflow/search-filter">filtering</a> rules <em>inside your own cluster</em>.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="865" src="https://middleware.io/backend/wp-content/uploads/2026/02/OTEL-Native-Filtering-in-observability-pipeline.webp" alt="OTEL-Native Filtering in observability pipeline" class="wp-image-14760"/></figure>



<p>Why does this matter? Because sending data over the internet costs money (egress fees) and uses <a href="https://middleware.io/blog/prevent-cpu-overload-on-linux-servers/">CPU power</a>. By dropping &#8220;Health Check&#8221; logs and noisy namespaces at the source, your <strong>observability pipeline</strong> saves you money on your <a href="https://middleware.io/blog/cloud-cost-optimization/">cloud provider bill</a> <em>and</em> your <a href="https://middleware.io/blog/observability-ways-to-reduce-it-costs-with-observability/">observability bill</a> simultaneously.</p>



<h3 class="wp-block-heading" id="h-4-backend-control">4. Backend Control</h3>



<p>The final stage of the <strong>observability pipeline</strong> happens just before data is committed to long-term storage and billing. This is where you set your &#8220;Policy Rules.&#8221;</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="871" src="https://middleware.io/backend/wp-content/uploads/2026/02/Backend-Control-in-observability-pipeline.webp" alt="Backend Control in observability pipeline" class="wp-image-14761"/></figure>



<p>Backend Control is designed for cost and compliance. If a log matches a specific &#8220;drop rule&#8221; (e.g., level=&#8221;debug&#8221; AND environment=&#8221;staging&#8221;), it is permanently discarded. To give you total confidence, we’ve included a <strong>Preview Expression</strong> feature.</p>



<p>You can write a rule and immediately see how many logs it would have caught over the last hour, ensuring you don&#8217;t accidentally silence critical production alerts.</p>



<h2 class="wp-block-heading" id="h-why-teams-are-switching-to-the-middleware-observability-pipeline">Why Teams Are Switching to the Middleware Observability Pipeline</h2>



<h3 class="wp-block-heading" id="h-cost-optimization-without-risk">Cost Optimization Without Risk</h3>



<p>Every team has &#8220;noisy&#8221; services, perhaps a legacy app that logs every mouse movement. Without an <strong>observability pipeline</strong>, you pay for that. With Middleware, you can create a rule to sample these logs at 5% or drop them entirely, while keeping 100% of your &#8220;Error&#8221; logs. You get the visibility you need at a fraction of the price.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;<em>Compared to other observability solutions, Middleware offered similar or even superior capabilities at a much lower cost, eliminating the need for expensive tiered pricing or additional charges for advanced features. This made Middleware a more accessible and scalable solution for a business like ours. In fact, we were able to reduce our costs by 75%.”</em></p><cite>Krishna Charan BS, Information Security Head, <a href="https://middleware.io/customers/mindorigin/">MindOrigin</a></cite></blockquote></figure>



<h3 class="wp-block-heading" id="h-automated-data-redaction-amp-compliance">Automated Data Redaction &amp; Compliance</h3>



<p>Manual redaction is impossible at scale. Our <strong>observability pipeline</strong> can be configured to recognize patterns (such as 16-digit numbers or email formats) and mask them in real time. This ensures that even if a developer accidentally logs a customer’s password, it is scrubbed before it ever leaves your secure environment.</p>



<h3 class="wp-block-heading" id="h-standardizing-global-telemetry">Standardizing Global Telemetry</h3>



<p>In large organizations, Team A might call a user ID <code>user_id</code>, while Team B calls it <code>u_id</code>. This makes cross-service troubleshooting a nightmare. You can use the <strong>observability pipeline</strong> to &#8220;normalize&#8221; these keys, ensuring that your entire platform speaks the same language.</p>



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  <p>Our drag-and-drop interface makes it easy for Dev and Ops teams to collaborate on data rules.
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<h2 class="wp-block-heading" id="h-setting-up-your-first-observability-pipeline">Setting Up Your First Observability Pipeline</h2>



<p>Ready to take control? Follow this blueprint to get your <strong>observability pipeline</strong> running in minutes:</p>



<ul class="wp-block-list">
<li>Open <strong>Settings → Pipelines</strong> and create a pipeline for your environment.</li>



<li>Select the <span style="box-sizing: border-box; margin: 0px; padding: 0px;">appropriate&nbsp;<strong>source type</strong>&nbsp;first (Host, Cluster, or Serverless), as the available controls depend on the selected source type</span>.</li>



<li>Enable <strong>Ingestion Controls</strong> to parse, shape, and enrich telemetry early in the flow.</li>



<li>For cluster sources, add <strong>OTEL-native filters</strong> when you want source-side filtering before data leaves the cluster.</li>



<li>Apply <strong>Backend Control</strong> rules to drop non-actionable telemetry before storage.</li>
</ul>



<p>The era of &#8220;blindly sending data&#8221; is over. To stay competitive, fast, and secure, you need an <strong>observability pipeline</strong> that works as hard as your developers do. By implementing <a href="https://middleware.io/platform/observability-pipeline/">Middleware Observability Pipelines</a>, you aren&#8217;t just saving money; you&#8217;re freeing your engineers to focus on what they do best: building great software.</p>



<figure class="wp-block-pullquote"><blockquote><p><em>&#8220;I don&#8217;t want my developers staying up all night digging through logs to fix issues; that&#8217;s a waste of everyone&#8217;s time. Middleware saves at least an hour of my time every day, allowing us to focus on building rather than searching.&#8221;</em></p><cite><strong>Akshat Gupta</strong>, Manager of Engineering Operations at <a href="https://middleware.io/customers/trademarkia/">Trademarkia</a></cite></blockquote></figure>



<p>The Middleware <strong>observability pipeline</strong> is now available for all users. It’s time to stop hoarding data and start mastering it.</p>



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<div><h3>Ready to reclaim your observability budget? </h3>
  <p>Middleware is the only platform that gives you this level of granular control at a flat, predictable price. Don&#8217;t let your data manage you; take control today.
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Middleware Observability Pipeline helps teams cut noise, reduce costs, and protect data by filtering, enriching, and controlling telemetry before storage.

Mastering Your Data Flow: Introducing the Middleware Observability Pipeline


<p>In the world of <a href="https://middleware.io/blog/microservices-architecture/">microservices</a>, service-level metrics often act like a &#8220;check engine&#8221; light. They tell you something is wrong under the hood, but they don&#8217;t tell you which specific part is failing. A service might report a healthy 99% success rate while a critical /checkout endpoint is silently failing for every user.</p>



<p>Traditional <a href="https://middleware.io/blog/apm-tools/">APM tools</a> aggregate data at the service level, which smooths out the very spikes you need to see. This &#8220;average&#8221; performance often hides &#8220;outlier&#8221; disasters, leaving engineers to hunt through <a href="https://middleware.io/blog/what-is-log-monitoring/">logs</a> and trace spans to find the culprit.</p>



<p>Today, we are excited to announce the launch of <strong>Endpoint Monitoring</strong>, a core pillar of our <a href="https://middleware.io/product/apm/">APM</a> suite. This feature moves beyond broad service averages to provide granular, route-level <a href="https://middleware.io/blog/observability/">observability</a>. By merging real-time trace traffic with your OpenAPI (Swagger) specifications, Middleware provides a single source of truth for both the design and the <a href="https://middleware.io/blog/api-monitoring/">performance of your APIs</a>.</p>



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<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>👉 <a href="https://app.middleware.io/auth/register/">Try Endpoint Monitoring</a> to see route-level insights in real time, or <a href="https://docs.middleware.io/apm-configuration/endpoints-observability">read endpoint docs</a> to learn how to get started.</p>
</blockquote>



<h2 class="wp-block-heading" id="h-the-missing-link-in-api-observability">The Missing Link in API Observability</h2>



<p>Most documentation fails because the &#8220;proof&#8221; (live data) rarely lives with the &#8220;plan&#8221; (the API spec). This gap creates friction in the moments that matter most. When an incident occurs, time is wasted switching between documentation repositories and observability <a href="https://docs.middleware.io/workflow/custom-dashboard/dashboard-builder-overview">dashboards</a> just to understand what a specific endpoint was <em>supposed</em> to do versus what it is <em>actually</em> doing.</p>



<p><a href="https://middleware.io/solutions/endpoint-monitoring/">Middleware Endpoint Monitoring</a> changes the experience immediately. Instead of treating requests as anonymous strings, we match real-world traffic to your documented operations, giving you a 360-degree view of your API health, performance, and compliance.</p>



<div class="container-cta">
  
<div><h3>🔥Don’t Let Slow Endpoints Impact Your Users</h3>
  <p>Middleware Endpoint Monitoring connects live trace data with your OpenAPI specs to help you pinpoint bottlenecks faster and resolve issues before they escalate.
 </p>
  <a href="https://middleware.io/solutions/endpoint-monitoring/" target="_blank" rel="noopener"><button class="primary white">Try Endpoint Monitoring</button></a>

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<h2 class="wp-block-heading" id="h-how-it-works-from-discovery-to-deep-dive">How it Works: From Discovery to Deep-Dive</h2>



<p>Middleware helps you move from raw data to a structured API inventory in seconds.</p>



<p>Watch the walkthrough below to see how to connect your specs and explore your endpoint signals:</p>



<div style="position: relative; padding-bottom: 69.76744186046511%; height: 0;"><iframe src="https://www.loom.com/embed/6fa165fd3d1242dd93d8a13c4de388f3" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>



<h3 class="wp-block-heading" id="h-1-automatic-discovery-via-trace-traffic">1. Automatic Discovery via Trace Traffic</h3>



<p>Middleware uses real-time trace data to automatically discover your API endpoints as they are hit in production. There is no manual configuration required.</p>



<ul class="wp-block-list">
<li><strong>Instant Inventory:</strong> Every Method + Route combination is identified and mapped to its serving service.</li>



<li><strong>Live Health Signals:</strong> See request volume, error rates, and <strong>P95/P99 latency</strong>. These tail latencies highlight the slowest requests, the ones your customers feel first.</li>
</ul>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Explore more insights on detecting, analyzing, and reducing <a href="https://middleware.io/blog/detect-api-latency/">API latency</a> to ensure faster performance and better user experiences across your services.</p>
</blockquote>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="857" src="https://middleware.io/backend/wp-content/uploads/2026/02/Endpoint-Observability.webp" alt="Endpoint Observability" class="wp-image-14724"/></figure>



<h3 class="wp-block-heading" id="h-2-activating-your-openapi-specs">2. Activating Your OpenAPI Specs</h3>



<p>Documentation shouldn&#8217;t be static. By linking an <strong>OpenAPI spec</strong> via GitHub sync or file upload, Middleware transforms your blueprints into an active monitoring tool.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="855" src="https://middleware.io/backend/wp-content/uploads/2026/02/middleware-openapi-endpoint-monitoring.webp" alt="Activating OpenAPI specs in Middleware to enable real-time endpoint monitoring and route-level API observability" class="wp-image-14727"/></figure>



<ul class="wp-block-list">
<li><strong>Contract Context:</strong> Middleware matches endpoints to documented operations, adding parameter definitions and response codes.</li>



<li><strong>Component Tracking:</strong> Monitor the complexity of your API using &#8220;Components&#8221; counts to ensure your reusable schemas are performing as expected.</li>
</ul>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="856" src="https://middleware.io/backend/wp-content/uploads/2026/02/middleware-api-endpoints-list-view.webp" alt="API endpoints list in Middleware showing documented routes, components, parameters, and real-time performance metrics" class="wp-image-14728"/></figure>



<h3 class="wp-block-heading" id="h-3-single-endpoint-intelligence">3. Single-Endpoint Intelligence</h3>



<p>Clicking into an endpoint opens a dedicated command center that separates the &#8220;what&#8221; (the definition) from the &#8220;how&#8221; (the performance):</p>



<ul class="wp-block-list">
<li><strong>Definition &amp; Info:</strong> Explore parameters (Path, Query, Header, Body) and documented response codes directly alongside live data.</li>



<li><strong>Span Summary:</strong> A breakdown of where time is spent, whether in <a href="https://middleware.io/blog/postgresql-monitoring/">PostgreSQL</a> queries, downstream HTTP calls, or internal functions.</li>
</ul>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="855" src="https://middleware.io/backend/wp-content/uploads/2026/02/middleware-single-endpoint-intelligence-dashboard.webp" alt="Single endpoint view in Middleware displaying API definition, parameters, response codes, and span summary with dependency-level latency breakdown." class="wp-image-14731"/></figure>



<h2 class="wp-block-heading" id="h-where-endpoint-monitoring-helps-the-most">Where Endpoint Monitoring Helps the Most</h2>



<h3 class="wp-block-heading" id="h-slashing-mttr-during-incidents">Slashing MTTR during Incidents</h3>



<p>When a service <a href="https://middleware.io/platform/alerts/">alert</a> fires, the fastest way to respond is to pinpoint the exact failing route. Endpoint Monitoring lets you sort your API list by &#8220;<strong>Error Rate</strong>&#8221; or &#8220;<strong>P99 Latency</strong>&#8221; instantly. Instead of triaging a whole service, you start your investigation from the impacted route, reducing the time spent in &#8220;war rooms.&#8221;</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>⭐ Learn how OpsAI helps you resolve issues: Once you&#8217;ve identified a failing endpoint, use our <a href="https://middleware.io/blog/opsai-ai-observability-copilot/">OpsAI Co-pilot</a> to instantly analyze traces and suggest a fix, moving from detection to resolution in seconds.</p>
</blockquote>



<h3 class="wp-block-heading" id="h-zero-regression-deployments">Zero-Regression Deployments</h3>



<p>The <strong>Deployments</strong> view allows you to compare endpoint performance across different service versions. You can validate whether a new release changed the behavior of a specific route by comparing <strong>Apdex scores</strong>, error rates, and latency percentiles between v1.0 and v1.1.</p>



<div class="container-cta">
  
<div><h3>🔥Turn Your API Specs into Live Observability</h3>
  <p>Activate Endpoint Monitoring to automatically discover routes, analyze latency, and gain deep performance insights all from a single source of truth.
 </p>
  <a href="https://middleware.io/solutions/endpoint-monitoring/" target="_blank" rel="noopener"><button class="primary white">Get Started</button></a>

 <a href="https://docs.middleware.io/apm-configuration/endpoints-observability" target="_blank" rel="noopener"><button class="secondary white">View Docs</button></a>
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<h3 class="wp-block-heading" id="h-pinpointing-bottlenecks-code-vs-db-vs-network">Pinpointing Bottlenecks (Code vs. DB vs. Network)</h3>



<p>The <strong>Span Summary</strong> groups the work happening under an endpoint by dependency type. If an endpoint is dragging, you can instantly see if 80% of the duration is spent in a database call or an internal function. This eliminates the &#8220;blame game&#8221; between database and application teams.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="921" src="https://middleware.io/backend/wp-content/uploads/2026/02/middleware-endpoint-span-summary-bottleneck-analysis-1.webp" alt="Span summary in Middleware showing dependency-level breakdown across database, network, and application code to quickly identify API performance bottlenecks" class="wp-image-14733"/></figure>



<h3 class="wp-block-heading" id="h-onboarding-amp-api-compliance">Onboarding &amp; API Compliance</h3>



<p>For new team members, the Endpoints screen acts as a live map. They can see what endpoints exist, read their descriptions from the <em><a href="https://docs.middleware.io/apm-configuration/endpoints-observability#link-endpoints-with-an-openapi-spec">OpenAPI spec</a></em>, and understand real-world traffic patterns without digging through outdated wikis.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="856" src="https://middleware.io/backend/wp-content/uploads/2026/02/middleware-endpoints-overview-api-map.webp" alt="Endpoints overview in Middleware providing a live API map with OpenAPI descriptions and real-time traffic insights for faster onboarding and compliance" class="wp-image-14735"/></figure>



<h2 class="wp-block-heading" id="h-shared-context-faster-resolution">Shared Context, Faster Resolution</h2>



<p>The value of Endpoint Monitoring compounds when teams share a unified view. The generic dashboard link is useful, but it doesn&#8217;t explain the contract. Sharing a trace is granular but lacks context.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Pro-Tip: Found a performance regression? Click &#8220;Add to Notebook&#8221; to drop your endpoint charts and trace evidence into a<a href="https://middleware.io/blog/introducing-middleware-notebooks/"> Middleware Notebook</a> for a collaborative incident report.</p>
</blockquote>



<p>Sharing an <strong>Endpoint Detail</strong> view gives your coworkers the narrative: the documented intent of the API, the current performance reality, and the specific spans causing the delay. It turns &#8220;<em><strong>I think this route is slow</strong></em>&#8221; into &#8220;<em><strong>Here is the proof</strong></em>, the contract, and the bottleneck.&#8221;</p>



<h2 class="wp-block-heading" id="h-stop-guessing-start-monitoring-at-the-route-level">Stop Guessing. Start Monitoring at the Route Level.</h2>



<p>Middleware Endpoint Monitoring turns your <a href="https://docs.middleware.io/public-api/api">API documentation</a> into a living, breathing part of your observability stack. By combining the engineer&#8217;s intent with the system&#8217;s evidence, we&#8217;re making API management faster and more reliable.</p>



<p><strong>Ready to see it in action?</strong></p>



<ul class="wp-block-list">
<li><strong>Existing Customers:</strong> Navigate to <strong>APM → Endpoints</strong> in your Middleware sidebar.</li>



<li><strong>New to Middleware?</strong> <a href="https://app.middleware.io/auth/register/">Experience Middleware for free</a> and see how Endpoint Monitoring brings your entire team onto the same page.</li>
</ul>


Introducing Endpoint Monitoring get granular, route-level API insights by combining live traces with OpenAPI specs to detect failures faster and resolve issues with confidence.

Introducing API Endpoint Monitoring


<p>When a service goes down, even if you already <a href="https://docs.middleware.io/workflow/alerting/setup-alert">created alerts</a> to detect abnormal behavior, the first 10 minutes are often a blur. You’re jumping between the <a href="https://docs.middleware.io/workflow/log-monitoring/log-explorer">Log Explorer</a>, <a href="https://middleware.io/product/apm/">APM</a> dashboards, and Slack frantically pasting screenshots and links that will be broken or irrelevant by the time the post-mortem starts.</p>



<p>Traditional incident notes fail because they are static. You might write that &#8220;DB latency spiked,&#8221; but the chart proving it is buried in another tab inside your <a href="https://middleware.io/blog/observability/">observability</a> dashboards, disconnected from the investigation itself. The &#8220;why&#8221; and the &#8220;evidence&#8221; live in two different worlds.</p>



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<div> <p>We are excited to announce Middleware Notebooks, a collaborative, interactive canvas that brings your investigation notes and live data into one unified story.
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<h2 class="wp-block-heading" id="h-the-missing-piece-of-the-operational-puzzle">The Missing Piece of the Operational Puzzle</h2>



<p>Most documentation fails because the &#8220;proof&#8221; rarely lives with the explanation. This gap creates friction in the moments that matter most. Handoffs slow down because the next engineer must rebuild the investigation path. Post-mortems become memory-based because the evidence is buried in dashboards or lost in chat threads.</p>



<p><a href="https://middleware.io/platform/notebook/">Middleware Notebooks</a> change the experience immediately. Instead of switching between dashboards, <a href="https://middleware.io/product/log-monitoring/">logs</a>, traces, and a separate document, you have one place where your reasoning and your supporting visuals sit side-by-side.</p>



<p><em>“The result is a note that reads like a story but behaves like a technical artifact your team can trust.”</em></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1202" height="738" src="https://middleware.io/backend/wp-content/uploads/2026/02/Middleware-Notebooks.webp" alt="Middleware Notebooks" class="wp-image-14677"/></figure>



<h2 class="wp-block-heading" id="h-why-notebooks-feel-different">Why Notebooks Feel Different</h2>



<p>Notebooks aren&#8217;t just a place to type; they are an extension of your <a href="https://middleware.io/blog/what-is-opentelemetry/">telemetry</a>. They combine a rich text editor with Live Data Blocks powered directly by your logs, metrics, and <a href="https://middleware.io/blog/what-is-application-performance-monitoring/">application performance monitoring</a> data.</p>



<h3 class="wp-block-heading" id="h-1-investigations-with-live-evidence">1. Investigations with &#8220;Live Evidence&#8221;</h3>



<p>Instead of describing a spike, you drop the query directly into the Notebook. It stays interactive. If a teammate opens the Notebook, they can hover over the data points, change the time range, or tweak the query without leaving the document.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1567" height="984" src="https://middleware.io/backend/wp-content/uploads/2026/02/middleware-notebooks-live-query-investigation.webp" alt="Interactive query inside Middleware Notebooks showing live observability data during an incident investigation." class="wp-image-14678"/></figure>



<h3 class="wp-block-heading" id="h-2-post-mortems-that-build-themselves">2. Post-Mortems That Build Themselves</h3>



<p>Since you’re already documenting your investigation in the Notebook as it happens, your <a href="https://middleware.io/blog/identify-root-cause-analysis/">Root Cause Analysis</a> (RCA) is 80% done by the time the issue is resolved. You have the timeline, logic, and proof in a single shareable link.</p>



<h3 class="wp-block-heading" id="h-3-living-runbooks">3. &#8220;Living&#8221; Runbooks</h3>



<p>Turn your static wikis into dynamic instructions. A Notebook runbook can include the &#8220;How-To&#8221; text alongside live graphs that show what a &#8220;Healthy&#8221; vs. &#8220;Unhealthy&#8221; state looks like right now.</p>



<p>Teams can reference healthy service patterns in their <a href="https://middleware.io/platform/dashboard/">Middleware AI dashboards</a> while documenting response steps.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>⭐Learn how the AI Dashboard Builder helps you create production-ready observability views from natural language, so you can move from detection to explanation faster. <a href="https://middleware.io/blog/introducing-fastest-ai-dashboard-builder/">Read More</a></p>
</blockquote>



<h3 class="wp-block-heading" id="h-see-it-in-action">See it in Action:</h3>



<div style="position: relative; padding-bottom: 69.76744186046511%; height: 0;"><iframe src="https://www.loom.com/embed/a6bb17443ff6457a97ec71a1361caa6b" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>



<h2 class="wp-block-heading" id="h-how-it-works-from-logs-to-logic">How it Works: From Logs to Logic</h2>



<p>Getting started is seamless. You can move from raw data to a structured report in seconds:</p>



<ol class="wp-block-list">
<li><strong>Access</strong>: Navigate to Logs &gt; Notebooks in the Middleware sidebar.</li>



<li><strong>Create</strong>: <a href="https://docs.middleware.io/workflow/log-monitoring/notebooks?_gl=1*g25evf*_ga*MTUwMDIzNzE1LjE3NDE2OTIxNDA.*_ga_2KBHR7YB2G*czE3NzAxMDc5ODIkbzEzMzAkZzEkdDE3NzAxMTIwNDkkajYwJGwwJGgw#create-a-new-notebook">Start a new Notebook</a> and give it a title (e.g., <em>&#8220;Q1 API Latency Investigation&#8221;</em>).</li>



<li><strong>Build:</strong> Mix rich-text documentation with live metrics to create your report, runbook, or troubleshooting sandbox.</li>
</ol>



<h2 class="wp-block-heading" id="h-beyond-plain-text-collaborative-notes-powered-by-graphs">Beyond Plain Text: Collaborative Notes Powered by Graphs</h2>



<p>Most documentation fails because the &#8220;proof&#8221; rarely lives with the explanation. Middleware Notebooks bridge this gap by bringing narrative and observability data into a single workflow.</p>



<p>Unlike a static wiki, Notebooks are an extension of your telemetry. You can start with a clean page, add structured text, and drop in <a href="https://middleware.io/blog/what-is-log-monitoring/">log monitoring</a> queries as interactive charts or tables. When you&#8217;re ready to loop in the team, they see the same notes and the same supporting views, eliminating the need to re-explain your logic in chat.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1598" height="575" src="https://middleware.io/backend/wp-content/uploads/2026/02/notebooks-observability-charts.webp" alt="Middleware Notebooks displaying collaborative notes with log monitoring queries visualized as interactive charts." class="wp-image-14683"/></figure>



<h3 class="wp-block-heading" id="h-1-flexible-visualization-types">1. Flexible Visualization Types</h3>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1477" height="524" src="https://middleware.io/backend/wp-content/uploads/2026/02/observability-visualization-types-notebooks.webp" alt="Multiple observability chart types in Middleware Notebooks, including timeseries, bar, and pie visualizations for telemetry analysis." class="wp-image-14684"/></figure>



<p>Pick the type that matches your goal. From the data source editor, you can choose output styles including:</p>



<ul class="wp-block-list">
<li><strong>Timeseries &amp; Bar Charts</strong> for trends and spikes.</li>



<li><strong>Pie, Scatter, &amp; Tree Charts</strong> for distribution and relationship analysis.</li>



<li><strong>List Values</strong> for quick breakdown tables.</li>



<li><strong>Hexagon &amp; Top List Charts</strong> for high-density data.</li>
</ul>



<h3 class="wp-block-heading" id="h-2-configure-with-quick-edit">2. Configure with &#8220;Quick Edit&#8221;</h3>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1468" height="788" src="https://middleware.io/backend/wp-content/uploads/2026/02/quick-edit-query-configuration-middleware-notebooks.webp" alt="Quick Edit panel in Middleware Notebooks showing multi-query configuration, formulas, and visualization controls for observability data." class="wp-image-14688"/></figure>



<p>Each data source block includes an <strong>Expand Quick Edit</strong> option. This allows you to tune your investigation on the fly:</p>



<ul class="wp-block-list">
<li><strong>Multi-Query Support:</strong> Add multiple queries (A, B, C&#8230;) in a single block to compare different data sets.</li>



<li><strong>Advanced Shaping:</strong> Apply functions, formulas, and aggregations (like uniq by or any by) to refine your results.</li>



<li><strong>Granular Control:</strong> Adjust Y-Axis controls, legends, and sorting to make your &#8220;evidence&#8221; as readable as possible.</li>
</ul>



<h3 class="wp-block-heading" id="h-3-access-amp-organization">3. Access &amp; Organization</h3>



<p>Navigate to <strong>Logs → Notebooks</strong> from the top navigation. Here, you can manage your library of insights:</p>



<ul class="wp-block-list">
<li><strong>Search &amp; Star:</strong> Quickly find notebooks by name or &#8220;Star&#8221; favorites for instant access.</li>



<li><strong>Ownership Tracking:</strong> The list shows the <strong>Author</strong> and <strong>Date Modified</strong>, so you always know who has the most recent version.</li>



<li><strong>Automatic TOC:</strong> As you add H1 and H2 headings, a <strong>Table of Contents</strong> updates on the left so you can jump between sections easily.</li>
</ul>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1152" height="495" src="https://middleware.io/backend/wp-content/uploads/2026/02/notebooks-workspace-navigation-and-organization.webp" alt="Middleware Notebooks workspace showing organized notebook library with search, favorites, and ownership tracking." class="wp-image-14692"/></figure>



<h3 class="wp-block-heading" id="h-4-write-and-format-content">4. Write and Format Content</h3>



<p>Notebooks support simple formatting to keep your notes readable without heavy markdown:</p>



<ul class="wp-block-list">
<li><strong>Headings:</strong> Use <strong>H1</strong> for main sections and <strong>H2</strong> for sub-sections.</li>



<li><strong>Lists:</strong> Use bullet points for findings and numbered lists for sequences or runbooks.</li>



<li><strong>Tables:</strong> Insert tables (using the / command) for environment variables, endpoints, or incident timelines.</li>
</ul>



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<div><h3>Start Building Evidence-Backed Investigations Today</h3> <p>Create your first Middleware Notebook and turn incident chaos into structured, shareable insight.
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<h2 class="wp-block-heading" id="h-where-notebooks-help-the-most">Where Notebooks Help the Most</h2>



<h3 class="wp-block-heading" id="h-1-incident-investigation-with-evidence-attached">1. Incident Investigation with Evidence Attached</h3>



<p>When an outage occurs, your <a href="https://middleware.io/blog/incident-management-kpis/">incident management</a> workflow depends on fast, evidence-backed decisions. You form hypotheses and test them in real time. A Notebook gives you a natural place to capture that flow.&nbsp;</p>



<p>You can keep a short timeline, record what you checked, and attach live visuals from the data source to confirm what changed. This turns a frantic session into a record others can follow without repeating your steps.</p>



<h3 class="wp-block-heading" id="h-2-clean-on-call-handoffs">2. Clean On-Call Handoffs</h3>



<p>Handoffs fail when the next person gets a wall of text or a set of links without context. A Notebook keeps the narrative, the current status, and the supporting graphs together. The next engineer can scan the story, review the evidence, and continue from the last known state rather than starting from scratch.</p>



<h3 class="wp-block-heading" id="h-3-post-mortems-that-are-faster-to-write-and-trust">3. Post-mortems That Are Faster to Write (and Trust)</h3>



<p>Post-mortems are painful when you have to reconstruct everything days later. When a Notebook is used during the incident, the core details already exist. The narrative is written while the incident is fresh, and the charts used to confirm impact are already embedded. This makes the final RCA less about recollection and more about verifiable evidence.</p>



<h3 class="wp-block-heading" id="h-4-living-runbooks-that-do-not-go-stale">4. Living Runbooks That Do Not Go Stale</h3>



<p>Most runbooks fail because they become unreadable over time. A Notebook-style runbook includes explanations, steps, and live charts that confirm the expected healthy vs. unhealthy states. This keeps documentation practical and reduces uncertainty for new team members during stressful moments.</p>



<h3 class="wp-block-heading" id="h-5-support-escalations-amp-stakeholder-summaries">5. Support Escalations &amp; Stakeholder Summaries</h3>



<p>When a customer-facing issue happens, <a href="https://middleware.io/blog/what-is-real-user-monitoring/">real user monitoring</a> (RUM) data helps teams understand the impact faster. Leaders need a crisp summary. A Notebook can hold the symptoms, impact window, and evidence in one place. This reduces back-and-forth and keeps everyone from support to engineering aligned on what is known and what remains to be tested.</p>



<h3 class="wp-block-heading" id="h-6-weekly-ops-reviews-amp-reliability-updates">6. Weekly Ops Reviews &amp; Reliability Updates</h3>



<p>Stop wasting time on slide decks or screenshot collections. A Notebook makes reliability updates lighter by combining a short narrative with key charts and action items on a single page that can be shared and revisited.</p>



<h2 class="wp-block-heading" id="h-shared-narratives-not-just-shared-links">Shared Narratives, Not Just Shared Links</h2>



<p>The value of Notebooks compounds when they are shared. Sharing a dashboard link is useful, but it doesn&#8217;t explain the <em>reasoning</em>. Sharing a screenshot is quick, but it becomes stale. Sharing a Notebook gives your coworkers the narrative, timeline, and visuals in the exact order in which the investigation unfolded.</p>



<h2 class="wp-block-heading" id="h-stop-guessing-start-documenting">Stop Guessing. Start Documenting.</h2>



<p>Middleware Notebooks turn &#8220;<em>I think this happened</em>&#8221; into &#8220;<em>Here is the proof</em>.&#8221; By combining the <em>engineer&#8217;s narrative</em> with the <em>system&#8217;s evidence</em>, we’re making incident response faster, clearer, and more human.</p>



<p><strong>Ready to see it in action?</strong></p>



<ul class="wp-block-list">
<li><strong>Existing Customers:</strong> Click the <strong>Notebooks</strong> icon in your Middleware Topbar.</li>



<li><strong>New to Middleware?</strong> Stop chasing logs across tabs. <a href="https://app.middleware.io/auth/register/">Experience Middleware for free</a> and see how Notebooks bring your entire team onto the same page.</li>



<li><strong>Join the Conversation:</strong> Connect with our engineering team in the <a href="https://middlewarepublic.slack.com/"><strong>Middleware Community Slack</strong></a>.</li>
</ul>


Middleware Notebooks unify investigation notes with live observability data, helping teams collaborate faster, validate root causes, and create reliable incident reports.

Introducing Middleware Notebooks: Turning Incident Chaos into Evidence-Backed Stories


<p>Modern <a href="https://middleware.io/blog/observability/">observability</a> requires more than just collecting data; it requires making that data actionable. However, as infrastructure grows to span Kubernetes clusters, serverless functions, and dozens of <a href="https://middleware.io/blog/microservices-architecture/">microservices</a>, time-to-value for a new dashboard often ranges from minutes to hours.</p>



<p>Engineers frequently find themselves manually hunting for metric names, configuring complex Y-axis scales, and fighting with JSON schemas just to get a basic overview of a new service.</p>



<p>Today, we’re introducing the <a href="https://middleware.io/platform/dashboard/">Middleware AI Dashboard Builder</a>. By using natural language processing, we are moving from &#8220;manual configuration&#8221; to &#8220;intent-based monitoring.&#8221; You describe the objective; we build the visualization. You tell the AI what you want to see, and it builds the production-ready dashboard for you.</p>



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<div><p>Middleware has launched a new AI-powered Dashboard Builder that turns natural language into full-stack observability views.
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<h2 class="wp-block-heading" id="h-the-challenge-the-empty-canvas-problem">The Challenge: The &#8220;Empty Canvas&#8221; Problem</h2>



<p>Building a dashboard from scratch typically involves three points of friction:</p>



<ol class="wp-block-list">
<li><strong>Metric Discovery:</strong> Knowing exactly which metric (e.g., <code>system.cpu.utilization vs process.cpu.usage</code>) represents the health of your specific stack.</li>



<li><strong>Context Switching:</strong> Jumping between documentation and the dashboard builder to understand which attributes (like <code>spanId</code> or <code>service.name</code>) are available for <a href="https://docs.middleware.io/workflow/search-filter">filtering</a>.</li>



<li><strong>Layout Fatigue:</strong> Manually resizing and grouping widgets to create a logical flow for on-call engineers.</li>
</ol>



<h2 class="wp-block-heading" id="h-introducing-the-ai-dashboard-builder">Introducing the AI Dashboard Builder</h2>



<p>The Middleware AI Dashboard Builder acts as an intelligent orchestration layer between your raw <a href="https://middleware.io/blog/what-is-opentelemetry/">telemetry</a> and your UI. Instead of hunting for buttons, you use natural language to define your observability goals.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="864" src="https://middleware.io/backend/wp-content/uploads/2026/02/Introducing-the-AI-Dashboard-Builder.webp" alt="Introducing the AI Dashboard Builder" class="wp-image-14630"/></figure>



<h3 class="wp-block-heading" id="h-see-it-in-action-generating-a-dashboard-with-a-single-prompt">See it in Action: Generating a Dashboard with a Single Prompt</h3>



<p><em>Check out this quick walkthrough of how the AI transforms a natural language prompt into a fully functional dashboard:</em></p>



<div style="position: relative; padding-bottom: 63.454759106933025%; height: 0;"><iframe src="https://www.loom.com/embed/dd5bdc985b094d3d91714cdf00d66ddd" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>



<p></p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>👉Stop fighting your data and start using it. You can be up and running with Middleware in under five minutes no complex migration or steep learning curve required. <a href="https://app.middleware.io/auth/register/">Start Your 14-Day Free Trial</a></p>
</blockquote>



<h2 class="wp-block-heading" id="h-how-it-works-from-prompts-to-production">How it Works: From Prompts to Production</h2>



<p>The AI Dashboard Builder eliminates these hurdles by acting as an intelligent orchestration layer between your telemetry data and the visualization UI.</p>



<h3 class="wp-block-heading" id="h-1-intent-based-generation">1. Intent-Based Generation</h3>



<p>Instead of picking a &#8220;Time Series&#8221; widget and then selecting a query, you provide a high-level goal. For example:</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p><em>&#8220;Create a Kubernetes health dashboard for nodes, pods, CPU, memory, and network.&#8221;</em></p>
</blockquote>



<p>The AI parses this intent, identifies the relevant telemetry being ingested from your environment, and selects the optimal visualization type (gauges for health, heatmaps for distribution, or time-series for trends).</p>



<h3 class="wp-block-heading" id="h-2-context-aware-widget-creation">2. Context-Aware Widget Creation</h3>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1627" height="808" src="https://middleware.io/backend/wp-content/uploads/2026/02/ai-dashboard-builder-prompts-to-production.webp" alt="Middleware AI Dashboard Builder generating observability dashboards from high-level natural language prompts, showing intent-based and context-aware widget creation" class="wp-image-14635"/></figure>



<p>You aren&#8217;t limited to full dashboards. If you have an existing production dashboard and realize you&#8217;re missing error context, you can iterate incrementally:</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p><em>&#8220;Create widgets that provide a clear overview of log activity, error behaviour, and anomaly patterns across all services.&#8221;</em></p>
</blockquote>



<p>The AI recognizes the <code>service.name</code> attribute and the <code>severityNumber</code> from your <a href="https://middleware.io/blog/what-is-log-monitoring/">logs</a> to build a grouped bar chart or stacked area graph instantly.</p>



<p>If you already have a <a href="https://docs.middleware.io/workflow/dashboard-builder/dashboard-basics">dashboard</a>, you can build it up gradually by asking AI to add just one <a href="https://docs.middleware.io/workflow/dashboard-builder/build-dashboard-with-ai#create-a-specific-widget-inside-an-existing-dashboard">widget</a> at a time. This is ideal when you want to iterate without changing the rest of the layout.&nbsp;</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p><em>“Add a widget for log volume by service.”</em></p>
</blockquote>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p><em>“Add an errors by service widget for the last week.”</em></p>
</blockquote>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="807" src="https://middleware.io/backend/wp-content/uploads/2026/02/ai-dashboard-builder-add-widgets-incrementally.webp" alt="Middleware AI Dashboard Builder adding error and log volume widgets incrementally to an existing dashboard using natural language commands." class="wp-image-14637"/></figure>



<h3 class="wp-block-heading" id="h-3-automatic-data-validation">3. Automatic Data Validation</h3>



<p>The AI doesn&#8217;t just &#8220;hallucinate&#8221; graphs. It validates that the underlying telemetry, whether from <a href="https://middleware.io/solutions/aws/">AWS</a>, NGINX, or custom <a href="https://docs.middleware.io/open-telemetry/otel-getting-started">OpenTelemetry traces</a>, is actually being ingested. If the AI detects that a service isn&#8217;t <a href="https://docs.middleware.io/getting-started/application-instrumentation">instrumented</a>, it displays a summary panel outlining what was created and what may be missing, reducing the frustration of &#8220;No Data Found&#8221;.</p>



<h2 class="wp-block-heading" id="h-data-insights-depth-for-the-power-user">Data Insights: Depth for the Power User</h2>



<p>While AI builds the foundation, the builder provides an &#8220;engine room&#8221; for deep-dive engineering analysis.</p>



<h3 class="wp-block-heading" id="h-advanced-querying-amp-boolean-filters">Advanced Querying &amp; Boolean Filters</h3>



<p>Precision is key. Our builder supports complex Boolean expressions (AND, OR, NOT) and advanced operators like REGEX, ILIKE, and IN. You can group and nest conditions using brackets to control exactly how data is filtered.</p>



<ul class="wp-block-list">
<li><em><strong>Example:</strong></em> (host.id != prod-machine AND os.type == linux) OR status == stop</li>
</ul>



<h3 class="wp-block-heading" id="h-formulas-functions-and-time-shifting">Formulas, Functions, and Time-Shifting</h3>



<ul class="wp-block-list">
<li><strong>Custom Formulas:</strong> Assign letters to your queries (a, b, c) and write expressions like (a / b) * 100 to calculate error percentages on the fly.</li>



<li><strong>Post-Process Functions:</strong> Transform raw counters into meaningful rates using <strong>Per Second/Minute/Hour Rate</strong> or <strong>Monotonic Difference</strong> to ignore resets in cumulative series.</li>



<li><strong>Time Comparison:</strong> In the Query Value graph, toggle <strong>&#8220;Show Comparison with Previous Time Period&#8221;</strong> to see instant percentage changes (e.g., a 7.3% decrease in latency vs. the previous hour).</li>
</ul>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="877" src="https://middleware.io/backend/wp-content/uploads/2026/02/ai-dashboard-builder-advanced-querying-functions.webp" alt="with advanced querying, Boolean filters, custom formulas, and time-shifting for precise observability dashboards." class="wp-image-14639"/></figure>



<h2 class="wp-block-heading" id="h-advanced-filtering-narrowing-the-noise">Advanced Filtering: Narrowing the Noise</h2>



<p>A dashboard is only as good as its ability to isolate issues. AI-generated dashboards in Middleware come pre-configured with intelligent filters. You can stack conditions like <code>is_anomaly</code>, <code>traceId</code>, or severityText to drill down from a global view to a single failing <a href="https://docs.middleware.io/workflow/infrastructure-monitoring/container-monitoring">container</a> in two clicks.&nbsp;</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="860" src="https://middleware.io/backend/wp-content/uploads/2026/02/ai-dashboard-builder-advanced-filtering.webp" alt="applying advanced filters to isolate issues and reduce noise in observability dashboards." class="wp-image-14641"/></figure>



<p>It also applies <strong>Filters</strong> automatically. If your prompt specifies &#8220;production,&#8221; it looks for tags like <code>env:prod</code> or <code>namespace:production</code> to ensure you aren&#8217;t seeing development noise.</p>



<h2 class="wp-block-heading" id="h-built-for-flexibility-the-custom-builder-gui">Built for Flexibility: The Custom Builder GUI</h2>



<p>While the AI is the fastest way to get started, we know that sometimes you need &#8220;pixel-perfect&#8221; control. Our overhauled <strong>GUI Dashboard Builder</strong> gives you a &#8220;No-Code&#8221; way to refine what the AI started.</p>



<h3 class="wp-block-heading" id="h-the-new-widget-editor">The New Widget Editor</h3>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="860" src="https://middleware.io/backend/wp-content/uploads/2026/02/ai-dashboard-builder-custom-gui-widget-editor.webp" alt="custom GUI with a no-code widget editor for refining AI-generated dashboards." class="wp-image-14644"/></figure>



<p>The editor is now split into three logical sections to keep you in flow:</p>



<ul class="wp-block-list">
<li><strong>The Top Bar:</strong> A live preview with a dedicated time-range picker so you can see your changes against real data in real-time.</li>



<li><strong>The Left Panel:</strong> This is your &#8220;High-Level Intent&#8221; area. Name your widget, add a description, and choose your visualization type (Pie, Scatter, Tree, Bar, or the classic Timeseries).</li>



<li><strong>The Right Panel:</strong> The engine room. Here, you can fine-tune the Query Data, add complex Formulas, and set Advanced Options like Y-axis scaling.</li>
</ul>



<h3 class="wp-block-heading" id="h-advanced-grouping-amp-ordering">Advanced Grouping &amp; Ordering</h3>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="902" src="https://middleware.io/backend/wp-content/uploads/2026/02/ai-dashboard-builder-grouping-ordering.webp" alt="Organizing widgets using advanced grouping and ordering for logical dashboard layouts." class="wp-image-14646"/></figure>



<p>Organizing a dashboard for an entire team requires structure. We’ve introduced <strong>Group Orders</strong>. You can now assign widgets to specific groups (e.g., &#8220;Database Health&#8221; vs &#8220;Frontend Performance&#8221;).&nbsp;</p>



<p>By setting a group order number, you ensure that even as you add new widgets, your dashboard remains logically sorted for an on-call engineer at 3:00 AM.</p>



<h2 class="wp-block-heading" id="h-collaboration-visibility-for-the-whole-team">Collaboration: Visibility for the Whole Team</h2>



<p>In the past, sharing insights was a chore. You&#8217;d have to take screenshots, export CSVs, or, worse, grant manual permissions to every single stakeholder so they could see a basic uptime graph. Middleware has reimagined this workflow to ensure that your AI-generated insights are as easy to share as they are to build.</p>



<h3 class="wp-block-heading" id="h-1-collaborative-troubleshooting-during-incidents">1. Collaborative Troubleshooting during Incidents</h3>



<p>When a critical service goes down, the last thing you want is three different engineers looking at three different sets of data. Middleware&#8217;s dashboards serve as a <strong>single source of truth.</strong> Teams can share live, interactive dashboard links that maintain the same time range and filter context.</p>



<p>This means that when a Lead Engineer or Product Stakeholder views a dashboard, they see the same spikes and log errors in real time. This shared context eliminates the &#8220;it works on my machine&#8221; mentality and slashes the time spent in war rooms.</p>



<h3 class="wp-block-heading" id="h-2-stakeholder-ready-reporting-the-shareholder-view">2. Stakeholder-Ready Reporting (The &#8220;Shareholder View&#8221;)</h3>



<p>Shareholders and executives don&#8217;t need to see every micro-latency spike, but they <em>do</em> need to see high-level trends, SLA compliance, and resource ROI.</p>



<p>The Middleware Dashboard Builder allows you to create <strong>Visibility Tiers</strong>:</p>



<ul class="wp-block-list">
<li><strong>For Devs:</strong> Deep-dive views with trace IDs and granular system metrics.</li>



<li><strong>For Shareholders:</strong> High-level &#8220;Executive Summaries&#8221; that aggregate complex data into readable KPIs like <em>System Health Score</em> or <em>Cost Per Request</em>.</li>
</ul>



<p>By providing these clear, digestible views, engineering teams can communicate their value to the business without getting bogged down in technical jargon.</p>



<h3 class="wp-block-heading" id="h-3-granular-access-amp-permissioning">3. Granular Access &amp; Permissioning</h3>



<p>Collaboration shouldn&#8217;t mean compromising security. Middleware enables precise visibility management. You can invite colleagues to specific dashboard folders, grant &#8220;View Only&#8221; access to external stakeholders, or provide full &#8220;Editor&#8221; rights to your core DevOps team. This ensures that while everyone has the visibility they need, the core configuration remains protected.</p>



<h2 class="wp-block-heading" id="h-why-this-matters-for-mttr">Why This Matters for MTTR</h2>



<p>Ultimately, observability is about <a href="https://middleware.io/blog/how-to-reduce-mttr/">reducing Mean Time to Resolution</a> (MTTR). Every minute spent building a dashboard or navigating a UI is a minute an application is down.</p>



<p>By automating the creation of these views, Middleware is helping teams:</p>



<ul class="wp-block-list">
<li><strong>Democratize Data:</strong> You don&#8217;t need to be an &#8220;Observability Expert&#8221; to get answers. Anyone from a junior dev to a product manager can create a dashboard.</li>



<li><strong>Reduce Tool Sprawl:</strong> With metrics, logs, traces, and AI insights in one place, you stop paying for multiple tools that don&#8217;t talk to each other.</li>



<li><strong>Improve Productivity:</strong> Users can achieve an 80% increase in <a href="https://middleware.io/blog/developer-productivity/">dev productivity</a> by spending less time on &#8220;Observability Ops&#8221; and more time on features.</li>
</ul>



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<p>Stop wasting time on manual queries.<a href="https://app.middleware.io/auth/register/"> Sign up for Middleware</a> and let AI handle your dashboarding today.</p>
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<h2 class="wp-block-heading" id="h-getting-started">Getting Started</h2>



<p>To start building with AI, ensure your integrations (<a href="https://docs.middleware.io/agent-installation/kubernetes/kubernetes-agent">Kubernetes</a>, <a href="https://middleware.io/product/apm/">APM</a>, etc.) are connected so the AI has a data catalog to work with.</p>



<ol class="wp-block-list">
<li>Navigate to <strong>Dashboards → Create Dashboard</strong>.</li>



<li>Enter your objective in the <strong>Prompt Box</strong>.</li>



<li>Refine and add widgets using natural language.</li>
</ol>



<p>By moving the focus from <em>how</em> to query to <em>what</em> to monitor, we’re helping teams spend less time building dashboards and more time fixing the issues they reveal.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Ready to automate your observability? <a href="https://docs.middleware.io/workflow/dashboard-builder/build-dashboard-with-ai">Check out our documentation</a> or <a href="https://middleware.io/"></a><a href="https://app.middleware.io/auth/register/">get started for free</a>.</p>
</blockquote>



<p></p>


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<p>The era of merely &#8220;collecting everything&#8221; is over. As <a href="https://middleware.io/blog/cloud-infrastructure-guide/">cloud-native architectures</a> grow exponentially in complexity, <strong>2026</strong> is shaping up to be a critical tipping point for the <a href="https://middleware.io/blog/observability/">observability</a> landscape.</p>



<p>The focus is shifting from simply having data (logs, metrics, traces) to possessing contextual intelligence and proactive automation.</p>



<p>Industry leaders are unanimous: the future of observability in 2026 is intelligent, cost-aware, and seamlessly integrated into the developer workflow. It&#8217;s transforming from a passive diagnostic tool into an active, predictive partner in software delivery.</p>



<p>These insights come from leading DevOps, Cloud, and Infrastructure experts. Here are the top 10 observability predictions that will shape modern software operations through 2026.</p>



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<h2 class="wp-block-heading" id="h-10-observability-predictions-for-2026">10 Observability Predictions for 2026</h2>



<h3 class="wp-block-heading" id="h-1-ai-shifts-from-anomaly-detection-to-proactive-remediation-aiops-2-0">1. AI Shifts from Anomaly Detection to Proactive Remediation (AIOps 2.0)</h3>



<p>The biggest change is a shift in mindset from reactive to proactive. By <strong>2026</strong>, AI&#8217;s role will evolve past basic <a href="https://middleware.io/blog/anomaly-detection/">anomaly detection</a>. Advanced <a href="https://middleware.io/blog/what-is-ai-ops/">AIOps</a> systems will predict failures and detect subtle configuration deviations. They will also automate fixes before an incident reaches production.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;I see <strong>2026</strong> as the year when observability truly transforms from a diagnostic tool to an intelligent, predictive partner&#8230; we will no longer just respond to incidents; our monitoring suites predict problems, detect subtle configuration deviations, and automate remediation before any team member is aware.&#8221;</p><cite> <a href="https://www.linkedin.com/in/basudeba-mandal-03b7a9119/">Basudeba Mandal</a>, Cloud DevOps Lead, SLB</cite></blockquote></figure>



<p>Observability becomes an <strong>early warning system</strong> that predicts <a href="https://middleware.io/blog/fix-application-performance-issues/">performance issues</a> and recommends changes.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;Instead of alerting us after something breaks, systems will suggest possible failures based on past data. In short, AI will turn observability from reactive to proactive, which is a big shift in mindset&#8230;&#8221;</p><cite><a href="https://www.linkedin.com/in/jaswindder-kummar/">Jaswindder Kummar</a>, Director &#8211; Cloud Engineering, OSTTRA</cite></blockquote></figure>



<h3 class="wp-block-heading" id="h-2-opentelemetry-becomes-the-undisputed-de-facto-standard">2. OpenTelemetry Becomes the Undisputed, De Facto Standard</h3>



<p>The problem of vendor lock-in and siloed data is driving enterprises toward a unified solution. OpenTelemetry (OTel) will solidify its position as the default language and standard for telemetry data collection. </p>



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<p>Its vendor-neutral approach and consistency across <a href="https://middleware.io/blog/what-is-distributed-tracing/">traces</a>, metrics, and logs reduce the pain of <a href="https://docs.middleware.io/getting-started/application-instrumentation">instrumentation</a>.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;OpenTelemetry (OTel) will become the de facto standard for observability data collection by the year <strong>2026</strong> due to the need to collect data across vendors in a vendor-agnostic way&#8230; The present pain points of vendor lock-in and the difficulty of correlating siloed data types means enterprises are being pushed to OTel&#8230;&#8221;</p><cite> <a href="https://www.linkedin.com/in/paul-demott/">Paul DeMott</a>, CTO</cite></blockquote></figure>



<p>This lets teams choose the best analysis tools without being locked into a single platform.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;Yes. By <strong>2026</strong>, OpenTelemetry (OTel) will be the default language for telemetry data. Its consistency across traces, metrics, and logs reduces integration pain and allows teams to switch tools without re-instrumenting code.&#8221;</p><cite> <a href="https://www.linkedin.com/in/sibasis-padhi/">Sibasis Padhi</a>, Staff Software Engineer, Walmart Global Tech</cite></blockquote></figure>



<h3 class="wp-block-heading" id="h-3-cost-optimization-and-data-tiering">3. Cost Optimization and Data Tiering</h3>



<p>As observability data grows exponentially, the associated storage and compute costs have become unsustainable. Organizations are moving toward intelligent data tiering. </p>



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<p>Only mission-critical, real-time telemetry will remain on high-performance storage to support instant <a href="https://middleware.io/blog/debug-logging/">debugging</a> and incident response. This shift allows engineering teams to maintain rapid visibility without being overwhelmed by infrastructure expenses.</p>



<p>Lower-priority or infrequently accessed data is being pushed to low-cost archival layers, such as data lakes, where it can still support compliance, trend analysis, and deeper forensics. </p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;The primary challenge I see for 2026 is organizations failing to balance the cost of observability with the demand for complete visibility&#8230; So, by 2026 we will have to have an automated intelligent sampling capability&#8230; only store 5% of the data that is outside of this baseline or is a meaningful deviation from the baseline, greatly reducing the overall cost of the data.&#8221;</p><cite> <a href="https://www.linkedin.com/in/michael-pedrotti-seo/">Michael Pedrotti</a>, Co-founder, Ghostcap</cite></blockquote></figure>



<p><em>As a result,</em> this balance helps companies control rising costs, and <em>in turn,</em> it ensures continued access to the historical insights needed for performance tuning and business continuity.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;Teams will adopt &#8216;observability budgets&#8217;, limits on telemetry volume tied to business value&#8230; Instead of collecting everything, organizations will store only the data that helps them detect failures, improve performance, or reduce risk.&#8221;</p><cite> <a href="https://www.linkedin.com/in/sibasis-padhi/">Sibasis Padhi</a>, Staff Software Engineer, Walmart Global Tech</cite></blockquote></figure>



<h3 class="wp-block-heading" id="h-4-focus-shifts-to-business-aligned-outcomes-slos-and-user-journey-health">4. Focus Shifts to Business-Aligned Outcomes (SLOs and User-Journey Health)</h3>



<p>Observability will move from a purely technical concern to a business-critical function. Teams will shift from &#8220;collect everything&#8221; to &#8220;collect what matters.&#8221; <em>Specifically,</em> they will focus on signals tied to business value, such as SLOs, cost impact, and user-journey health.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;In <strong>2026</strong>, observability will shift from &#8216;collect everything&#8217; to &#8216;collect what matters.&#8221; Teams will focus on business-aligned signals; SLOs, cost impact, and user-journey health, instead of raw volume.&#8221; </p><cite><a href="https://www.linkedin.com/in/sibasis-padhi/">Sibasis Padhi</a>, Staff Software Engineer, Walmart Global Tech</cite></blockquote></figure>



<p>Outcome-driven dashboards will replace raw telemetry streams, clearly showing <em>what</em> is breaking and <em>why</em> it affects the customer or the bottom line.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;Observability is moving beyond just collecting logs, metrics, and traces. It&#8217;s shifting towards contextual intelligence. By <strong>2026</strong>, I think the focus will be on how fast teams can connect the dots between data points and act on them.&#8221; </p><cite><a href="https://www.linkedin.com/in/jaswindder-kummar/">Jaswindder Kummar</a>, Director &#8211; Cloud Engineering, OSTTRA</cite></blockquote></figure>



<h3 class="wp-block-heading" id="h-5-observability-deepens-with-ebpf-powered-kernel-level-visibility">5. Observability Deepens with eBPF-Powered Kernel-Level Visibility</h3>



<p>However, achieving accurate end-to-end visibility in complex cloud-native environments requires going deeper than application code. </p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Discover how <a href="https://middleware.io/blog/kubernetes-monitoring/">K</a><a>ubernetes monitoring</a> with intelligent anomaly detection can keep your clusters healthy.</p>
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<p>Emerging technologies like <a href="https://middleware.io/blog/ebpf-observability/">eBPF</a> (Extended Berkeley Packet Filter) will gain traction, offering incredibly deep visibility into the kernel and network layer without requiring heavy instrumentation or modifying application code. </p>



<p>This provides a hyper-efficient way to capture the contextual data needed for precise root cause analysis.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;If I had to pick, I&#8217;d say eBPF-based observability&#8230; eBPF gives incredibly deep visibility without heavy instrumentation. I&#8217;ve been experimenting with it, and it&#8217;s impressive.&#8221;&nbsp;</p><cite><a href="https://www.linkedin.com/in/jaswindder-kummar/">Jaswindder Kummar</a>, Director &#8211; Cloud Engineering, OSTTRA</cite></blockquote></figure>



<h3 class="wp-block-heading" id="h-6-end-to-end-visibility-demands-full-infrastructure-linkage">6. End-to-End Visibility Demands Full Infrastructure Linkage</h3>



<p>The limitations of looking only at application logs will become acutely apparent. By <strong>2026</strong>, there will be a hard switch from <a href="https://middleware.io/product/apm/">application-only monitoring</a> to full-service infrastructure linkage. </p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;By <strong>2026</strong>, the major tipping point will be a hard switch from application-only monitoring to full-service infrastructure linkage&#8230; The role of the AI is to find patterns that humans miss and that will be used to failing a user&#8217;s lag report to a specific servers CPU voltage or a failing network switch in our DE cluster.&#8221; </p><cite><a href="https://www.linkedin.com/in/honetito/">Hone John Tito</a>, Co-founder of Game Host Bros</cite></blockquote></figure>



<p>AI will be used to find patterns that link a user&#8217;s latency report directly to a failing network switch, a specific server&#8217;s CPU voltage, or a bad code deploy, creating a clear, bright picture of the <a href="https://middleware.io/blog/proactive-infrastructure-monitoring-with-middleware/">system&#8217;s health</a> across the entire stack.</p>



<h3 class="wp-block-heading" id="h-7-autonomous-ai-agents-auto-generate-root-cause-summaries-and-fixes">7. Autonomous AI Agents Auto-Generate Root Cause Summaries and Fixes</h3>



<p>The focus of AI shifts entirely from detection to <strong>remediation</strong>. AI will evolve into an <strong>Effulgent agent</strong> capable of automatically generating summaries of <a href="https://middleware.io/blog/identify-root-cause-analysis/">root cause analyses</a>.&nbsp;</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
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<p>Furthermore, these agents will suggest code or configuration changes, dynamically adjust alert thresholds, and generate valid runbook steps. This will drastically <a href="https://middleware.io/blog/how-to-reduce-mttr/">reduce MTTR</a> by eliminating manual correlation efforts.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;By <strong>2026</strong> AI will move from detecting anomalies to being an Effulgent agent auto generating summaries of root cause analysis and suggesting the changes of the code or configurations for remediation. Autonomous AI agents will be able to control the noise by dynamically adjusting the alert threshold&#8230;&#8221; </p><cite><a href="https://www.linkedin.com/in/paul-demott/">Paul DeMott</a>, CTO<strong>, </strong>Helium SEO</cite></blockquote></figure>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;Instead of searching through logs and traces, AI will spot patterns, point out the root cause, and suggest fixes before users notice any problems.&#8221; </p><cite><a href="https://www.linkedin.com/in/sibasis-padhi/">Sibasis Padhi</a>, Staff Software Engineer, Walmart Global Tech</cite></blockquote></figure>



<h3 class="wp-block-heading" id="h-8-strategic-noise-reduction-becomes-paramount">8. Strategic Noise Reduction Becomes Paramount</h3>



<p>Signal overload, too many signals, not enough meaning, is the biggest challenge facing scaling organizations. The real work for <a href="https://middleware.io/blog/what-is-devops/">DevOps</a> teams will be building smart sampling, automated noise reduction, and clear Service Level Indicators (SLIs) to cut through the data volume.&nbsp;</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;The biggest challenge I see is data overload too many signals, not enough meaning. To overcome this, I think organizations need to focus more on observability strategy to decide what actually matters&#8230;&#8221;&nbsp;</p><cite><a href="https://www.linkedin.com/in/jaswindder-kummar/">Jaswindder Kummar</a>, Director &#8211; Cloud Engineering, OSTTRA</cite></blockquote></figure>



<p>Teams will invest in unified data pipelines and clear ownership models to ensure they focus only on issues that genuinely affect customers or performance.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;The biggest challenge will be signal overload. As systems become more distributed, the volume of telemetry grows faster than the ability to interpret it. The real work will be building smart sampling, clear SLOs, and automated noise reduction&#8230;&#8221;&nbsp;</p><cite><a href="https://www.linkedin.com/in/sibasis-padhi/">Sibasis Padhi</a>, Staff Software Engineer, Walmart Global Tech</cite></blockquote></figure>



<h3 class="wp-block-heading" id="h-9-observability-is-embedded-in-the-platform-and-the-developer-workflow">9. Observability is Embedded in the Platform and the Developer Workflow</h3>



<p>Observability will be integrated deeper into the platform design and the overall software development lifecycle (SDLC). It will support key Developer Experience (DX) metrics and compliance automation.&nbsp;</p>



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<p>By providing instant, contextual feedback directly within the <a href="https://middleware.io/blog/what-is-a-ci-cd-pipeline/">CI/CD pipeline</a> and <a href="https://middleware.io/blog/devops-tools/">development tools</a>, engineers can focus on innovation rather than constantly firefighting.</p>



<figure class="wp-block-pullquote"><blockquote><p>&#8220;The complexity of cloud-native environments necessitates prioritizing actionable insights&#8230; Observability is integrated more than ever into our platform design efforts, supporting developer experience metrics, as well as metrics and compliance automation.&#8221; </p><cite><a href="https://www.linkedin.com/in/basudeba-mandal-03b7a9119/">Basudeba Mandal</a>, Cloud DevOps Lead, SLB</cite></blockquote></figure>



<h2 class="wp-block-heading" id="h-how-to-prepare-for-2026-observability">How to Prepare for 2026 Observability</h2>



<ul class="wp-block-list">
<li>Invest in AI-powered <a href="https://middleware.io/platform/">observability platforms</a> that unify metrics, logs, traces, and data/AI monitoring.</li>



<li>Adopt <a href="https://middleware.io/blog/what-is-opentelemetry/">OpenTelemetry</a> as the standard for consistent, portable telemetry collection.</li>



<li>Focus on scalable solutions that balance visibility depth with cost control.</li>



<li>Prioritize security observability to enforce compliance and detect threats early.</li>



<li>Enhance Kubernetes and edge monitoring with smart anomaly detection and predictive analytics.</li>



<li>Embed observability deeply into data and AI workflows for continuous reliability and trustworthiness.</li>
</ul>



<h2 class="wp-block-heading" id="h-conclusion-the-path-forward">Conclusion: The Path Forward</h2>



<p>The path through 2026 will demand a strategic, disciplined approach to observability. The organizations that succeed will be those that embrace standardization (OTel), prioritize intelligence (AIOps/eBPF), and enforce cost-aware strategies (intelligent sampling and observability budgets).&nbsp;</p>



<p>The journey is no longer about collecting data; it&#8217;s about generating affordable, actionable, and automated insights that drive tangible business outcomes.</p>



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 </p>
  <a href="https://middleware.io/demo-request/" target="_blank" rel="noopener"><button class="primary white">Request Your Free Demo</button></a>

</div>

</div>


Discover the top observability trends for 2026, including proactive AIOps, OTel adoption, cost-aware telemetry, and deeper, intelligent insights.

Observability Predictions for 2026

Learn how proactive alerts for slow APIs prevent downtime, reduce latency issues, protect SLAs, and keep your user experience fast and reliable.

Proactive Alerts for Slow APIs

Troubleshoot Kubernetes workloads efficiently with Middleware. Detect CrashLoopBackOff, OOMKilled, and FailedMount errors in real time and reduce downtime.

Troubleshooting Common Kubernetes Workloads Issues with Middleware

This guide explains SNMP monitoring, how SNMP managers and agents work, key metrics to track, SNMPv3 setup, and best practices to keep your network healthy and prevent outages.

SNMP Monitoring: What It Is and How It Works?

User Experience Monitoring helps you track real user behavior, detect problems faster, and improve performance for a smoother, more engaging digital experience.

Real User Monitoring (RUM): 7 Ways to Improve User Experience

Predict and resolve issues before users feel the impact. Middleware’s AI-powered observability delivers instant root-cause insights, faster fixes, and fewer incidents.

Resolve Root Cause Issues with Middleware Before User Impact

Discover how shift-left testing boosts software quality by catching bugs early. See how Middleware enables faster, error-free releases with real-time insights.

Shift-Left Testing: What It Means, Why It Matters, and How to Implement It

Compare OpenTelemetry Collector vs Agent, learn when to use each, and see how Middleware simplifies observability with unified telemetry insights.

OpenTelemetry Collector vs Agent: How to Choose the Right Telemetry Approach

Step-by-step guide to identify root causes, capture real user sessions, and resolve production errors faster with Middleware and intelligent OpsAI insights.

From Alerts to Action: Debugging Live Production Problems

Detect, prevent, and fix DNS issues in real time with Middleware’s intelligent monitoring for faster, reliable, and always-available websites.

How Middleware Detects and Resolves DNS Issues


<p>KubeCon + CloudNativeCon North America 2025, taking place in Atlanta, Georgia, from November 10–13, 2025, is the must-attend gathering for anyone passionate about cloud-native <a href="https://middleware.io/blog/observability/">observability</a>, AI-powered DevOps, platform engineering, and next-gen infrastructure innovation.</p>



<h2 class="wp-block-heading" id="h-the-excitement-around-kubecon-cloudnativecon-2025">The Excitement Around KubeCon + CloudNativeCon 2025</h2>



<p>The Cloud Native Computing Foundation (CNCF)’s flagship event, <a href="https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/">KubeCon + CloudNativeCon North America 2025</a>, continues to be the heartbeat of the <a href="https://middleware.io/blog/cloud-infrastructure-guide/">cloud-native ecosystem</a>. It attracts thousands of developers, DevOps engineers, SREs, and platform teams worldwide.</p>



<p>This year’s discussions will focus on observability, <a href="https://middleware.io/blog/platform-engineering/">platform engineering</a>, and AI-driven DevOps automation, reflecting the evolution of cloud-native systems. </p>



<p>Here’s what to look forward to at this year’s Atlanta edition and how Middleware is joining the conversation.</p>



<h2 class="wp-block-heading" id="h-why-kubecon-matters-for-cloud-native-builders">Why KubeCon Matters for Cloud-Native Builders</h2>



<p>For attendees in Atlanta or joining virtually, KubeCon North America 2025 is where open-source innovation meets production-grade Kubernetes experience.</p>



<p>KubeCon brings together a vibrant global community, fostering collaboration among developers, platform engineers, SREs, and business leaders. KubeCon US serves as a fertile ground for launching and advancing open-source CNCF projects, enabling knowledge exchange and community-driven innovation. </p>



<p>Being part of KubeCon means immersing yourself in the <a href="https://middleware.io/blog/kubernetes-monitoring/">Kubernetes</a> and observability community, gaining insights from production-scale deployments and contributing to the future trajectory of cloud-native technologies.</p>



<h2 class="wp-block-heading" id="h-key-themes-to-watch-at-kubecon-2025">Key Themes to Watch at KubeCon 2025</h2>



<h3 class="wp-block-heading" id="h-unified-observability-takes-center-stage">Unified Observability Takes Center Stage</h3>



<p>The conference spotlights the shift from fragmented monitoring tools to unified observability platforms that integrate metrics, logs, and traces. </p>



<p><a href="https://middleware.io/blog/what-is-opentelemetry/">OpenTelemetry</a> remains a pivotal standard in consolidating telemetry data, enabling teams to gain real-time debugging insights and optimize performance across distributed systems. </p>



<p>As more teams adopt OpenTelemetry for standardized telemetry collection, unified observability remains a key driver of performance and reliability in 2025.</p>



<h3 class="wp-block-heading" id="h-ai-driven-automation-and-opsai">AI-Driven Automation and OpsAI</h3>



<p>AI-driven observability (OpsAI) is transforming how DevOps teams <a href="https://middleware.io/blog/anomaly-detection/">detect anomalies</a>, predict failures, and maintain uptime with minimal manual intervention. </p>



<p>Expect to see deep dives into how AI models are now powering proactive incident detection, automated <a href="https://middleware.io/blog/identify-root-cause-analysis/">root cause analysis</a>, and self-healing infrastructure.</p>



<p>Sessions at KubeCon 2025 will explore how combining AIOps, predictive analytics, and real-time telemetry can reduce operational burden, improve reliability, and help teams move toward truly autonomous cloud-native operations.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>👉 Learn more about <a href="https://middleware.io/product/ops-ai/">OpsAI by Middleware</a>, the AI-driven engine that detects and correlates system-wide issues automatically.</p>
</blockquote>



<h3 class="wp-block-heading" id="h-developer-experience-and-platform-engineering">Developer Experience and Platform Engineering</h3>



<p>Platform engineering continues to redefine developer workflows by integrating observability directly into Internal Developer Platforms (IDPs), making Kubernetes management simpler and more efficient.</p>



<p>Teams are moving toward self-service platforms that reduce cognitive load, automate repetitive DevOps tasks, and enable developers to focus on building rather than managing infrastructure.</p>



<p>At KubeCon 2025, expect sessions highlighting how platform engineering, observability, and automation converge to improve developer productivity, accelerate deployments, and deliver better visibility into production systems, all while maintaining reliability and security across environments.</p>



<h3 class="wp-block-heading" id="h-sustainability-and-cost-optimization">Sustainability and Cost Optimization</h3>



<p>As organizations scale their cloud-native infrastructure, sustainability and cost control have become top priorities.</p>



<p>Expect sessions at KubeCon Atlanta 2025 to address <a href="https://middleware.io/blog/cloud-cost-optimization/">cloud cost optimization</a>, sustainable operations, and energy efficiency through smarter observability.</p>



<p>With cloud expenses continuing to rise, teams are turning to observability-driven insights to identify underutilized resources, improve workload placement, and balance performance with environmental impact.</p>



<p>Speakers and panelists will explore practical strategies for building cost-efficient Kubernetes environments, optimizing resource utilization, and leveraging AI-driven observability for real-time visibility into performance and spending.</p>



<h2 class="wp-block-heading" id="h-must-attend-observability-sessions-at-kubecon-2025">Must-Attend Observability Sessions at KubeCon 2025</h2>



<p>If you’re attending KubeCon + CloudNativeCon North America 2025 in Atlanta, the following sessions are a must for anyone passionate about cloud-native observability, Kubernetes performance, and AI-powered operations. </p>



<p>These talks highlight how leading organizations are solving real-world observability challenges at scale.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>For attendees focused on <strong>observability, AIOps, and platform performance</strong>, these sessions are packed with insights from the world’s leading cloud-native teams.</p>
</blockquote>



<figure class="wp-block-table"><table class="has-fixed-layout"><tbody><tr><td><strong>Session Title</strong></td><td><strong>Speakers</strong></td><td><strong>Description</strong></td></tr><tr><td>1000 Clusters, 1 Brain: Approach to Self-Healing Using AIOps</td><td>Vikram Venkataraman (AWS), Srikanth Rajan (Salesforce)</td><td>How Salesforce uses generative AI and multi-agent systems to manage and auto-remediate massive clusters.</td></tr><tr><td>Container Runtime Customization at Netflix: A Case Study With NRI and OCI Hooks</td><td>Erikson Tung (Netflix)</td><td>Insights into Netflix’s global container platform evolution leveraging NRI and OCI runtime hooks.</td></tr><tr><td>In-Place Pod Resize in Kubernetes: Dynamic Resource Management Without Restarts</td><td>Tim Allclair &amp; Mofi Rahman (Google)</td><td>New K8s features for dynamic resource allocation without impacting running applications.</td></tr><tr><td>TikTok’s IPv6 Journey to Cilium: Pitfalls and Lessons Learned</td><td>Giri Kuncoro &amp; Joseph Pallamidessi (TikTok)</td><td>Migration experiences running IPv6-only clusters and rebuilding observability with Cilium.</td></tr><tr><td>Security Theater or Real Defense? Navigating Open Source Security in a Cloud Native World</td><td>Rotem Refael, Constanze Roedig, Megan Wolf, Stefana Muller, Oshrat Nir</td><td>Panel dissecting open source security with real-world production failures and lessons.</td></tr><tr><td>Observability Day (Co-located Event)</td><td>Multiple CNCF Maintainers</td><td>Deep technical sessions: OpenTelemetry, distributed tracing, logging, metrics pipelines, and office hours.</td></tr></tbody></table></figure>



<h2 class="wp-block-heading" id="h-middleware-s-perspective-simplifying-cloud-native-observability">Middleware’s Perspective: Simplifying Cloud-Native Observability</h2>



<p>At <strong>KubeCon + CloudNativeCon North America 2025 in Atlanta</strong>, <strong>Middleware</strong> will join the global cloud-native community to showcase how <strong>unified observability</strong> can help teams simplify complexity across modern infrastructure.</p>



<p>Today’s DevOps and platform engineering teams juggle multiple monitoring tools, siloed telemetry data, and <a href="https://middleware.io/blog/what-is-alert-fatigue/">alert fatigue</a>. Middleware solves this by offering a single pane of glass for metrics, logs, and traces powered by AI-driven insights and built on OpenTelemetry standards.</p>



<p>Our platform is designed for speed, simplicity, and scalability helping teams move beyond fragmented observability stacks. Whether you’re managing multi-cluster Kubernetes environments or optimizing cloud workloads for cost and performance, Middleware gives you the visibility and automation needed to stay ahead of issues before they impact users.</p>



<p>During KubeCon Atlanta 2025, the <a href="https://middleware.io/">Middleware</a> team will be engaging with developers, SREs, and platform engineers to explore:</p>



<ul class="wp-block-list">
<li>How to <strong>standardize observability data collection</strong> with OpenTelemetry.</li>



<li>How <strong>AI-enhanced alerting</strong> can reduce noise and speed up resolution times.</li>



<li>How <strong>cost-efficient observability</strong> can align with sustainability goals.</li>
</ul>



<p>Middleware’s commitment aligns with CNCF’s mission fostering vendor-neutral, open-source-first observability ecosystems that empower engineering teams to deliver reliable and sustainable software at scale.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p><a href="https://app.middleware.io/auth/register/">Visit Middleware</a> at KubeCon NA 2025 to see live demos, connect with our team, and discover how unified observability can transform your DevOps strategy.</p>
</blockquote>



<h3 class="wp-block-heading" id="h-connect-our-team-at-kubecon">Connect Our Team at KubeCon </h3>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="719" height="235" src="https://middleware.io/backend/wp-content/uploads/2025/10/middleware-kubecon-usa-team.webp" alt="Middleware Team visiting Kubecon USA 2025" class="wp-image-13047"/></figure>



<ul class="wp-block-list">
<li><a href="https://www.linkedin.com/in/laduramvishnoi/" target="_blank" rel="noreferrer noopener">Laduram Vishnoi</a>, Founder &amp; CEO, Middleware</li>



<li><a href="https://www.linkedin.com/in/sawaramsuthar/" target="_blank" rel="noreferrer noopener">Sam Suthar</a>, Founding Director, Middleware</li>



<li><a href="https://www.linkedin.com/in/devmraj/" target="_blank" rel="noreferrer noopener">Meghraj Choudhary</a>, Senior Principal Engineer, Middleware</li>



<li><a href="https://www.linkedin.com/in/bhogayatakb/" target="_blank" rel="noreferrer noopener">Keval Bhogayata</a>, Principal Engineer, Middleware</li>
</ul>



<h2 class="wp-block-heading" id="h-the-road-ahead-how-kubecon-2025-will-shape-observability">The Road Ahead: How KubeCon 2025 Will Shape Observability</h2>



<p>The innovations and <a href="https://middleware.io/blog/observability/trends/">Observability trends</a> emerging from <a href="https://middleware.io/events/kubecon-na-2025/">KubeCon North America 2025</a> are expected to drive tighter integration between AI, DevOps, and open-source observability stacks. </p>



<p>The future of <a href="https://middleware.io/whitepaper/cloud-native-observability-the-new-normal-for-enterprises/">cloud-native observability</a> points to enhanced automation, deeper telemetry standardization, and collaborative community-driven development. Middleware is committed to advancing this vision by fostering open, accessible, and intelligent observability solutions.</p>



<p>Check out the page for all the details about <a href="https://middleware.io/events/kubecon-na-2025/" target="_blank" rel="noreferrer noopener">the Middleware</a> team coming to <a href="https://middleware.io/events/kubecon-na-2025/">KubeCon NA</a>.</p>



<p>Stay tuned as Middleware brings you insights, updates, and learnings from KubeCon + CloudNativeCon North America 2025, shaping the future of observability together.</p>



<h3 class="wp-block-heading">FAQ: KubeCon North America 2025</h3>


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				<h3>When and where is KubeCon + CloudNativeCon North America 2025?
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<p>It will be held from November 10–13, 2025, in Atlanta, Georgia.</p>

			</div>
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				<h3>What are the main themes of KubeCon 2025?</h3>				<div>
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<p>Unified observability, AI-driven DevOps automation, developer experience, and sustainability in cloud-native systems.</p>

			</div>
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				<h3>How is Middleware participating in KubeCon 2025?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>Middleware is participating as a sponsor at KubeCon + CloudNativeCon North America 2025. The team will showcase its AI-powered observability and OpsAI platform and connect with the cloud-native community.</p>

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Explore key observability, AI, and platform engineering insights from KubeCon + CloudNativeCon North America 2025 in Atlanta with Middleware.

What to Expect at KubeCon North America 2025: The Future of Cloud-Native Observability

Discover how Middleware simplifies identifying Root Cause Analysis in complex distributed systems using AI-powered insights, unified visibility, and faster RCA.

Identify Root Cause Analysis in Distributed Systems

Unify synthetic monitoring and distributed tracing with Middleware to proactively detect issues, reduce MTTR, and optimize your app’s performance

Unifying Synthetic Monitoring and Distributed Tracing for Proactive Incident Detection

Discover how Middleware helps you monitor infrastructure proactively with AI alerts, real-time dashboards, and deep visibility to prevent costly outages.

Proactive Infrastructure Health Monitoring Using Middleware

Tired of juggling multiple tools? Middleware unifies logs, metrics, traces, and alerts in one platform, speeding up incident resolution and reducing costs.

Why Engineering Teams are Replacing 3–4 Tools with Middleware


<p>ServiceNow Cloud Observability, formerly Lightstep, is reaching its End of Life (EOL) on March 1, 2026. To avoid disruption in <a href="https://middleware.io/blog/observability/">observability</a> and performance monitoring, organizations should plan a ServiceNow migration to Middleware, a modern observability platform that delivers full-stack visibility and AI-driven insights.&nbsp;</p>



<p>This guide offers a clear roadmap to help organizations transition smoothly, highlighting Middleware’s unique advantages as a modern observability platform.</p>



<div class="table-of-content" id="accordian">
<div class="toc-heading" data-toggle="collapse" data-target="#toc">
Table of Contents
</div> <div id="toc" class="collapse" data-parent="#accordian">
<div class="toc-list">
</div>
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<h2 class="wp-block-heading" id="h-why-plan-servicenow-cloud-observability-migration">Why Plan ServiceNow Cloud Observability Migration?</h2>



<ul class="wp-block-list">
<li><strong>End of Support:</strong> After March 1, 2026, ServiceNow Cloud Observability will no longer receive updates or support. Planning a ServiceNow migration now ensures uninterrupted monitoring and operational continuity.</li>



<li><strong>Strategic Shift: </strong>ServiceNow is shifting focus toward Service Observability and Service Reliability Management, without a direct replacement for <a href="https://middleware.io/whitepaper/cloud-native-observability-the-new-normal-for-enterprises/">Cloud Observability</a>.</li>



<li><strong>Business Continuity:</strong> Migrating to a supported observability platform like Middleware ensures uninterrupted operational efficiency and system health.</li>
</ul>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>👉 Don’t wait until ServiceNow Cloud Observability sunsets — <a href="https://app.middleware.io/auth/register/">Start your<strong> </strong>ServiceNow Migration</a><strong> </strong>now and secure uninterrupted visibility with Middleware.</p>
</blockquote>



<h2 class="wp-block-heading" id="h-middleware-the-superior-choice-for-observability">Middleware: The Superior Choice for Observability</h2>



<h3 class="wp-block-heading" id="h-unified-observability-across-the-stack">Unified Observability Across the Stack</h3>



<p>When planning a ServiceNow migration, Middleware provides true end-to-end visibility, including AI-powered log analysis and <a href="https://middleware.io/blog/kubernetes-observability/">Kubernetes observability</a>, enabling teams to detect issues across <a href="https://middleware.io/blog/cloud-infrastructure-guide/">cloud infrastructure</a>, applications, databases, and containers proactively.</p>



<p>All within a single, intuitive platform boasting over 200 integrations, so teams can instantly correlate events and trace root causes from business KPIs to individual requests.&nbsp;</p>



<p>It also dramatically reduces incident resolution times by working from a unified “single pane of glass” instead of piecing together siloed data sources.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>👉 See Middleware in Action – <a href="https://middleware.io/demo-request/">Book a Demo</a></p>
</blockquote>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1600" height="908" src="https://middleware.io/backend/wp-content/uploads/2025/10/Migrating-from-ServiceNow-Lightstep-to-middleware.webp" alt="Migrating from ServiceNow Lightstep to middleware" class="wp-image-12734"/></figure>



<h3 class="wp-block-heading" id="h-unified-data-ingestion">Unified Data Ingestion</h3>



<p>Middleware’s purposeful telemetry collection via its data pipelines ensures only meaningful data is ingested, optimizing observability costs while maintaining complete visibility.</p>



<p>Complete native <a href="https://middleware.io/blog/what-is-opentelemetry/">open-telemetry</a> compatibility, rapid <a href="https://docs.middleware.io/agent-installation/kubernetes/auto-instrumentation">auto-instrumentation</a> for all popular languages, and uninterrupted ingestion through established agents. It consolidates all observability signals efficiently, controlling data retention and cost, and accommodating petabyte-scale telemetry without friction.</p>



<h3 class="wp-block-heading" id="h-ai-powered-insights">AI- Powered Insights</h3>



<p>By embedding AI and machine learning, Middleware’s OpsAI provides full-stack observability, automatically detects issues, generates and prioritizes alerts to reduce <a href="https://middleware.io/blog/what-is-alert-fatigue/">alert fatigue</a>, and even fixes problems without manual intervention. This dramatically reduces MTTR and frees engineering teams to focus on strategic work.</p>



<p>Its AI engine not only <a href="https://middleware.io/blog/anomaly-detection/">detects anomalies</a> but also creates and prioritizes alerts intelligently, reducing noise and ensuring teams focus on what truly matters. It also identifies frequent emerging dangers, while AI-operated diagnostic features reduce problems by 80% before they are analyzed.</p>



<p>See AI in action with real-world error tracking by exploring our blog on<a href="https://middleware.io/blog/github-commit-ownership-error-tracking/"> GitHub Commit Ownership &amp; Error Tracking</a> and learn how teams can quickly identify and resolve issues.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1140" height="655" src="https://middleware.io/backend/wp-content/uploads/2025/10/Migrate-Servicenow-Lightstep-to-Middleware-for-better-error-tracking.webp" alt="Migrate Servicenow Lightstep to Middleware for better error tracking" class="wp-image-12735"/></figure>



<h3 class="wp-block-heading" id="h-smooth-servicenow-migration-to-middleware">Smooth ServiceNow Migration to Middleware</h3>



<p>Keeping in mind the enterprise change, the middleware provides rapid, low-risk onboarding with easy setup. It also automates source mapping, provides seamless dual-installed validation, includes <a href="https://docs.middleware.io/quickstart">comprehensive documentation</a>, and offers direct ServiceNow Lightstep migration support from platform experts. It also ensures that a complex environment can be made smooth and error-free without compromising on complexity or compliance.</p>



<h3 class="wp-block-heading" id="h-scalability-and-flexibility">Scalability and Flexibility</h3>



<p>Built on a modern, elastic architecture, middleware supports organizations from startup scale to large enterprise deployments, providing reliability and scalability. It also has tenant protection dynamically for millions of telemetry events per second.&nbsp;</p>



<h3 class="wp-block-heading" id="h-predictable-pricing">Predictable Pricing</h3>



<p>Middleware helps companies slash observability spend without compromising visibility, with a transparent, pay-as-you-use <a href="https://middleware.io/pricing/">pricing</a> model that scales with business needs. Organizations migrating from ServiceNow Cloud Observability can reduce spend with Middleware’s pay-as-you-use pricing, scaling costs naturally as the business grows. Organizations can <a href="https://middleware.io/customers/mindorigin/">reduce costs by up to 75% </a>compared to legacy tools.</p>



<p>It provides transparent metered billing for only the data and features used, along with complete visibility into costs. This enables organizations of any size to optimize observability spending, forecast budgets, and avoid surprise overages or locked-in minimums.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>For more details on migrating, see the Middleware’s guide:<br>👉<a href="https://middleware.io/blog/switch-to-middleware-day0-week4/"> What to Expect When You Switch to Middleware (Day 0 – Week 4)</a></p>
</blockquote>



<h2 class="wp-block-heading" id="h-servicenow-cloud-observability-vs-middleware">ServiceNow Cloud Observability vs. Middleware</h2>



<figure class="wp-block-table"><table class="has-fixed-layout"><tbody><tr><td>Feature</td><td>ServiceNow Cloud Observability</td><td>Middleware</td></tr><tr><td>Support Status</td><td>End of Life by March 1, 2026</td><td>Active, full support</td></tr><tr><td>OpenTelemetry Integration</td><td>Limited</td><td>Comprehensive</td></tr><tr><td>AI-Driven Insights</td><td>Basic</td><td>Advanced analytics</td></tr><tr><td>Real User Monitoring (RUM)</td><td>Not available</td><td>Available</td></tr><tr><td>ServiceNow Migration Assistance</td><td>None</td><td>Dedicated teams</td></tr><tr><td>Data Retention Policy</td><td>Proprietary limits</td><td>Transparent, configurable</td></tr><tr><td>Pricing Model</td><td>Proprietary, contract-based</td><td>Transparent, usage-based</td></tr><tr><td>Deployment Flexibility</td><td>SaaS only</td><td>Cloud &amp; self-hosted options</td></tr><tr><td>API &amp; SDK Coverage</td><td>Enterprise-focused, some gaps</td><td>Full SDK &amp; API support</td></tr></tbody></table></figure>



<h2 class="wp-block-heading" id="h-benefits-of-migrating-to-middleware">Benefits of Migrating to Middleware</h2>



<h3 class="wp-block-heading" id="h-1-lower-costs-with-pay-as-you-go">1. Lower Costs with Pay-As-You-Go</h3>



<p>Transparent, use-based pricing of middleware means that organizations only pay for the data they actually ingest and analyze. It eliminates expensive upfront commitments and reduces unnecessary overpricing.&nbsp;</p>



<p>This consumption-driven model scales with your business. You can plan your budget easily and <a href="https://middleware.io/blog/reduce-observability-costs/">reduce observability costs</a> by up to 75% compared to legacy tools.</p>



<p> This empowers you to adapt expenses by gaining deep insights and operational controls.</p>



<h3 class="wp-block-heading" id="h-2-avoid-vendor-lock-in">2. Avoid Vendor Lock-In</h3>



<p>Built on open standards like OpenTelemetry, Middleware makes your telemetry data fully portable and avoids silos or vendor lock-in. This freedom enables you to manage your data lifecycle and transition to new tools without a complicated ServiceNow migration process.&nbsp;</p>



<p>Additionally, demonstrate your observability strategy in a rapidly evolving cloud-native scenario, with future-proofing flexibility and reduced operational risk.</p>



<h3 class="wp-block-heading" id="h-3-faster-issue-resolution-with-ai">3. Faster Issue Resolution with AI</h3>



<p>Middleware unites all telemetry logs, metrics, traces, and KPIs in a single, correlated context rich in the art of AI analytics. It also automatically detects issues and guides engineers directly to the root causes.&nbsp;</p>



<p>This intelligent, end-to-end observability exposes events and accelerates troubleshooting, <a href="https://middleware.io/blog/how-to-reduce-mttr/">reducing the MTTR</a> by up to 80% and minimizing the financial impact of downtime on your business.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1600" height="826" src="https://middleware.io/backend/wp-content/uploads/2025/10/Migrate-from-ServiceNow-lightstep-for-end-to-end-observability.webp" alt="Migrate from ServiceNow lightstep for end-to-end observability" class="wp-image-12736"/></figure>



<h3 class="wp-block-heading" id="h-4-boost-developer-productivity">4. Boost Developer Productivity</h3>



<p><a href="https://middleware.io/product/ops-ai/">Ops AI</a> of middleware not only automatically detects issues but also provides actionable solutions and generates a PR. Developers and SREs spend less time pursuing symptoms and more time increasing team efficiency and delivering flexible, high-quality software rapidly.</p>



<h3 class="wp-block-heading" id="h-5-flexible-deployment-options">5. Flexible Deployment Options</h3>



<p>Recognizing the diverse needs of various ventures, middleware enables flexible deployment across public clouds, private clouds, and hybrid environments. It also supports fully self-hosted configurations, equipped with a safe multi-tenant architecture and comprehensive compliance certificates.&nbsp;</p>



<p>This adaptability ensures that observability with your existing infrastructure strategy can be effectively integrated with strategies for performance, security, or governance.</p>



<h2 class="wp-block-heading" id="h-migration-support-and-services">Migration Support and Services</h2>



<p>Organizations can start by <a href="https://app.middleware.io/auth/register/">trying Middleware for free</a> to explore its features and understand how it fits into their environment. Once ready to migrate from ServiceNow, dedicated customer success and technical teams are available to guide the transition, ensuring a smooth and low-risk onboarding.&nbsp;</p>



<p>Detailed documentation and training resources are also provided to help teams get up to speed quickly and confidently, ensuring a seamless ServiceNow migration process that maintains business continuity and minimizes risk.</p>



<div class="container-cta">
  
<div><h3>✨Try Middleware Risk-Free</h3>
  <p>Explore AI-driven alerts, OpsAI, and full observability across cloud, applications, and Kubernetes—no commitment required.
 </p>

 <a href="https://app.middleware.io/auth/register/" target="_blank" rel="noopener"><button class="primary white">Start Free Trial</button></a>
</div>

</div>



<h3 class="wp-block-heading" id="h-conclusion">Conclusion</h3>



<p>Migrating from ServiceNow Cloud Observability to Middleware is not just necessary to avoid disruption; a ServiceNow migration is a strategic step to enhance full-stack observability and AI-driven monitoring. The integrated, AI-driven platform of middleware provides unique operational capabilities through faster issue resolution, deeper insights, and adaptive scalability.&nbsp;</p>



<p>A smooth ServiceNow Lightstep migration process, transparent pricing, and dedicated expert support ensure that the business not only maintains continuity but also gains a competitive advantage through increased reliability, cost optimization, and developer productivity. Choosing middleware means predicting your observability strategy today to run continuous success tomorrow.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>👉 <a href="https://middleware.io/contact-us/">Contact us</a> today for a ServiceNow migration consultation or schedule a personalized demo.</p>
</blockquote>



<p><br></p>


Migrate from ServiceNow Cloud Observability to Middleware for seamless AI-driven monitoring, faster issue resolution, and flexible, cost-efficient observability.

Migration From ServiceNow Cloud Observability to Middleware


<p>High API latency frustrates users and can drive them to competitors. Monitoring and reducing latency is essential for a smooth user experience and system reliability.</p>



<p>For this reason, <a href="https://middleware.io/blog/how-dem-improve-user-journey/">user experience</a> and system reliability depend on the latency. Most of the time, the problem originates from API latency, which poor backend code, slow databases, or slow networks can cause.</p>



<p>The good news is that with Middleware APM, you don’t have to guess where the problem is coming from. You can <a href="https://middleware.io/blog/latency-reduction/">detect latency</a> issues early, <a href="https://middleware.io/blog/identify-root-cause-analysis/">identify the root cause</a>, and resolve them before they affect users. In this article, you’ll learn how to use <a href="https://middleware.io/product/apm/">Middleware APM</a> to detect and reduce API latency.</p>



<div class="table-of-content" id="accordian">
<div class="toc-heading" data-toggle="collapse" data-target="#toc">
Table of Contents
</div> <div id="toc" class="collapse" data-parent="#accordian">
<div class="toc-list">
</div>
</div>
</div>



<h2 class="wp-block-heading" id="h-what-is-api-latency">What is API latency?</h2>



<p>API latency refers to the time it takes for an API to receive a request, process it, and send a response back to the user. It displays the wait time for users accessing your API.</p>



<p>Many people often confuse latency and throughput, so let me explain the difference between them. You can determine your system&#8217;s capacity to handle calls by examining its throughput, which indicates the number of calls it can process per unit of time, and its latency, which measures the time it takes to process each call. </p>



<p>Some systems have both high throughput and high latency. This means that they can handle a large number of requests simultaneously, but each one takes a considerable amount of time.</p>



<p>Some of the causes of high API latency include:</p>



<ul class="wp-block-list">
<li><strong>Network delays</strong>: Problems with routing, physical distance, and network congestion</li>



<li><strong>Third-party packages</strong>: Calls to external APIs and service integrations</li>



<li><strong>Backend processing issues</strong>: Insufficient server resources and scaling problems</li>



<li><strong>Infrastructure limitations</strong>: Insufficient server resources and scaling problems</li>
</ul>



<p>When you understand the causes of latency, it’ll be easier for you to handle it effectively.</p>



<h2 class="wp-block-heading" id="h-how-to-use-middleware-apm-to-fix-api-latency-problems">How to Use Middleware APM to Fix API Latency Problems</h2>



<p>With the aid of middleware&#8217;s extensive monitoring features, you can see how well your API is performing in real-time and spot problems before they become serious.</p>



<p>In this section, we’ll go through the complete process of setting up Middleware <a href="https://middleware.io/blog/reducing-error-rates-nodejs-with-apm/">APM for a Node.js application</a>. You’ll learn how to install and configure the <a href="https://docs.middleware.io/getting-started/deploying-the-agent">monitoring agent</a> and utilize Middleware’s dashboard to identify and <a href="https://middleware.io/blog/fix-application-performance-issues/">resolve performance issues</a> to their root cause.</p>



<div class="container-cta">
  
<div><h3>Detect &#038; Fix API Latency Instantly</h3>
  <p>Start monitoring your APIs in real time with Middleware APM. Identify slow endpoints, trace issues, and optimize performance effortlessly.
 </p>
  <a href="https://app.middleware.io/auth/register/" target="_blank" rel="noopener"><button class="primary white">Monitor My API</button></a>
</div>

</div>



<p><strong>Note</strong>: This approach also works for other languages. The only difference is the installation and configuration. You can use the ideas from this guide to work with different languages.</p>



<h3 class="wp-block-heading" id="h-set-up-a-simple-project">Set Up a Simple Project</h3>



<p>We need an application to work with before we can <a href="https://middleware.io/blog/api-monitoring/">monitor API</a> latency. A Node.js CRUD API that handles user data will be used for this demonstration. </p>



<p>We will later on include a couple of endpoints that simulate high and low latency scenarios. This will help us identify how different types of operations are displayed in the Middleware monitoring dashboard.</p>



<p>Here’s how to set up the project:</p>



<p><strong>1. Install dependencies</strong></p>



<p>You need to install Express.js, cors (if you&#8217;re using it with a frontend app), and Nodemon (to restart the server while you work on it) if you&#8217;re using Node.js.</p>



<div class="code-block content-copy">
<div class="pre" id="code-blog"><pre><code>
npm init -y
npm install express cors nodemon
</code>
</pre>
</div>
<a class="copy-btn" id="first-button"></a>
</div>



<p><strong>2. Update package.json scripts</strong></p>



<div class="code-block content-copy">
<div class="pre" id="code-blog"><pre><code>
"scripts": {
  "dev": "nodemon server.js"
}
</code>
</pre>
</div>
<a class="copy-btn" id="first-button"></a>
</div>



<p><strong>3. Create a server.js file and add the code</strong></p>



<div class="code-block content-copy">
<div class="pre" id="code-blog"><pre><code>
const express = require('express');
const cors = require('cors');

const app = express();
const PORT = 4000;

app.use(cors());
app.use(express.json());

let users = [];
let userID = 1;

app.post('/users', (req, res) => {
    const {name, email} = req.body;
    const newUser = {id: userID++, name, email}
    users.push(newUser);
    res.status(201).json(newUser);
});

app.get('/users', (req, res) => {
    res.json(users);
});

app.get('/users/:id', (req, res) => {
    const user = users.find(u => u.id === parseInt(req.params.id));
    if(!user) return res.status(404).json({message: 'User not found'});
    res.json(user);
});

app.put("/users/:id", (req, res) => {
  const user = users.find(u => u.id === parseInt(req.params.id));
  if (!user) return res.status(404).json({ message: "User not found" });

  const { name, email } = req.body;
  user.name = name || user.name;
  user.email = email || user.email;
  res.json(user);
});

app.delete("/users/:id", (req, res) => {
  users = users.filter(u => u.id !== parseInt(req.params.id));
  res.json({ message: "User deleted" });
});

app.listen(PORT, () => {
    console.log(`Server is running on http://localhost:${PORT}`);
});
</code>
</pre>
</div>
<a class="copy-btn" id="first-button"></a>
</div>



<p>This includes endpoints for adding, retrieving, updating, and deleting users.</p>



<p><strong>4. Start the application</strong></p>



<div class="code-block content-copy">
<div class="pre" id="code-blog"><pre><code>
npm run dev
</code>
</pre>
</div>
<a class="copy-btn" id="first-button"></a>
</div>



<p><strong>5. Test the endpoints</strong></p>



<p>Use Postman or your preferred API client to verify that the routes are functioning correctly.</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="1268" height="792" src="https://middleware.io/backend/wp-content/uploads/2025/10/postman-api-testing.webp" alt="Testing Node.js API endpoints using Postman" class="wp-image-12673"/></figure>



<p>Now that the API is up and running, we can add Middleware APM and begin real-time tracking of latency.</p>



<h3 class="wp-block-heading" id="h-install-and-configure-middleware-agent">Install and Configure Middleware Agent</h3>



<p>Now that our API is up and running, we&#8217;ll add Middleware APM to monitor the app&#8217;s performance. The middleware agent will automatically collect metrics, traces, and performance data.</p>



<p><strong>1. Create a Middleware account and get your API key</strong></p>



<ul class="wp-block-list">
<li>Sign up at <a href="https://middleware.io">middleware.io</a></li>



<li>Log in to your dashboard, navigate to your profile, then click “API Key” to get your API key</li>
</ul>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1197" height="635" src="https://middleware.io/backend/wp-content/uploads/2025/10/middleware-dashboard-api-key.webp" alt="Accessing Middleware API key from dashboard" class="wp-image-12674"/></figure>



<ul class="wp-block-list">
<li>You’ll need this key to authenticate your application with Middleware’s servers</li>
</ul>



<p><strong>2. Install the Middleware agent</strong></p>



<p>In your project directory, run:</p>



<div class="code-block content-copy">
<div class="pre" id="code-blog"><pre><code>
npm install @middleware.io/node-apm --save
</code>
</pre>
</div>
<a class="copy-btn" id="first-button"></a>
</div>



<p><strong>3. Initialize the agent</strong></p>



<p>At the top of your project file (server.js), add:</p>



<div class="code-block content-copy">
<div class="pre" id="code-blog"><pre><code>
const tracker = require('@middleware.io/node-apm');
tracker.track({
  serviceName: "Latency-With-APM",
  accessToken: "<MW_API_KEY>",
  target: "https://ccang.middleware.io",
});
</code>
</pre>
</div>
<a class="copy-btn" id="first-button"></a>
</div>



<p>&lt;MW_API_KEY&gt; is the API key from your dashboard. Replace it.</p>



<p><strong>4. Restart your application and make a request.</strong></p>



<div class="code-block content-copy">
<div class="pre" id="code-blog"><pre><code>
npm run dev
</code>
</pre>
</div>
<a class="copy-btn" id="first-button"></a>
</div>



<h3 class="wp-block-heading" id="h-check-dashboard">Check Dashboard</h3>



<p>After your application is up and running and linked to Middleware, you may examine the monitoring dashboard to identify any signs of latency problems.</p>



<p><strong>1. Confirm your service is connected</strong></p>



<p>From your Middleware dashboard, scroll down to the section labeled &#8220;Services.&#8221; The name of the service you chose during setup should appear, such as Latency-With-APM, if it appears that your app is sending data correctly.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1383" height="561" src="https://middleware.io/backend/wp-content/uploads/2025/10/middleware-service-connected.webp" alt="Middleware dashboard showing connected service" class="wp-image-12675"/></figure>



<p><strong>2. Simulate latency for testing</strong></p>



<p>You can verify if the Middleware is catching delays by making your endpoints act like they are experiencing latency. For instance:</p>



<div class="code-block content-copy">
<div class="pre" id="code-blog"><pre><code>
// 5-second delay on /users
app.get('/users', (req, res) => {
  setTimeout(() => {
    res.json(users);
  }, 5000); // 5000 ms = 5 seconds delay
});

// 4-second delay on /users/:id
app.get('/users/:id', (req, res) => {
  setTimeout(() => {
    const user = users.find(u => u.id === parseInt(req.params.id));
    if (!user) return res.status(404).json({ message: "User not found" });
    res.json(user);
  }, 4000); // simulate 4s latency
});
</code>
</pre>
</div>
<a class="copy-btn" id="first-button"></a>
</div>



<p>When you call these endpoints, go to your dashboard and navigate to the APM section. There, you’ll find <a href="https://middleware.io/product/metrics/">metrics</a> and information that you can use to analyze and resolve issues in your application.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1398" height="467" src="https://middleware.io/backend/wp-content/uploads/2025/10/middleware-apm-metrics-dashboard.webp" alt="Middleware APM dashboard showing API metrics" class="wp-image-12676"/></figure>



<p>You’ll also see each request you made, along with the time it took to receive a response.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1194" height="303" src="https://middleware.io/backend/wp-content/uploads/2025/10/middleware-apm-request-tracing.webp" alt="Middleware APM showing individual API requests and response times" class="wp-image-12677"/></figure>



<p>This information will help you identify the endpoint that is experiencing issues. When you click on each one, you&#8217;ll also discover further information that will help you figure out what went wrong.</p>



<p><strong>3. Set up alerts</strong></p>



<p>Go to the Alerts section and create a rule for response times. For example, set a threshold so you’re notified if an endpoint takes more than 2 seconds to respond.</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="854" height="404" src="https://middleware.io/backend/wp-content/uploads/2025/10/middleware-apm-alerts-setup.gif" alt="Setting up API response time alerts in Middleware APM" class="wp-image-12679"/></figure>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Set up response time alerts in Middleware APM to get instant notifications when your endpoints slow down. 👉<a href="https://docs.middleware.io/workflow/alerting/setup-alert">Configure Alerts Now</a></p>
</blockquote>



<h3 class="wp-block-heading" id="h-how-hotplat-reduced-latencies-by-90-with-middleware">How Hotplat Reduced Latencies by 90% with Middleware</h3>



<p><a href="https://middleware.io/customers/hotplate/">Hotplate</a>, a fast-growing platform for pop-up chefs, struggled with performance issues during high-traffic events. Their team required a cost-effective solution to detect problems, reduce latency, and enhance the customer experience.</p>



<p>According to Rangaraj Tirumala, the founding engineer at Hotplate,</p>



<figure class="wp-block-pullquote"><blockquote><p>“We experienced frequent performance issues but lacked the tools to measure the extent of the degradation accurately.”</p><cite>Rangaraj Tirumala, the founding engineer at Hotplate</cite></blockquote></figure>



<p>By adopting Middleware APM and <a href="https://middleware.io/product/real-user-monitoring/">Real-User Monitoring (RUM)</a>, Hotplate achieved:</p>



<ul class="wp-block-list">
<li>90% reduction in latency across millions of monthly events</li>



<li>75% faster <a href="https://middleware.io/blog/identify-root-cause-analysis/">root cause analysis</a> using detailed traces and <a href="https://middleware.io/product/real-user-monitoring/session-replays/">session replays</a></li>



<li>10x <a href="https://middleware.io/blog/reduce-observability-costs/">reduction in observability&nbsp;costs</a> compared to other tools</li>
</ul>



<p>Middleware APM’s combination of <a href="https://middleware.io/product/distributed-tracing/">detailed tracing</a>, real-user monitoring, and cost-effective pricing enabled Hotplate to transform its <a href="https://middleware.io/blog/api-monitoring/">API performance</a> while scaling efficiently. With Middleware, Hotplate not only optimized <a href="https://middleware.io/blog/what-is-application-performance-monitoring/">system performance</a> but also enhanced customer interactions by diagnosing issues from the user’s perspective.</p>



<p>Managing API latency is necessary for building responsive applications. With Middleware APM, you don’t just detect latency issues; you can trace them to the root cause and resolve them before they affect users.</p>



<div class="container-cta">
  
<div><h3>Start Tracking Latency in Real-Time</h3>
  <p>Learn how to visualize your API performance, set alerts, and troubleshoot issues faster with Middleware’s APM.
 </p>
  <a href="https://middleware.io/product/apm/" target="_blank" rel="noopener"><button class="primary white">Explore APM</button></a>

 <a href="https://app.middleware.io/auth/register/" target="_blank" rel="noopener"><button class="secondary white">Start Free Trial</button></a>
</div>

</div>



<p><a href="https://middleware.io/product/apm/">Get started with Middleware APM</a> to reduce API latency.</p>



<h3 class="wp-block-heading" id="h-faqs">FAQs</h3>


		<section		help class="sc_fs_faq sc_card    "
				>
				<h3>What is a good latency threshold for APIs?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>It depends on the use case. However, generally, APIs should respond within 100-500 ms for a smooth user experience. Anything over 1 second usually feels slow.</p>

			</div>
		</div>
		</section>
				<section		help class="sc_fs_faq sc_card    "
				>
				<h3>How quickly can Middleware detect latency anomalies?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>Middleware detects issues in real time. It flags unusual spikes in latency as soon as they occur.</p>

			</div>
		</div>
		</section>
				<section		help class="sc_fs_faq sc_card    "
				>
				<h3>Can Middleware monitor APIs across multiple regions?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>Yes. Middleware can track API performance across different regions and environments, helping you spot region-specific issues.</p>

			</div>
		</div>
		</section>
				<section		help class="sc_fs_faq sc_card    "
				>
				<h3>What languages and frameworks can Middleware APM work with?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>Middleware APM can be integrated with various popular programming languages and tools, including Node.js, Python, Java, .NET, Ruby, PHP, and others. This makes it simple to integrate with most tech stacks.</p>

			</div>
		</div>
		</section>
		
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<h3 class="wp-block-heading" id="h-"></h3>


Detect and resolve API latency with Middleware APM. Learn real-time monitoring, tracing, and optimization techniques to boost API performance and reliability.

Detecting and Resolving API Latency Issues with Middleware APM

Switching monitoring tools feels risky. This guide shows what your first 4 weeks with Middleware look like from setup to full ROI and cost savings.

What to expect when you switch to Middleware(Day 0 – Week 4)

Learn to troubleshoot common Kubernetes errors like CrashLoopBackOff, OOMKilled, and ImagePullBackOff for smooth pod and cluster performance.

Kubernetes Common Errors & How to Fix Them

Gain clarity on Kubernetes metrics with best practices for collection, analysis, and monitoring. Ensure cluster health, optimize performance, and debug issues faster.

Understanding Kubernetes Metrics: Best Practices for Effective Monitoring

Learn how to restart Kubernetes pods using kubectl, why it matters, and the safest methods plus monitor pods easily with Middleware for smarter decisions.

How to Restart Pods in Kubernetes Using kubectl

Automate complex workloads with a K8 Operator. Simplify scaling, backups, upgrades, and observability for stateful apps like databases and message queues.

Automating Stateful Apps with Kubernetes Operators


<p>Running production workloads on Kubernetes without proper <a href="https://middleware.io/blog/observability/">observability</a> is like flying blind in adverse conditions. As your applications run across multiple pods, nodes, and services, monitoring your Kubernetes app in real time becomes essential to understand what’s happening under the surface. A single failing pod or resource bottleneck can quickly escalate into a critical outage, making effective Kubernetes app monitoring crucial to ensuring business continuity.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Learn more about <a href="https://middleware.io/blog/kubernetes-observability/">Kubernetes observability</a> concepts and best practices in our dedicated guide.</p>
</blockquote>



<p>In production environments, <a href="https://middleware.io/">Middleware</a> simplifies Kubernetes monitoring by offering a fast, visual way to monitor workloads. Additionally, this modern observability platform provides comprehensive insights through intuitive dashboards and intelligent, <a href="https://middleware.io/blog/real-time-alerts/">real-time alerts</a>.</p>



<p></p>



<p>This tutorial demonstrates how to set up Middleware, <a href="https://middleware.io/product/metrics/">monitor metrics</a> and <a href="https://middleware.io/blog/what-is-log-monitoring/">logs</a> in real-time, navigate the UI, and maintain a smooth running of your Kubernetes apps.</p>



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Table of Contents
</div> <div id="toc" class="collapse" data-parent="#accordian">
<div class="toc-list">
</div>
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</div>



<h2 class="wp-block-heading" id="h-setting-up-middleware-for-kubernetes-application-monitoring">Setting Up Middleware for Kubernetes Application Monitoring</h2>



<p>Deploy Middleware into your Kubernetes cluster in just a few simple steps. Unlike other monitoring tools that require large configuration files and complex setup procedures, Middleware gets you monitoring in minutes, not hours.</p>



<h3 class="wp-block-heading" id="h-step-1-signing-up-or-logging-into-middleware">Step 1: Signing up or logging into Middleware</h3>



<p>Visit Middleware to <a href="https://app.middleware.io/auth/register/">create an account</a> or log in if you already have one. The signup is quick and easy; enter your basic details, and you’re ready to start.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1600" height="868" src="https://middleware.io/backend/wp-content/uploads/2025/09/Middleware-Kubernetes-monitoring-dashboard-showing-cluster-overview-and-real-time-metrics.webp" alt="Middleware monitoring dashboard showing cluster overview and real-time metrics" class="wp-image-12281"/></figure>



<h3 class="wp-block-heading" id="h-step-2-installing-the-middleware-agent-helm-chart-in-the-cluster">Step 2: Installing the Middleware agent/Helm chart in the cluster</h3>



<p>Next, install the Middleware agent in your Kubernetes cluster. Once logged in, Middleware provides a simple <a href="https://middleware.io/blog/helm-chart-tutorial/">Helm chart</a> command that adds the Helm repository. Installing the agent then takes just a few easy steps, as shown below.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>For full installation instructions and advanced setup options, refer to the official Middleware documentation → <a href="https://docs.middleware.io/agent-installation/kubernetes/kubernetes-agent">Middleware Kubernetes Agent Installation Guide</a>.</p>
</blockquote>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1579" height="840" src="https://middleware.io/backend/wp-content/uploads/2025/09/Installing-Middleware-agent-in-Kubernetes-cluster-using-Helm-chart-commands.webp" alt="Installing Middleware agent in Kubernetes cluster using Helm chart commands" class="wp-image-12283"/></figure>



<p>And that’s it! Deployed as a DaemonSet, the agent automatically runs on every node in your cluster, ensuring complete monitoring with no additional setup required.</p>



<h3 class="wp-block-heading" id="h-step-3-automatic-cluster-discovery-nodes-pods-deployments">Step 3: Automatic cluster discovery (nodes, pods, deployments)</h3>



<p>Middleware makes cluster discovery effortless, with no manual configuration required. Once the agent is deployed, it automatically detects and monitors all key components:</p>



<ul class="wp-block-list">
<li><strong>Nodes:</strong> All worker and master nodes are detected automatically</li>



<li><strong>Pods:</strong> Every pod across all namespaces gets monitored</li>



<li><strong>Deployments:</strong> Your applications and services are identified instantly</li>



<li><strong>Services:</strong> Network components are mapped without manual setup</li>
</ul>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1640" height="1174" src="https://middleware.io/backend/wp-content/uploads/2025/09/Middleware-automatically-discovering-Kubernetes-nodes-pods-deployments-and-services.webp" alt="Middleware automatically discovering Kubernetes nodes, pods, deployments, and services" class="wp-image-12284"/></figure>



<h3 class="wp-block-heading" id="h-step-4-verifying-successful-connection-and-data-ingestion">Step 4: Verifying successful connection and data ingestion</h3>



<p>You should confirm everything works correctly in the final step. Within a few minutes of installation, you should see data streaming into your Middleware dashboard.</p>



<p>First, check the infrastructure view to confirm that all cluster nodes are visible and that your pods are actively sending metrics. Once real-time data appears on your dashboards, you know Middleware is successfully monitoring your Kubernetes cluster.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1784" height="925" src="https://middleware.io/backend/wp-content/uploads/2025/09/Middleware-dashboard-showing-real-time-Kubernetes-cluster-metrics-and-node-monitoring.webp" alt="Middleware dashboard showing real-time cluster metrics and node monitoring" class="wp-image-12285"/></figure>



<p>The best part about Middleware is its simplicity. Unlike other tools that require extensive configuration, custom dashboards, or manual monitoring setup, Middleware handles everything automatically, giving you complete Kubernetes monitoring with virtually no effort.</p>



<h2 class="wp-block-heading" id="h-observing-metrics-for-monitoring-of-your-kubernetes-app">Observing Metrics for Monitoring of Your Kubernetes App</h2>



<p>With Middleware running, you can start monitoring your Kubernetes cluster in real time. Its intuitive UI makes tracking metrics and cluster activity simple and efficient.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Monitoring CPU, memory, and storage metrics is crucial for avoiding bottlenecks. For a comprehensive overview of Kubernetes monitoring approaches, <a href="https://middleware.io/blog/kubernetes-monitoring/">see our guide</a>.</p>
</blockquote>



<h3 class="wp-block-heading" id="h-cluster-overview-live-view-for-monitoring-your-kubernetes-app">Cluster Overview: Live View for Monitoring Your Kubernetes App</h3>



<p>When you launch Middleware after your agent installation, you will see the Cluster Overview page. Think of this page as your command center. You can see all your nodes, your namespaces, and even your pods with their current status clearly. My favorite part is that you can quickly determine which areas of your cluster are running healthily and which require attention.</p>



<p>The live view changes in real time, so you&#8217;re never looking at stale info. You will see your workloads in their current state, not as they were five minutes ago. This real-time feedback is extremely useful while troubleshooting or simply ensuring that the new deployment went smoothly.</p>



<h4 class="wp-block-heading" id="h-resource-utilization-cpu-memory-and-storage-metrics-at-the-pod-and-node-levels">Resource Utilization: CPU, memory, and storage metrics at the pod and node levels</h4>



<p>Middleware visualizes resource usage with easy-to-read charts, making monitoring your Kubernetes app effortless and accurate. You can drill down from cluster-level metrics to individual pods, monitoring CPU, memory, and storage efficiently.</p>



<p>When users report slow responses, you can quickly identify whether a node is maxed out on CPU or a specific pod consumes excessive memory. Storage metrics help prevent surprises like unexpected disk full alerts, keeping your cluster running smoothly.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1348" height="925" src="https://middleware.io/backend/wp-content/uploads/2025/09/Middleware-dashboard-showing-Kubernetes-cluster-overview-with-nodes-pods-resource-utilization-metrics.webp" alt="Middleware dashboard showing cluster overview with nodes, pods, resource utilization metrics" class="wp-image-12286"/></figure>



<h4 class="wp-block-heading" id="h-pod-health-and-restarts-tracking-your-kubernetes-app-for-crashes-and-restarts">Pod Health and Restarts: Tracking Your Kubernetes App for Crashes and Restarts</h4>



<p>Pods can be unpredictable, but Middleware’s <strong>Pod Health and Restarts</strong> monitoring removes the guesswork. You can instantly see which pods have restarted, how often, and whether a deployment has failed.</p>



<p>Middleware also tracks restart trends over time, helping you identify consistent issues before they impact your applications. Any underlying reasons for failures are highlighted, reducing the need to dig through logs manually.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Explore common pod issues and their resolutions in our <a href="https://middleware.io/blog/kubernetes-troubleshooting-techniques/">Top 10 Kubernetes Troubleshooting Techniques</a> blog.</p>
</blockquote>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1695" height="875" src="https://middleware.io/backend/wp-content/uploads/2025/09/Middleware-dashboard-showing-Kubernetes-pod-health-restarts-and-failed-deployments.webp" alt="Middleware dashboard showing pod health, restarts, and failed deployments" class="wp-image-12288"/></figure>



<h4 class="wp-block-heading" id="h-network-metrics-traffic-between-services-and-latency-insights">Network Metrics: Traffic between services and latency insights</h4>



<p>Middleware’s <strong>Network Metrics</strong> make it easy to visualize traffic between services, identify bottlenecks, and detect unusual patterns in service-to-service communication.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>For insights into managing network-related issues, check out our <a href="https://middleware.io/blog/exit-code-137-in-kubernetes-causes-diagnosis-fixes/">Exit Code 137 in Kubernetes: Causes, Diagnosis, and Fixes</a></p>
</blockquote>



<p><a href="https://middleware.io/blog/latency-reduction/">Latency</a> insights help you quickly determine if performance issues are caused by the network or specific service calls, allowing faster troubleshooting and improved <a href="https://middleware.io/product/apm/">application performance</a>.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1906" height="983" src="https://middleware.io/backend/wp-content/uploads/2025/09/Middleware-dashboard-showing-Kubernetes-network-traffic-and-service-latency-metrics.webp" alt="Middleware dashboard showing network traffic and service latency metrics" class="wp-image-12289"/></figure>



<h3 class="wp-block-heading" id="h-automatic-anomaly-detection-your-silent-guardian">Automatic Anomaly Detection: Your Silent Guardian</h3>



<p>Middleware goes beyond charts by actively analyzing metrics, ensuring continuous monitoring of your Kubernetes application, and automatically <a href="https://middleware.io/blog/anomaly-detection/">detecting anomalies</a>. It identifies unusual behavior, such as a pod consuming 90% CPU at midnight, and alerts you before it impacts your applications.</p>



<p>The system learns what’s normal in your cluster and flags abnormal <a href="https://middleware.io/blog/debug-faster-with-log-patterns/">log patterns</a>, whether it’s unexpected pod restarts or unusual memory usage, so you can address issues proactively and maintain stable Kubernetes operations.</p>



<h2 class="wp-block-heading" id="h-centralized-logs-and-alerts-for-kubernetes-app-monitoring">Centralized Logs and Alerts for Kubernetes App Monitoring</h2>



<p>When something goes wrong in your cluster, you need answers fast. Middleware automatically pulls logs from all your containers, pods, and cluster events into a single unified view, with no extra configuration required and no separate log agents to manage. Everything flows into a single, searchable interface.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Learn more about <a href="https://middleware.io/blog/kubernetes-logging/">Kubernetes logging best practices</a> to optimize log collection and troubleshooting.</p>
</blockquote>



<h3 class="wp-block-heading" id="h-searching-and-filtering-logs">Searching and Filtering Logs</h3>



<p>Middleware’s log viewer makes finding issues simple. <a href="https://docs.middleware.io/workflow/log-monitoring/search-filter">Filter logs</a> instantly by service, namespace, or time window, or search using error codes, service names, or partial messages. The interface updates in real time, so you don’t waste time while troubleshooting critical problems.</p>



<h3 class="wp-block-heading" id="h-one-click-filtering-and-severity-switching">One-Click Filtering and Severity Switching</h3>



<p>Click any value pod name, error type, or request ID to filter similar entries automatically. Severity switching allows you to toggle between <a href="https://middleware.io/blog/log-levels-guide/">log levels</a> <strong>error, warning, and info logs</strong>, with color-coded highlighting for fast visual analysis. These one-click filters save valuable time, helping you <a href="https://middleware.io/blog/catch-deployment-issues/">debug production issues</a> efficiently.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1579" height="839" src="https://middleware.io/backend/wp-content/uploads/2025/09/middleware-kubernetes-logs-dashboard.webp" alt="Middleware centralized log viewer showing Kubernetes container, pod, and cluster logs with filters and severity levels" class="wp-image-12290"/></figure>



<h2 class="wp-block-heading" id="h-alerts-amp-notifications">Alerts &amp; Notifications</h2>



<p>With Middleware, you can stay ahead of issues before they impact your users. <span style="box-sizing: border-box; margin: 0px; padding: 0px;"><a href="https://docs.middleware.io/workflow/alerting/setup-alert">Setting up&nbsp;alerts</a> for your Kubernetes cluster&nbsp;is simple;</span> no complex YAML or rule syntax is needed.</p>



<h3 class="wp-block-heading" id="h-configuring-alerts-for-kubernetes-events">Configuring Alerts for Kubernetes Events</h3>



<p>Use the alert configuration UI to monitor what matters most. Set alerts for pod failures, <a href="https://middleware.io/blog/prevent-cpu-overload-on-linux-servers/">high CPU usage</a> or memory usage, and unexpected restart rates. Drag-and-drop sliders and namespace selection make configuration fast and easy. Restart thresholds help catch subtle issues like <a href="https://middleware.io/blog/memory-leaks/">memory leaks</a> or misconfigurations before they escalate.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>For advanced debugging techniques, refer to our Troubleshoot Smarter Using Advanced <a href="https://middleware.io/blog/debug-logging/">Debug Logging</a> Techniques</p>
</blockquote>



<h3 class="wp-block-heading" id="h-alert-dashboard-and-incident-timeline">Alert Dashboard and Incident Timeline</h3>



<p>The dashboard displays warnings on a timeline, showing when issues occurred and their context. You can quickly see affected pods, relevant metrics, and associated log entries to troubleshoot efficiently.</p>



<h3 class="wp-block-heading" id="h-integration-with-slack-and-pagerduty">Integration with Slack and PagerDuty</h3>



<p>Middleware integrates with Slack and PagerDuty, sending notifications directly to your team for quick response. <a href="https://middleware.io/platform/alerts/">Alerts</a> provide enough context to understand the severity and scope of an issue, keeping your team informed and proactive.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1698" height="1027" src="https://middleware.io/backend/wp-content/uploads/2025/09/middleware-kubernetes-alerts-dashboard.webp" alt="Middleware Kubernetes alert dashboard showing pod failures, CPU/memory alerts, and incident timeline" class="wp-image-12291"/></figure>



<h2 class="wp-block-heading" id="h-try-middleware-for-your-kubernetes-clusters-today">Try Middleware for your Kubernetes clusters today</h2>



<p>You now have everything you need to monitor your Kubernetes clusters professionally. Middleware makes everything surprisingly simple, from real-time data and consolidated logs to helpful smart alarms.</p>



<p>Why not see it in action? <a href="https://app.middleware.io/auth/register/">Start monitoring your Kubernetes app</a> with Middleware today and experience monitoring that works. Your future self (and your team) will thank you for making the switch.</p>



<p>Your clusters are waiting for the monitoring they deserve.</p>



<div class="container-cta">
  
<div><h3>Take Control of Your Kubernetes Monitoring with Middleware</h3>
  <p>Get real-time visibility, automatic pod and node discovery, intelligent alerts, and centralized logs—all in one platform.
 </p>
  <a href="https://docs.middleware.io/getting-started/deploying-the-agent/k8s-agent" target="_blank" rel="noopener"><button class="primary white">Deploy the Middleware Agent</button></a>

 <a href="https://app.middleware.io/auth/register/" target="_blank" rel="noopener"><button class="secondary white">Start Monitoring Now</button></a>
</div>

</div>


Monitor your Kubernetes application clusters with Middleware. Get real-time dashboards, intelligent alerts, auto-discovery of pods and nodes, and centralized logs for smooth operations.

Monitoring Kubernetes Application with Middleware

EKS monitoring helps you track nodes, pods, apps, and security in Kubernetes. This guide explains what to monitor, tools available, and how Middleware makes observability simple.

Amazon EKS Monitoring: Essential Guide to Kubernetes Observability

Exit code 137 in Kubernetes means a container was killed with SIGKILL, usually due to running out of memory (OOMKilled). Learn the common causes, how to diagnose it, and the best fixes to prevent forced pod terminations.

Exit Code 137 in Kubernetes: Causes, Diagnosis, and Fixes


<p>Hyderabad, the city of Nawabs, was buzzing on August 5–7, 2025, as KubeCon India 2025 brought together over 4,000 cloud-native and <a href="https://middleware.io/blog/what-is-devops/">DevOps</a> professionals, featuring 12+ keynotes, 10+ lightning talks, 56+ technical sessions, and 30+ booths. KubeCon India 2025 was more than just a conference; it was a convergence of innovation, collaboration, and the relentless pursuit of excellence in the <a href="https://middleware.io/blog/cloud-infrastructure-guide/">cloud-native ecosystem</a>.</p>



<p><a href="https://middleware.io/">Middleware</a> immersed itself in the heart of this transformative event, showcasing our commitment to helping organisations with an AI-powered <a href="https://middleware.io/blog/observability/">observability</a> solution.</p>



<p>Building on last year’s experiences in the US, Middleware brought the same energy and commitment to India, further reinforcing our global presence in the cloud-native ecosystem.</p>



<h3 class="wp-block-heading" id="h-looking-back-from-kubecon-usa-to-india">Looking Back: From KubeCon USA to India</h3>



<p>Last year, Middleware sponsored <a href="https://middleware.io/events/kubecon-na-2024/">KubeCon USA 2024</a> and collaborated with Devtron to host a Happy Hour party, attracting over 200 attendees, including CNCF ambassadors and industry leaders. Inspired by the event’s impact, our team decided to sponsor <a href="https://middleware.io/events/kubecon-india-2025/">KubeCon India 2025</a>, reinforcing Middleware’s commitment to innovation and community engagement.</p>



<h2 class="wp-block-heading" id="h-kubecon-kickoff-round-table-thought-leadership-in-action">KubeCon Kickoff Round Table: Thought Leadership in Action</h2>



<p>On August 5, 2025, Middleware hosted a <strong><a href="https://middleware.io/events/kubecon-kickoff-india-2025/">pre-KubeCon round table</a></strong> in Radisson Hitech City, Hyderabad:</p>



<ul class="wp-block-list">
<li><strong>Objectives</strong>: Facilitate a discussion on challenges faced by DevOps experts and AI-operated solutions.</li>



<li><strong>Attendance</strong>: Despite heavy rains, 25 senior industry leaders of top technology companies participated.</li>



<li><strong>Highlight:</strong> The session concluded with a live demonstration of <a href="https://middleware.io/product/ops-ai/">OpsAI</a>, garnering glowing feedback and several requests for follow-up demonstrations.</li>
</ul>



<figure class="wp-block-pullquote"><blockquote><p><em>&#8220;It was incredible to witness leaders sharing insights and engaging deeply on the future of DevOps and AI,&#8221;</em>  </p><cite><strong>Sam Suthar, Founding Director</strong> at <strong>Middleware.</strong></cite></blockquote></figure>



<p>Beyond thought leadership sessions, Middleware also engaged attendees directly at our booth, turning conversations into hands-on experiences with our AI-powered <a href="https://middleware.io/blog/observability/tools/">observability tools</a>.</p>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="720" height="585" src="https://middleware.io/backend/wp-content/uploads/2025/08/KubeCon-Kickoff-Round-Table-Thought-Leadership-in-Action.webp" alt="KubeCon Kickoff Round Table Thought Leadership in Action" class="wp-image-12117"/></figure>



<h2 class="wp-block-heading" id="h-engaging-with-attendees-at-the-booth">Engaging with Attendees at the Booth</h2>



<p>Middleware’s booth at Novotel became a hub for interaction:</p>



<ul class="wp-block-list">
<li>Hands-on OpsAI <a href="https://middleware.io/demo-request/">demos</a>.</li>



<li>Discussion on the challenges faced by the company in Observability.</li>



<li>Interactive quizzes and Q&amp;A sessions.</li>



<li>Networking with industry leaders, DevOps professionals, and observability experts.</li>
</ul>



<p>The booth attracted high engagement, with more than 100 people present at the time of the OpsAI Demo and giveaway. Attendees asked detailed technical questions about OpsAI and its application in real-world DevOps scenarios.</p>



<h2 class="wp-block-heading" id="h-middleware-developer-advocate-session-highlights">Middleware Developer Advocate Session Highlights</h2>



<p>Our session, <strong>“Freeze, Investigate, Recover: Unlocking Forensic Container Checkpointing with CRI-U”</strong>, led by Neel Shah, offered an insightful look into container checkpointing.</p>



<p>Using CRIU technology, he explored how developers can capture complete container states, perform in-depth investigations, and recover seamlessly, unlocking new possibilities in security, <a href="https://middleware.io/blog/debug-logging/">debugging</a>, and incident response.</p>



<p>Alongside the session, we shared engaging activities, showcased live demos, and distributed giveaways, making the experience interactive and memorable for all participants.</p>



<p>Watch the full session highlights <a href="https://youtube.com/playlist?list=PLj6h78yzYM2MEQTMX_LIOK1hrePHxLD6U&amp;si=Dmr22OzxcM5_S_xA">here</a>.</p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="Freeze,Investigate,Recover: Unlocking Forensic Container Checkpoint... Suman Chakraborty &amp; Neel Shah" width="500" height="281" src="https://www.youtube.com/embed/CRPhKh1hqmc?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p>These sessions, demos, and activities combined to highlight Middleware’s broader impact, from innovation to community engagement.</p>



<h2 class="wp-block-heading" id="h-middleware-impact-amp-takeaways">Middleware Impact &amp; Takeaways</h2>



<ul class="wp-block-list">
<li><strong>Showcasing Innovation:</strong> OpsAI demos highlighted the power of AI-driven DevOps.<br></li>



<li><strong>Thought Leadership:</strong> Hosting a <strong>pre-event round table</strong> positioned Middleware as a leader in AI, Observability and cloud-native solutions.<br></li>



<li><strong>Community Engagement:</strong> Interacted with thousands of attendees, building relationships and gaining insights into the future of cloud-native technologies.</li>
</ul>



<figure class="wp-block-image size-full"><img loading="lazy" decoding="async" width="720" height="388" src="https://middleware.io/backend/wp-content/uploads/2025/08/KubeCon-India-2025-1.webp" alt="KubeCon India 2025" class="wp-image-12127"/></figure>



<h3 class="wp-block-heading" id="h-a-journey-of-innovation-and-collaboration">A Journey of Innovation and Collaboration</h3>



<p>Our KubeCon experience began well before the event. In the days leading up to the conference, our team engaged in spirited discussions with industry leaders, sharing insights and exploring the future of cloud-native technologies. These conversations set the stage for the impactful interactions that would unfold at the conference.</p>



<p>Our impact at the event was rooted in the efforts that began long before KubeCon India, as our team engaged in strategic conversations and collaborations with industry leaders.</p>



<h3 class="wp-block-heading" id="h-key-takeaways-from-the-event">Key Takeaways from the Event</h3>



<p>KubeCon India 2025 provided invaluable insights into the future of DevOps:</p>



<ul class="wp-block-list">
<li><strong>AI is Transforming DevOps:</strong> The integration of AI is enhancing efficiency and resilience in cloud-native environments.<br></li>



<li><strong>Observability is Crucial:</strong> Real-time insights are essential for proactive issue resolution and system optimization.<br></li>



<li><strong>Community Collaboration Drives Innovation:</strong> Shared knowledge and experiences accelerate the development of cutting-edge solutions.</li>
</ul>



<h3 class="wp-block-heading" id="h-join-the-middleware-community">Join the Middleware Community</h3>



<p>KubeCon India 2025 reinforced Middleware’s commitment to innovation, AI-driven DevOps, and community leadership.</p>



<ul class="wp-block-list">
<li><a href="https://middleware.io/events/"><strong>Stay updated</strong></a> on upcoming events and webinars.<br></li>



<li><a href="https://middleware.io/demo-request/"><strong>Request a demo</strong></a> of OpsAI to see how AI can optimize your DevOps workflow.<br></li>



<li><a href="https://middlewarepublic.slack.com/join/shared_invite/zt-39l76rpo6-ZNGfpA_4U_kYL6oTuYAgmQ"><strong>Join our community</strong></a> to discuss observability and OpsAI in more detail.</li>
</ul>



<p>Watch the highlights of the event <a href="https://youtu.be/glDbS-uL9Aw">here</a>. See you at the next KubeCon!</p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="KubeCon India 2025 Highlights" width="500" height="281" src="https://www.youtube.com/embed/glDbS-uL9Aw?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p>Building on the momentum from KubeCon India, Middleware is now gearing up for its next milestone: KubeCon USA 2025, where we will continue to showcase AI-driven DevOps innovation on a global stage.</p>



<h2 class="wp-block-heading" id="h-gearing-up-for-kubecon-usa-2025-nbsp">Gearing Up for KubeCon USA 2025&nbsp;</h2>



<p>We are thrilled to announce that Middleware will be heading to KubeCon NA USA 2025 from November 10th to 13th in Atlanta, Georgia, joining the global cloud-native community for this milestone event. </p>



<p>As industry experts and enthusiasts gather to discuss cloud-native innovation and <a href="https://middleware.io/blog/observability/trends/">observability trends</a>, our team looks forward to showcasing Middleware’s AI-powered observability solution, which helps organizations drastically <a href="https://middleware.io/blog/observability-ways-to-reduce-it-costs-with-observability/">cut observability costs</a>, speed up issue resolution, and elevate <a href="https://middleware.io/blog/what-is-application-performance-monitoring/">application performance</a>.  For full details, visit <a href="https://middleware.io/events/kubecon-na-2025/">KubeCon USA 2025</a>.</p>


Middleware stood out at KubeCon India 2025 by highlighting AI-driven observability with OpsAI, conducting a container checkpointing session, hosting a pre-event roundtable, and connecting with the cloud-native community through demos, activities, and interactive discussions.

Middleware at KubeCon India 2025

Master debug logging in Node.js and other apps. Learn best practices, avoid common mistakes, and monitor logs efficiently for faster troubleshooting.

Troubleshoot Smarter Using Advanced Debug Logging Techniques 

Every click and form submission matters in your web app. Middleware’s browser tests help you monitor full user journeys, catch hidden issues like JavaScript errors, layout failures, or broken logins, and fix them before they frustrate your users.

Monitor Web App User Journeys with Browser Tests in Middleware

Server health monitoring helps you detect issues early, maintain uptime, and deliver a seamless user experience. This guide covers essential metrics, monitoring methods, and how Middleware simplifies the process with real-time insights and alerts.

Proactive Server Health Monitoring: Avoid Downtime Before It Happens


<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>“Every minute spent chasing a bug in production is a minute not spent building features. The biggest slowdown? Figuring out <em>who owns the failing code.</em>”</p>
</blockquote>



<p>Production errors are a headache for every engineering team. The issue isn’t just the bug itself, but the time it takes to trace where it came from, who wrote the code, and how it slipped through. Without the right <strong>error debugging tools</strong>, engineers often bounce between error <a href="https://middleware.io/product/log-monitoring/">logs</a>, GitHub commit history, and Slack threads to figure out who should even look into the problem.</p>



<p>Middleware’s Ops AI changes that. Pulling in GitHub commit and ownership data directly into your <strong>error tracking with GitHub</strong> workflow shows you the root cause and the right owner in seconds. No more guesswork, no more wasting hours chasing leads that go nowhere.</p>



<p>In this blog, we’ll explore how Middleware’s integration with GitHub works, how it automatically maps errors to code changes and owners, and how this level of <a href="https://middleware.io/blog/incident-management-kpis/">incident management</a> automation helps teams resolve issues faster and <a href="https://middleware.io/blog/how-to-reduce-mttr/">reduce mean time to resolution</a> (MTTR).</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Looking to cut debugging time in half? <a href="https://middleware.io/blog/opsai-ai-observability-copilot/">See how Middleware</a> helps engineering teams streamline error resolution. </p>
</blockquote>



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<h2 class="wp-block-heading" id="h-what-is-middleware-ops-ai">What Is Middleware Ops AI?</h2>



<p>To understand how GitHub data powers better error tracking, it’s important to understand what <a href="https://middleware.io/product/ops-ai/">Middleware Ops AI</a> actually is.</p>



<p>Middleware Ops AI is an AI-powered <a href="https://middleware.io/blog/observability/">observability</a> engine that monitors your application stack: <a href="https://middleware.io/product/apm/">APM</a>, logs, metrics, <a href="https://middleware.io/product/synthetic-monitoring/">frontend performance</a>, and automatically correlates incidents with the underlying code and responsible teams. Unlike traditional <strong>error debugging tools</strong>, it doesn’t just tell you that something broke. It tells you why, where, and who can fix it.</p>



<p>Here’s what makes Ops AI unique:</p>



<ul class="wp-block-list">
<li><a href="https://middleware.io/blog/anomaly-detection/">Detects anomalies</a> across backend, frontend, and <a href="https://middleware.io/blog/what-is-infrastructure-monitoring/">infrastructure</a> automatically.<br></li>



<li>Links each error to the exact code commit, file, and developer who last changed it with <strong>error tracking through GitHub commits</strong>.<br></li>



<li>In high-confidence scenarios, generate a pull request with a recommended fix.<br></li>



<li>Assigns incidents based on real ownership, not guesswork or rotating on-call schedules.<br></li>



<li>Only pulls metadata and specific lines of code necessary to diagnose the issue, not your entire repo.</li>
</ul>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>👉 Want to try it yourself? <a href="https://docs.middleware.io/integrations/github-integration">See how to set up GitHub Integrations</a> and connect Middleware Ops AI with your repo in minutes.</p>
</blockquote>



<h2 class="wp-block-heading" id="h-how-github-commit-and-ownership-data-actually-helps-you-fix-errors-faster">How GitHub Commit and Ownership Data Actually Helps You Fix Errors Faster</h2>



<p>Let’s be honest, when an error shows up in production, </p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>First question isn’t “what failed?” It’s “who last touched this code?”</p>
</blockquote>



<p>And that’s where <a href="https://middleware.io/product/ops-ai/">Middleware’s Ops AI</a> makes a big difference. Instead of leaving you to jump between your error logs and GitHub manually, it connects the dots for you, showing which commit introduced the problem, who made the change, and how it’s connected to the current error.</p>



<p>Here’s how it works in real life:</p>



<h2 class="wp-block-heading" id="h-trace-errors-to-the-exact-commit">Trace Errors to the Exact Commit</h2>



<p>When an error hits production, most teams scramble to answer: <em>what changed that triggered this?</em> </p>



<p>With Middleware, you don’t have to dig through logs or GitHub history yourself. It uses <strong>error tracking with GitHub</strong> to match the error to the right commit automatically.</p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="Introducing Ops AI by Middleware | Observability Co-pilot | AI Agent" width="500" height="281" src="https://www.youtube.com/embed/29pzH-1_Dpc?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div><figcaption class="wp-element-caption">In this short demo, you’ll see how Ops AI detects issues across your stack and automatically recommends GitHub fixes.</figcaption></figure>



<p><strong>Here’s how it works:</strong></p>



<ul class="wp-block-list">
<li><strong>Matches the stack trace to the right commit: </strong>When something breaks, Middleware looks at the stack trace, pinpoints the exact file and line where it happened, and checks your Git history for commits that touched those areas, even across different branches.<br></li>



<li><strong>Finds the real cause, not just the last deploy: </strong>The most recent commit/deploy isn’t always the culprit. Middleware looks for the meaningful change that actually caused the issue, even if it happened hours or days earlier.<br></li>



<li><strong>Puts all the commit details in your alert: </strong>When a commit is flagged, you see who made the change, the diff, the commit message, the timestamp, and the pull request link; all without leaving the <a href="https://docs.middleware.io/workflow/alerting/setup-alert">alert</a>.<br></li>



<li><strong>Keeps results clean for big codebases: </strong>For monorepos or multi-service setups, Middleware scopes its search to the correct repo structure or service, so you don’t get flooded with irrelevant matches.<br></li>



<li><strong>Connects deploys to commits: </strong>By linking deployment markers to Git commit hashes, it’s easy to confirm whether a bug came from the latest push or if it’s a regression from an older change.</li>
</ul>



<p>With this workflow, engineering teams can <strong>reduce mean time to resolution (MTTR)</strong> dramatically turning hours of detective work into minutes.</p>



<h3 class="wp-block-heading" id="h-use-case">Use Case</h3>



<p>If a deployment suddenly triggers 500 errors on a critical API, Middleware’s Ops AI can help you identify the exact commit responsible within seconds. By linking stack traces to commit history and showing the code diff, you’ll know exactly what changed and who owns it. </p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Learn more about how Middleware improves error tracking and <a href="https://middleware.io/blog/how-to-reduce-mttr/">cuts down MTTR</a> ⏱️ for modern engineering teams</p>
</blockquote>



<p>From there, you can roll back or patch the issue in minutes, without combing through logs or GitHub manually.</p>



<p>Middleware not only matches stack traces to commits but also filters logs by severity <a href="https://middleware.io/blog/log-levels-guide/">logs level </a>(Error, Warning, Info). This ensures you’re focusing on the real problem instead of sifting through noisy debug data.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="2299" height="1187" src="https://middleware.io/backend/wp-content/uploads/2025/08/stack-traces-to-commit-history-in-Middleware-OpsAI.webp" alt="stack traces to commit history in Middleware OpsAI" class="wp-image-11897"/></figure>



<h2 class="wp-block-heading" id="h-know-who-owns-the-failing-code">Know Who Owns the Failing Code</h2>



<p>Finding the root cause is one part of the problem. The next challenge? Figuring out <strong>who should fix it</strong>. Middleware uses GitHub ownership data to automatically identify the right person or team behind the broken code.</p>



<ul class="wp-block-list">
<li><strong>Maps errors to GitHub commit history:</strong> When an error occurs, Middleware examines the stack trace to pinpoint the file and function involved, then checks the commit history to determine who has worked on that code most recently or frequently.<br></li>



<li><strong>Works with individual and team ownership:</strong> Whether you use GitHub’s CODEOWNERS file or rely on commit activity, Middleware can match the error to a specific engineer or an entire team. It understands patterns across large repos, not just the last person who touched the file.<br></li>



<li><strong>Delivers alerts to the right person fast: </strong>Once the owner is identified, Middleware sends the alert directly via Slack, email, or your incident response tool so it lands with the right person immediately.<br></li>



<li><strong>Removes the “who owns this?” guessing game: </strong>During incidents, you don’t have to waste time in back-and-forth messages. Alerts include the most likely owner and full commit context, so you can go straight to fixing the problem.</li>
</ul>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>🔎 <em>Discover how Middleware correlates logs, metrics, and traces 📊 into one view for faster debugging.</em> <a href="https://middleware.io/solutions/log-analysis-correlation/">Learn More</a></p>
</blockquote>



<h3 class="wp-block-heading" id="h-use-case-0">Use Case</h3>



<p>If a frontend update in your web app suddenly starts throwing errors, Middleware’s Ops AI can point out the exact component and the developer who last committed/fixed it. </p>



<p>The alert goes straight to their inbox or chat, skipping the usual back-and-forth in Slack or manual log digging. The developer can see the commit, diff, and context right away, ship a fix, and get the app stable again before the next deployment window.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Learn how <a href="https://middleware.io/blog/how-dem-improve-user-journey/">Digital Experience Monitoring</a> (DEM) improves user journeys and how Middleware simplifies monitoring across web and mobile apps.</p>
</blockquote>



<h2 class="wp-block-heading" id="h-get-full-error-context-in-one-view">Get Full Error Context in One View</h2>



<p>Even with the right commit and code owner, engineers still need context to act fast: what triggered the error, what the user was doing, and what environment it happened in.</p>



<p>Middleware pulls all that into a single view, so you don’t need to piece it together manually.</p>



<ul class="wp-block-list">
<li>Combines GitHub commit data with runtime details like environment, stack trace, and user actions<br></li>



<li>Links error events directly to related deployments and code changes<br></li>



<li>Shows when the error first appeared and how often it’s been happening<br></li>



<li>Helps teams understand if it’s an edge case or something breaking at scale</li>
</ul>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Loved how Ops AI pinpoints commits and reduces MTTR? Dive deeper into foundational concepts behind AI-powered monitoring in our <a href="https://middleware.io/blog/what-is-ai-ops/">What is AIOps</a> guide.</p>
</blockquote>



<h3 class="wp-block-heading" id="h-use-case-1">Use Case</h3>



<p>If your SaaS product’s conversion rate starts dropping with no clear cause, Middleware’s Ops AI can detect silent errors that slip past normal monitoring. It correlates the issue to the exact commit and file, showing the dev team when and how the problem was introduced. With this context, engineers can deploy a fix before the business feels the impact.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1343" height="878" src="https://middleware.io/backend/wp-content/uploads/2025/08/Code-updated-from-suggested-fixes.webp" alt="Code updated from suggested fixes" class="wp-image-11903"/></figure>



<h2 class="wp-block-heading" id="h-reduce-time-to-resolution-with-smarter-workflows">Reduce Time to Resolution with Smarter Workflows</h2>



<p>Triaging production issues isn’t just about finding bugs; it’s about understanding context, routing it to the right team, and resolving it fast. The challenge? Most teams juggle too many tools to get the full picture. Middleware brings it all into one place, aligning error data with code, commits, and ownership so engineers can act with confidence, and not assumptions.</p>



<ul class="wp-block-list">
<li>Without this visibility, teams often have to guess whether a deploy introduced the bug, relying on cross-checking timestamps, commit logs, or deployment tools. Middleware cuts through the noise by linking errors to the exact commit that went live, helping teams identify if the issue is deployment-related within seconds.<br></li>



<li>When an error appears in production, Middleware parses the associated stack trace and automatically checks Git history to identify the related commit. This makes it easy to pinpoint not just what broke, but when and how it was introduced.<br></li>



<li>Instead of vague alerts that send engineers hunting for context, Middleware sends detailed alerts with commit info, file paths, environment, and owner. Teams get everything they need to act, right where they work.<br></li>



<li>Middleware can automatically generate GitHub issues tied to the failing commit or notify the reviewer responsible for the change. This shortens the feedback loop and ensures accountability without manual triage.<br></li>



<li>In modern architectures, knowing which team owns what is crucial. Middleware tags errors by service or team using repo structure and ownership metadata, helping large orgs route issues quickly and accurately.</li>
</ul>



<h3 class="wp-block-heading" id="h-use-case-2">Use Case</h3>



<p>In a <a href="https://middleware.io/blog/microservices-architecture/">microservices</a>-heavy environment, incident triage can eat up valuable time. Middleware’s Ops AI pinpoints the commit and author responsible for an error, even across dozens of services. Instead of passing issues through a central SRE queue, the alert goes straight to the right engineer with full context, often cutting resolution time from hours to minutes.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1320" height="896" src="https://middleware.io/backend/wp-content/uploads/2025/08/Middlewares-Ops-AI-pinpoints-the-commit.webp" alt="Middleware’s Ops AI pinpoints the commit" class="wp-image-11901"/></figure>



<p>Debugging shouldn’t feel like a never-ending guessing game. With Middleware, you get error alerts that already know where the problem started and who can fix it, so your team can jump straight to the solution.</p>



<p>No more long nights chasing bugs or waiting on answers. Just clear context, faster fixes, and more time to focus on building the things that matter.</p>



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  <p>Ready to troubleshoot smarter? Get started with Middleware Ops AI and connect your GitHub repo today. 
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<p></p>



<p>📚 <strong>Also Read</strong></p>



<ul class="wp-block-list">
<li><a href="https://middleware.io/blog/python-error-types/">Python Error Types</a>: Quick guide to identifying and fixing the most common Python errors.</li>



<li><a href="https://middleware.io/blog/reducing-error-rates-nodejs-with-apm/">Reducing Error Rates in a High-Traffic Node.js App Using APM</a>: See how APM tools help lower Node.js error rates in production.</li>



<li>Discover how smart <a href="https://middleware.io/blog/debug-faster-with-log-patterns/">log pattern detection</a> can reduce noise and surface anomalies in your logs instantly.</li>
</ul>


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What is AIOps? A Complete Guide to AI-Powered IT Operations

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Grafana vs Datadog Comparison Guide : Features, Pricing, Use Cases

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Kibana vs Grafana: Comparison Guide for Monitoring, Visualization, and Alerting

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How Digital Experience Monitoring Transforms User Journeys Across Web & Mobile

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Grafana vs New Relic: Which Observability Tool Is Right for You?

Discover 14 common application performance issues that can slow down your app, frustrate users, and hurt revenue. Learn how to detect, troubleshoot, and fix them with proven solutions.

14 Common Application Performance Issues & How to Fix Them

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How Middleware Helps Catch Deployment Issues Before They Hit Users

Discover how log pattern analysis helps you detect issues faster, reduce noise, and monitor smarter using Middleware’s AI-powered log monitoring tools.

How Log Patterns Help You Debug Faster and Monitor Smarter


<p>Error tracking and performance monitoring of the platform or applications have been stuck in the past with static dashboards and manual detective work to sift through logs to find bugs. Currently, developers spend almost 60% of their time on <a href="https://middleware.io/blog/identify-root-cause-analysis/">finding the root cause of errors</a> and fixing them.</p>



<p>At <a href="https://middleware.io/">Middleware</a>, our mission has been to help companies keep their apps available to customers all the time by providing unified <a href="https://middleware.io/blog/observability/">observability</a> by collating logs, metrics, and <a href="https://middleware.io/product/distributed-tracing/">traces</a> in one place. We have always been thinking about how to increase <a href="https://middleware.io/blog/developer-productivity/">developer productivity</a>.</p>



<p>As we are in the early years of the AI era, we started thinking about building a tool suitable for the new age of computing. New-age programming tools are helping developers generate billions of lines of code every day. </p>



<p>While that means teams are shipping more code faster, it also results in more errors creeping into the codebase and breaking production systems. As the codebase grows, it becomes harder to monitor bugs.</p>



<p>For that, we need an ever-aware tool to observe your codebase. But that’s not enough. Apart from detecting errors, it should also fix these exceptions so your engineers don’t need to hamper their sleep cycle at 3:00 AM.&nbsp;</p>



<p>That’s why we built <strong>Ops AI</strong>, our new <strong>AI co-pilot</strong> that spots and explains errors while finding ready fixes for you to apply within seconds.&nbsp;</p>



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<h2 class="wp-block-heading" id="h-why-use-ops-ai">Why use Ops AI?</h2>



<p>Ops AI is an AI observability co-pilot that works across any platform, language, or framework. Ops AI can detect and fix issues across both your frontend and backend. With full awareness of your codebase, it delivers accurate, pinpoint insights into exceptions.</p>



<p>Built on top of Middleware’s trusted <a href="https://middleware.io/product/apm/">APM</a> solution, it leverages deep context from logs, traces, and metrics to provide fast, reliable fixes.</p>



<p>At Middleware, we want to create an environment of trust and safety. That’s why we started using Ops AI for our own system and got robust results.&nbsp;</p>



<figure class="wp-block-pullquote"><blockquote><p>“We started using Ops AI at Middleware, and it now resolves over half of our production issues automatically. In tests with multiple customers, we&#8217;ve seen a detection-to-resolution rate of over 70%. We believe this is a game-changer for observability,”</p><cite>Laduram Vishnoi, Founder and CEO of Middleware</cite></blockquote></figure>



<p>The new Ops AI tool boosts on-call developer productivity by more than 80% and reduces mean time to respond (MTTR) by 5 times, allowing developers to concentrate on important tasks for creating applications.</p>



<p>Ops AI also learns from historical patterns, and as it catches and fixes more bugs, it becomes smarter as you use it more.</p>



<p>We have created this new tool with privacy-first principles. We don’t use your data to train our AI models.&nbsp;</p>



<h2 class="wp-block-heading" id="h-how-does-ops-ai-work">How does Ops AI work?</h2>



<p>On a high level, Ops AI pulls together all issues across your frontend (<a href="https://middleware.io/product/real-user-monitoring/">real-user monitoring</a>) and back-end applications (application performance monitoring) —&nbsp; including syntax errors, code exceptions, and runtime errors in a single report. These issues include details such as error type, frequency, and timeline.&nbsp;</p>



<p>After installing our latest <a href="https://github.com/middleware-labs/mw-agent">APM agent</a>, customers can connect their GitHub and let our observability AI do its work. You can connect your GitHub account, and Ops AI will automatically collect errors from all your repositories. It helps you identify and fix issues with just one click.&nbsp;</p>



<h3 class="wp-block-heading" id="h-error-issue-detection">Error/Issue Detection</h3>



<p>On a more granular level, once you install the agent, it starts monitoring your application stack. When it catches a code exception, syntax or runtime error, it will use information from traces, logs, request headers and body, error messages, and environment to create a detailed report.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1140" height="654" src="https://middleware.io/backend/wp-content/uploads/2025/06/Error-or-Issue-detection-by-OpsAI.webp" alt="Error or Issue detection by OpsAI" class="wp-image-11126"/></figure>



<p>Through GitHub integration, it helps fetch the file and code context to show the exact error location, including the file and line number in your codebase.&nbsp;</p>



<h3 class="wp-block-heading" id="h-solution-finding">Solution Finding</h3>



<p>Before solving the error, Ops AI acts as an investigator to find the root cause of the bug using context from the Middleware’s full-stack observability suite. </p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1140" height="655" src="https://middleware.io/backend/wp-content/uploads/2025/06/Code-updates-from-the-suggested-fixes-by-OpsAI-Observability-co-pilot.webp" alt="Code updates from the suggested fixes by OpsAI Observability co-pilot" class="wp-image-11127"/></figure>



<p>It observes commits made before the error, code dependencies, past data about similar errors, and other developer activities to build the complete picture to understand what caused the breakdown of the system.&nbsp;</p>



<h3 class="wp-block-heading" id="h-generating-pr-and-solutions">Generating PR and Solutions</h3>



<figure class="wp-block-image size-large is-resized"><img loading="lazy" decoding="async" width="1140" height="655" src="https://middleware.io/backend/wp-content/uploads/2025/06/Generating-PR-and-solutions-by-OpsAI-Observability-Co-pilot.webp" alt="Generating PR and solutions by OpsAI Observability Co-pilot" class="wp-image-11128" style="width:620px;height:auto"/></figure>



<p>All these details are passed to our refactoring agent to get suggestions for the bug fix. Finally, apply them to the code. Ops AI only creates a PR if it&#8217;s more than 95% confident of the fix. </p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1140" height="629" src="https://middleware.io/backend/wp-content/uploads/2025/06/Fix-development-application-issue-by-OpsAI-observability-co-pilot.webp" alt="Fix development application issue by OpsAI observability co-pilot" class="wp-image-11130"/></figure>



<p>For a lower confidence score, it provides all the context for the error to engineers to start debugging without having to spend time going through logs.</p>



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<h2 class="wp-block-heading" id="h-what-can-aiops-co-pilot-do">What Can AIOps Co-Pilot Do?</h2>



<ul class="wp-block-list">
<li><strong>Error Monitoring and Summarization: </strong>The tool collects all errors from the front-end, back-end, error logs, and code exceptions to present them in an easily readable format that shows error type, error message, exception, and error code line with complete stack trace. You can also track and manage errors in a more efficient way by assigning statuses like &#8216;reviewed&#8217;, &#8216;resolved&#8217;, and &#8216;ignored&#8217;.</li>



<li><strong>Detailed Root Cause Analysis: </strong>Find the exact place that caused the error<strong> </strong>through a link to the codebase. It provides detailed error information, including the file name, code line, stack trace, and even related variables and version details. This makes it easy to understand what went wrong, and you can start fixing issues right away without wasting time searching through logs or code.</li>



<li><strong>One-click error resolution: </strong>With Ops AI, you can view the root cause and a recommended one-click fix on a single screen. You can also generate a PR with fixed bugs through this interface to save time and get your application up and running again.</li>



<li><strong>Preserves your data privacy: </strong>Ops AI is designed to maintain the security and integrity of your data. All your inputs and responses are private, and only your team can access them. Plus, the tool doesn’t share AI-generated responses publicly outside your organization.&nbsp;</li>
</ul>



<p>This AI observability co-pilot summarizes errors, provides root cause analysis, and even auto-generates fixes.</p>



<h2 class="wp-block-heading" id="h-limitations-and-what-is-next">Limitations and What is next?</h2>



<p>This launch is the first step towards the future of <strong><em>AI-powered observability</em></strong>. We are working on building upgrades to Ops AI to cover Logs and Kubernetes monitoring.</p>



<p>Our goal is for Ops AI to generate a ready-to-use root cause analysis report before system engineers start investigating. This gives them a head start and saves valuable debugging time.</p>



<p>Middleware and Ops AI currently support Node.js, Golang, Python, Java, and JavaScript. However, we are scaling our development to be compatible with other languages, including Ruby, .NET, PHP, and more. On the version control front, we already have GitHub integration with GitLab and Bitbucket support in the works.&nbsp;</p>



<h2 class="wp-block-heading" id="h-how-to-get-started-with-ops-ai-nbsp">How to get started with Ops AI&nbsp;</h2>



<p>At Middleware, we have been helping our clients be AI-ready for a while now. First, our AI-powered search allowed our customers to use natural language to make sense of their data. Then, we used AI to boost <a href="https://middleware.io/blog/anomaly-detection/">anomaly detection</a> and make the systems of our clients more reliable. With Ops AI, we are stepping into the agentic era to create a reliable partner for engineering teams to seamlessly handle production issues.&nbsp;</p>



<p>Ops AI is available for all Middleware’s existing and new customers starting from 25th June. You can <a href="https://app.middleware.io/auth/register/">try</a> it for 14 days, no extra setup required.&nbsp;</p>



<p>If you have any questions or feedback, we are happy to listen to them. Please <a href="https://middleware.io/contact-us/">reach out to us</a>.&nbsp;</p>



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We’re excited to launch Ops AI — your new AI observability co-pilot. Built on Middleware’s APM, it helps developers detect, debug, and fix issues faster across the stack. Boost productivity and cut MTTR by 5x with every bug it resolves.

Introducing Ops AI: Observability Co-Pilot to Resolve Your Production Issues Instantly


<p>Before <a href="https://middleware.io/blog/understanding-the-docker-ecosystem/">Docker</a> existed, developers had a hard time trying to package, ship and deploy their applications consistently across various environments. By enabling the much-needed <a href="https://middleware.io/blog/containerization/">containerization</a>, Docker gives you the superpower that ensures your application behaves the same way regardless of the environment. However, with this great power comes the great responsibility of monitoring and troubleshooting your applications effectively.&nbsp;</p>



<p>In this roundup, we’ll introduce you to some robust logging mechanisms that you can utilize for your&nbsp; Docker container logs to provide your application the reliability and performance it needs.&nbsp;</p>



<p>We’ll dive deep into Docker container logs, explore some common Docker container logs commands, and understand how you can access and manage them.&nbsp;</p>



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<h2 class="wp-block-heading" id="h-what-are-docker-container-logs">What Are Docker Container Logs?</h2>



<p>When you run applications within containers, Docker container logs capture the standard output and error messages your application generates. Think of these as application logs, but specifically for your container.&nbsp;</p>



<p>Typically, docker container logs give you information about any exceptions or errors your application throws, status messages, events emitted by your application, relevant performance metrics, etc. These logs are extremely valuable to provide insights for troubleshooting and understanding the behavior of your application.&nbsp;</p>



<h2 class="wp-block-heading" id="h-accessing-docker-container-logs">Accessing Docker Container Logs</h2>



<p>To access your Docker container logs,&nbsp; you can run the following command using Docker CLI:</p>



<pre class="wp-block-code"><code>docker logs my-container</code></pre>



<p>You can also enable these logs to run in real-time by using the -f flag and view Docker container logs:</p>



<pre class="wp-block-code"><code>docker logs -f my-container</code></pre>



<p>Alternately, you can also view logs for a specific service using Docker Compose:</p>



<pre class="wp-block-code"><code>docker-compose logs web-backend</code></pre>



<p>The above command uses Docker Compose to show you logs for your service called “web-backend”.&nbsp;</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Understand the fundamentals of <a href="https://middleware.io/blog/what-is-log-monitoring/">log monitoring</a> and how it helps proactively detect issues before they impact users.</p>
</blockquote>



<h3 class="wp-block-heading" id="h-log-drivers-and-why-they-re-important">Log Drivers and why they’re important</h3>



<p>Log drivers in Docker determine where and how your container logs should be stored and managed. This could be a JSON file, which is the default log driver that stores all your Docker logs as JSON.&nbsp;</p>



<p>Other options for log drivers include syslog, which logs your Docker container logs to the syslog daemon, journald, which integrates with systemd journal, or <strong>gelf</strong>, <strong>fluentd</strong>, <strong>awslogs</strong> for centralized logging.</p>



<p>Each log driver has its driver-specific features, including storage persistence, scalability, and ease of use.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Understanding <a href="https://middleware.io/blog/docker-logging-tutorial/">Docker Logging</a>. Explore how Docker handles logs, best practices, and advanced options for managing them efficiently.</p>
</blockquote>



<h3 class="wp-block-heading" id="h-configuring-log-drivers">Configuring Log Drivers</h3>



<p>Docker CLI lets you configure the log driver for your Docker container logs at the time of creating your container:</p>



<pre class="wp-block-code"><code>docker run --log-driver syslog --log-opt syslog-address=udp://192.168.0.42:514 my-container</code></pre>



<p>In the above command, the main <code>--log-driver</code> flag specifies the log driver we’re using, which in this case is the syslog. Then, the -log-opt flag provides options specific to the selected log driver. After that, we tell Docker the address and port of the syslog server using syslog-address. Finally, the container called “<code>my-container</code>” is run, whose logs are routed to the syslog server at the specified address.&nbsp;</p>



<p>To directly configure the log driver options in the <code>/etc/docker/daemon.json</code> file, modify it’s contents as shown below:</p>



<pre class="wp-block-code"><code>{
  "log-driver": "json-file",
  "log-opts": {
    "max-size": "10m",
    "max-file": "3"
  }
}</code></pre>



<h2 class="wp-block-heading" id="h-managing-and-viewing-docker-logs">Managing and Viewing Docker Logs</h2>



<p>Developers often burn entire afternoons chasing down what turned out to be straightforward configuration errors, all because they were drowning in log noise. When you can effectively manage and view your logs, you can narrow down the ones that can cause critical problems. </p>



<p>Moreover, staying on top of your container logs can help you with deeper log analysis and avoid problems such as your disk space suddenly running out and causing your entire system to halt.&nbsp;</p>



<h3 class="wp-block-heading" id="h-viewing-and-filtering-logs">Viewing and Filtering Logs</h3>



<p>Docker provides several different ways to view Docker container logs and filter them. This eventually helps you focus on specific logs that you need to focus on during debugging and troubleshooting.&nbsp;</p>



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<p>For instance, the below command will show you all the logs from the last 30 minutes:</p>



<pre class="wp-block-code"><code>docker logs --since 30m my-container&nbsp;</code></pre>



<p>But you’re not just limited by a time duration, you can view logs for a precise moment in time, like a specific timestamp:</p>



<pre class="wp-block-code"><code>docker logs --since "2024-01-15T10:30:00" my-container&nbsp;</code></pre>



<p>The above command will show you all the logs taken on the exact timestamp specified. Moreover, you can also view logs until a specific time:</p>



<pre class="wp-block-code"><code>docker logs --until "2024-01-15T11:00:00" my-container&nbsp;</code></pre>



<p>The <code>--until</code> flag returns all the logs till that moment in time. You can combine the <code>--since</code> flag to get a window of time and view all logs in that window, as shown below:</p>



<pre class="wp-block-code"><code>docker logs --since "1h30m" --until "30m" my-container</code></pre>



<p>You can also follow logs in real-time with timestamps:</p>



<pre class="wp-block-code"><code>docker logs -f -t my-container&nbsp;</code></pre>



<p>The above will show you logs alongside their timestamp. To reduce noise from unwanted logs, you can also stream logs from the last 50 lines or so:</p>



<pre class="wp-block-code"><code>docker logs -f --tail 50 my-container</code></pre>



<p>The -f flag is like your messiah when it comes to debugging during development. Watching your application’s behavior in real-time makes it easier to spot any issues as they happen.&nbsp;</p>



<p>But how do you see logs for a specific pattern? Using advanced log filtering, you can specify a pattern using grep:</p>



<pre class="wp-block-code"><code>docker logs my-container 2&gt;&amp;1 | grep "ERROR"</code></pre>



<p>The above log redirects logs containing the word <code>“ERROR”</code> to your window. Let’s say you have a web application whose container logs look like this:</p>



<pre class="wp-block-code"><code>2024-01-15 10:30:15 INFO Starting application
2024-01-15 10:30:16 INFO Database connected
2024-01-15 10:30:20 ERROR Failed to connect to Redis
2024-01-15 10:30:25 INFO Request processed successfully
2024-01-15 10:30:30 ERROR Timeout connecting to external API</code></pre>



<p>As you can see, the container logs show that your application failed to connect to Redis and timed out connecting to an external API. To dig deeper, you can retrieve these relevant logs using the above command.&nbsp;</p>



<h3 class="wp-block-heading" id="h-log-size-management-and-rotation">Log Size Management and Rotation</h3>



<p>Uncontrolled logs can get out of hand easily and start taking up more disk space than needed. This can lead to crashing your entire system. To prevent this, you should set limits to your logs when creating a container:</p>



<pre class="wp-block-code"><code>docker run -d \ --name my-app \ --log-driver json-file \ --log-opt max-size=10m \ --log-opt max-file=5 \ nginx:latest</code></pre>



<p>Using the <code>max-size=10m</code>, you specify the maximum size of a file that your logs can take. Similarly, using the&nbsp; <code>max-file=5</code>, you can declare the maximum number of files that will be used for your <a href="https://middleware.io/product/container-monitoring/">container logs</a>. All in all, this will set a size limit of 50MB.&nbsp; When the current log file reaches 10MB, Docker creates a new one and eventually removes the oldest when the limit is exceeded.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>If you’re facing storage bloat, learn how to free up unused containers, volumes, and images in our <a href="https://middleware.io/blog/docker-cleanup/">Docker Cleanup</a> Guide.</p>
</blockquote>



<h3 class="wp-block-heading" id="h-log-file-manipulation">Log File Manipulation</h3>



<p>There are cases where you might directly need to access the log files and manipulate the logs. For example, when you need more power and flexibility, such as advanced text processing, performance upside with large log files, etc. </p>



<p>For instance, consider the below docker command that logs the entire log into memory, slowing down the process for large logs in GBs:</p>



<pre class="wp-block-code"><code>docker logs huge-container | grep "ERROR"</code></pre>



<p>You can directly access the file instead, which would be much faster:</p>



<pre class="wp-block-code"><code>grep "ERROR" $(docker inspect --format='{{.LogPath}}' huge-container)</code></pre>



<p>Here’s another example where you might want to get lines <code>1000-1500</code> from a log file, which is harder to do directly with Docker CLI. Instead, you can directly access the file and retrieve those lines using file manipulation:</p>



<pre class="wp-block-code"><code>tail -n +1000 $(docker inspect --format='{{.LogPath}}' my-container) | head -500&nbsp;</code></pre>



<p>You can still use Docker CLI for the exact Docker container logs location:</p>



<pre class="wp-block-code"><code>docker inspect --format='{{.LogPath}}' my-container&nbsp;</code></pre>



<h2 class="wp-block-heading" id="h-best-practices-for-efficient-log-management">Best Practices for Efficient Log Management</h2>



<p>Here are some quick best practices you should keep in mind to get an efficient log management system for your Docker container logs:</p>



<ul class="wp-block-list">
<li><strong>Rotate logs regularly:</strong> Disk overflow is a common consequence of not rotating Docker container logs regularly. Configuring the daemon with rotation settings can ensure that you always have enough disk space available.</li>
</ul>



<ul class="wp-block-list">
<li><strong>Set log size limits: </strong>Use flags such as max-size and max-file, as we explored in the previous section, to ensure proper file size restrictions are in place. An unpredictable surge in traffic on your application could easily eat up a lot of unwanted memory if size limits are not in place.&nbsp;</li>
</ul>



<ul class="wp-block-list">
<li><strong>Follow structured logging:</strong> When streaming Docker container logs, parsing or running custom analytics, use structured formats only, like <code>JSON</code>. This can help you not get tangled in processing your logs and give you more flexibility in terms of working on top of the logs.&nbsp;</li>
</ul>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p>Learn how to structure logs using formats like JSON for better readability and machine processing. See <a href="https://middleware.io/blog/log-formatting/">Log Formatting</a> Best Practices.</p>
</blockquote>



<h2 class="wp-block-heading" id="h-centralized-logging-and-routing-logs-nbsp">Centralized Logging and Routing Logs&nbsp;</h2>



<p>Modern applications have complex architectures, interfaces and communicate extensively with external APIs. Practically, it’s best to have all your Docker container logs centralized in one place for viewing, accessing, managing and processing. Not only does centralized logging simplify management across multiple containers and environments, but using dedicated logging tools can give you benefits such as advanced filtering and real-time analytics.&nbsp;</p>



<p>The given command shows how you can route your Docker container logs to a popular monitoring platform <a href="https://middleware.io/">Middleware</a>:</p>



<pre class="wp-block-code"><code>docker run --log-driver fluentd --log-opt fluentd-address=middleware.io:24224 my-app</code></pre>



<h2 class="wp-block-heading" id="h-best-practices-for-docker-logging">Best Practices for Docker Logging</h2>



<p>As we’re close to a wrap, let’s also understand some best practices that can help us utilize Docker container logs effectively. We’ve already explored how structured logging formats like JSON can be helpful for readability and parsing logs for further analysis.&nbsp;</p>



<p>Security is paramount for every organization and their customers. A common security consideration often missed is logging sensitive data. You should never log any kind of sensitive data like passwords, auth tokens, payment information, etc.&nbsp;</p>



<p>You can save countless hours of log analysis and management by using a reliable <a href="https://middleware.io/blog/log-management/">log management</a> tool like Middleware. Which do all the heavy lifting and offer extremely valuable features like <a href="https://middleware.io/blog/log-aggregation/">log aggregations</a>, automated notifications and alerting for critical log events.</p>



<p>Finally, ensure you regularly audit and archive your container logs to meet any compliance standards necessary. Log management solutions automate audit trails and simplify regulatory compliance out of the box, so you can use them directly to meet compliance standards conveniently.</p>



<h3 class="wp-block-heading" id="h-conclusion">Conclusion</h3>



<p>By combining the power of your Docker container logs with effective log management and dedicated log management tools like Middleware, you can ensure reliability for your application. Following the best practices is just as crucial, so make sure you’re not missing them.&nbsp;</p>



<h3 class="wp-block-heading" id="h-faqs">FAQs</h3>


		<section		help class="sc_fs_faq sc_card    "
				>
				<h3>How do I check Docker container logs?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>To check the Docker container logs, you can use the Docker CLI command docker logs my-container</p>

			</div>
		</div>
		</section>
				<section		help class="sc_fs_faq sc_card    "
				>
				<h3>How can I follow Docker container logs in real-time?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>When you use the command docker logs -f my-container, your Docker container logs are streamed in real-time.</p>

			</div>
		</div>
		</section>
				<section		help class="sc_fs_faq sc_card    "
				>
				<h3>What are the best practices for managing Docker container logs?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>Some best practices for managing Docker container logs include regularly rotating logs, setting size limits using flags like max-size and max-file, using structured log formats like JSON, avoiding sensitive information in logs, and implementing centralized log management tools such as Middleware.</p>

			</div>
		</div>
		</section>
				<section		help class="sc_fs_faq sc_card    "
				>
				<h3>How do I filter Docker container logs for specific errors?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>The command docker logs my-container 2&gt;&amp;1 | grep &#8220;ERROR&#8221; can be used to filter Docker container logs for specific errors</p>

			</div>
		</div>
		</section>
				<section		help class="sc_fs_faq sc_card    "
				>
				<h3>What is structured logging, and why is it important?</h3>				<div>
						<div class="sc_fs_faq__content">
				

<p>When you format your Docker container logs into a structured format, such as JSON, it becomes easier to parse, analyse, and automate monitoring.</p>

			</div>
		</div>
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<p>At Middleware, our motto is to help and transform the process of how developers and organizations handle <a href="https://middleware.io/blog/observability/">observability</a> at scale. We are on a mission to provide a full-stack observability platform that empowers developers to build, monitor, and troubleshoot infrastructure and applications with unparalleled ease and efficiency. </p>



<p>We are currently helping out many companies with their observability problems, and we believe that observability is not just a tool but the cornerstone of modern applications.</p>



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<p>The belief in helping organizations has driven us to relentlessly innovate and create a platform that seamlessly integrates logs, <a href="https://middleware.io/blog/what-is-distributed-tracing/">traces</a>, and metrics into a single pane of glass. With detailed insight, we are helping organizations to rapidly identify issues and effortlessly solve them, enhancing operational efficiency, minimizing downtime, and reducing observability costs.</p>



<p>At Middleware we strongly believe in innovation and excellence and with that motto comes a lot of responsibility, we constantly enhance our platform and add new <a href="https://middleware.io/platform/integrations/">integrations</a> to make the platform better and have more access to data. </p>



<p>Our goal is to provide developers with the most comprehensive and seamless observability experience possible. That’s why we have integrated Kapstan into our ecosystem to further elevate the developer experience. This integration ensures that developers have the tools they need to succeed in today’s fast-paced, cloud-native world.</p>



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<h2 class="wp-block-heading" id="h-making-the-deployments-more-insightful-a-shared-vision-with-kapstan">Making the Deployments More Insightful: A Shared Vision with Kapstan</h2>



<p>Kapstan’s vision deeply resonates with our own as they also believe that “A well-observed system is the only well-behaved system”. We are gearing up together to enhance the developer experience through observability and automating the deployment process.</p>



<p><a href="https://www.kapstan.io/">Kapstan</a> is a comprehensive platform designed to simplify Kubernetes management while unlocking its full potential. It empowers developers to deploy applications using intent-based workflows without worrying about the configuration files. </p>



<p>Middleware steps in here to make the developer experience more seamless by providing complete end-to-end observability, streamlining insights, and ultimately optimizing their technology stack for success.</p>



<h2 class="wp-block-heading" id="h-announcing-our-partnership-with-kapstan-io">Announcing Our Partnership with Kapstan.io</h2>



<p>In that spirit, we are thrilled to announce our strategic partnership with Kapstan.io!</p>



<p>Kapstan helps developers instantly provision, deploy and manage complex cloud infrastructure in their own cloud account. They give engineers world-class developer experience in managing infrastructure and deploying applications, databases, jobs, and more without the infrastructure sprawl or the platform lock-in of Vercel/Heroku.</p>



<p>For larger engineering organizations with DevOps teams, Kapstan offers a fully customizable abstraction over Kubernetes clusters with getting bogged down in the intricacies of infrastructure management such as Kubernetes upgrades, repetitive tasks, and one-off tickets from developers to help them provision an S3 bucket.&nbsp;</p>



<h2 class="wp-block-heading" id="h-introducing-the-middleware-x-kapstan-integration">Introducing the Middleware x Kapstan Integration</h2>



<p>We are excited to announce a full-fledged integration of Middleware for Kapstan users to ease their Observability headache. With just a single click, Kapstan customers can now observe their environments within Middleware with the integration, gaining access to a unified platform that brings together logs, traces, and metrics. </p>



<p>This integration gives developers a holistic view of their applications, enabling faster issue resolution and smoother operations.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1890" height="1013" src="https://middleware.io/backend/wp-content/uploads/2025/04/Middleware-Kapstan-Integration-1.webp" alt="Middleware Kapstan Integration" class="wp-image-10846"/></figure>



<h2 class="wp-block-heading" id="h-a-shared-commitment-to-developer-experience">A Shared Commitment to Developer Experience</h2>



<p>This partnership is more than just a collaboration—it’s our shared commitment to improving the developer experience together. By combining Middleware’s observability expertise with Kapstan’s intuitive IDP and ZeroOps Kubernetes solution, we would create a tech ecosystem where developers can focus on what truly matters: building innovative, reliable, and scalable applications.</p>



<p>We are thrilled to embark on this journey with Kapstan and look forward to the incredible value this partnership will bring to developers worldwide. Stay tuned for more updates as we continue to innovate and redefine the future of the developer experience together!</p>



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Middleware and Kapstan Join Forces to Enhance Kubernetes Observability for Developers

Kapstan Partner with Middleware to Maximize Developer Experience with Observability


<p>I’m sure, as an engineer, there’s no bigger nightmare than a production outage at 3 AM. We live in a world where software is becoming more complex by the minute. From distributed architectures to <a href="https://middleware.io/blog/what-is-container-orchestration/">container orchestration</a> and microservices, an <a href="https://middleware.io/blog/observability/tools/">observability tool</a> is a must-have digital vigilante for your system and infrastructure.&nbsp;</p>



<p>Prometheus is a powerful open-source monitoring tool that enables system administrators and engineers to collect useful data points about their system&#8217;s health and performance. </p>



<p>These data points or metrics are called Prometheus metrics, help in tracking resource utilization, identifying system bottlenecks, and ensuring smooth operations. If you&#8217;re wondering <strong>what is Prometheus metric</strong>, it is essentially a time-series data point that represents system behavior over time.</p>



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<p>In this guide, we&#8217;ll unravel how Prometheus metrics provide visibility into your systems. By the end of this post, you&#8217;ll have everything under your belt to make the most of Prometheus metrics.</p>



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<h2 class="wp-block-heading" id="h-what-are-prometheus-metrics">What Are Prometheus Metrics?</h2>



<p>Prometheus collects data points that represent the behavior and <a href="https://middleware.io/blog/what-is-application-performance-monitoring/">performance of your application</a> or infrastructure. These data points, also known as <strong>Prometheus metrics</strong>, are stored in a <strong>Prometheus metrics format</strong>, which follows a structured approach to time-series data. </p>



<p>For instance, a data point that measures your <a href="https://middleware.io/blog/efficient-server-utilization/">server&#8217;s CPU consumption</a>, the number of requests your service receives, or the average response time of your server are all examples of Prometheus metrics.</p>



<p>Let’s look at a <strong>Prometheus metrics example</strong> to understand how these metrics work in <a href="https://middleware.io/blog/what-is-real-user-monitoring/">real-time monitoring</a>. Consider <a href="https://middleware.io/blog/prevent-cpu-overload-on-linux-servers/">CPU usage</a> and average response time for a web server:</p>



<p><strong>CPU usage:</strong></p>



<p>&#8211; &nbsp; 10:00:00 AM: 45% utilization</p>



<p>&#8211; &nbsp; 10:00:15 AM: 48% utilization</p>



<p>&#8211; &nbsp; 10:00:30 AM: 73% utilization (sudden spike)</p>



<p><strong>Average response time:</strong></p>



<p>&#8211; 10:00:00 AM: 85 ms</p>



<p>&#8211; 10:00:15 AM: 90 ms</p>



<p>&#8211; 10:00:30 AM: 250 ms</p>



<p>Prometheus stores metrics as time-series data in a structured <strong>Prometheus metrics format</strong>, allowing engineers to query, visualize, and analyze them to identify performance trends. </p>



<p>You can effectively monitor system health and make data-driven decisions by understanding different&nbsp;Prometheus metrics types, such as counters, gauges, histograms, and summaries. </p>



<p>For instance, in the above example, the time-series data can be used to visualize the correlation between increased request rate and the CPU/memory spikes. We see that there was a sudden spike that happened at 10:00:30 AM, so Prometheus can also send alerts for visibility.&nbsp;</p>



<h2 class="wp-block-heading" id="h-understanding-prometheus-metrics-types-and-their-role">Understanding Prometheus Metrics Types and Their Role</h2>



<p>Before we dive deeper into each metric type and their role, let&#8217;s first understand some key concepts related to Prometheus metrics.&nbsp;</p>



<h3 class="wp-block-heading" id="h-1-nbsp-labels-nbsp-nbsp">1.&nbsp; Labels&nbsp;&nbsp;</h3>



<p>Labels are key-value pairs that give dimension to the metrics like instance, method,&nbsp;service, etc.</p>



<p>For instance, a metric like <strong><code>http_requests_total</code></strong> might include labels such as <code><strong>method="POST</strong>"</code>, <strong><code>service="checkout"</code></strong>, and<strong> <code>instance="server-1"</code></strong>.&nbsp;</p>



<p>If you wish to query metrics specifically for your checkout service, you can do so using a label selector in PromQL:</p>



<pre class="wp-block-code"><code>http_requests_total{service="checkout"}</code></pre>



<p>These queries fetch data from the <strong>Prometheus metrics endpoint</strong>, which serves the latest metric values collected from various services. The <strong>Prometheus metrics endpoint</strong> allows tools like Grafana and Middleware to retrieve metrics in real time for visualization and alerting.</p>



<h3 class="wp-block-heading" id="h-2-nbsp-metric-name-and-value-nbsp-nbsp">2.&nbsp; Metric Name and Value&nbsp;&nbsp;</h3>



<p>The name of a metric describes what the metric represents, whereas the value is the actual data point associated with that metric. For instance, a metric used to represent CPU usage is called</p>



<p>&nbsp;<strong><code>cpu_usage_seconds_total</code></strong>, which tells you how many seconds the CPU has been used in total.&nbsp;&nbsp;&nbsp;</p>



<p>For instance, if the <strong><code>cpu_usage_seconds_total</code></strong> metric has a value of <strong>450</strong> for <strong><code>instance="server-2"</code></strong>. This means that your server-2&#8217;s CPU has been used for 450 seconds since last it was started or reset.&nbsp;</p>



<p>Also, with PromQL, you can query the rate of change for this metric.</p>



<pre class="wp-block-code"><code>rate(cpu_usage_seconds_total{instance="server-2"}&#91;5m])</code></pre>



<p>The result of the above query tells you how fast your CPU usage has increased in the last 5 minutes. You can check the same for any specified period. You can use this information to decide if you need to scale up resources. </p>



<p>For example, a value of 0.75 or higher may indicate a significant spike in CPU usage that you may need to address.&nbsp;</p>



<h3 class="wp-block-heading" id="h-3-nbsp-prometheus-metric-types-nbsp-nbsp">3.&nbsp; Prometheus Metric Types&nbsp;&nbsp;</h3>



<p>We&#8217;ve seen earlier the four core metrics that Prometheus provides, but let&#8217;s examine them more thoroughly.</p>



<h4 class="wp-block-heading" id="h-counters">Counters</h4>



<p>A counter metric, as the name suggests, is a metric that counts or cumulates the value. It only gets incremented or reset to 0. You can use counter metrics to track the number of requests a service has handled, tasks a job has completed, the number of errors or crashes a system has encountered, etc.&nbsp;</p>



<p>For instance, you could have a counter metric <strong><code>requests_total</code></strong>. When its value changes from 100 to 150, we know there have been 50 new requests since the last measurement.&nbsp;</p>



<p>Using PromQL, we can also get a _rate_ of requests over time as shown below:</p>



<pre class="wp-block-code"><code>rate(requests_total&#91;5m])</code></pre>



<h4 class="wp-block-heading" id="h-gauges">Gauges</h4>



<p>To track values that can fluctuate over time, a gauge metric is used. It can increase in value, or go down/decrease in value. You can use a gauge to measure how much memory is used or the number of active sessions for your users.&nbsp;</p>



<p>For instance, consider a gauge metric called <strong><code>memory_usage_bytes</code></strong> . If it has a value of 2,147,483,648 it means that 2GB of memory has been consumed up to that point.&nbsp;</p>



<h4 class="wp-block-heading" id="h-histograms">Histograms</h4>



<p>Let&#8217;s say you want to understand how quick or slow your application appears to your users. Measuring response time would be helpful here. However, not every user may get the same response time. So it may be more helpful to get a range of response times, say from 20ms to 1000ms. </p>



<p>To get a clearer picture, you might want to see these response times sorted with a count telling you how many requests fall into each category.</p>



<figure class="wp-block-table"><table class="has-fixed-layout"><tbody><tr><td>Response Time20ms</td><td>Count150</td></tr><tr><td>50ms</td><td>200</td></tr><tr><td>100ms</td><td>400</td></tr><tr><td>500ms</td><td>150</td></tr></tbody></table></figure>



<p>Histograms in Prometheus are like organized bucket systems that help you understand how long things take or how big things are.&nbsp;</p>



<p>A histogram metric might look like this (in a simplified text format):</p>



<pre class="wp-block-code"><code># HELP request_duration_seconds Request duration in seconds
&nbsp; &nbsp; # TYPE request_duration_seconds histogram
&nbsp; &nbsp; request_duration_seconds_bucket{le="0.05"} 240
&nbsp; &nbsp; request_duration_seconds_bucket{le="0.1"} 638
&nbsp; &nbsp; request_duration_seconds_bucket{le="0.2"} 912
&nbsp; &nbsp; request_duration_seconds_bucket{le="0.5"} 980
&nbsp; &nbsp; request_duration_seconds_bucket{le="1"} 995
&nbsp; &nbsp; request_duration_seconds_bucket{le="+Inf"} 1000
&nbsp; &nbsp; request_duration_seconds_sum 123
&nbsp; &nbsp; request_duration_seconds_count 1000</code></pre>



<p>From this data, you can calculate the distribution of request durations. Some useful features of Histograms are statistics like median response time (50th percentile) and 90th percentile (the time below which 90% of your requests are completed) to get a broader sense of how your application is performing.</p>



<h4 class="wp-block-heading" id="h-summaries">Summaries</h4>



<p>Summaries are similar to histograms but they also give you information like the sum of all the observations and configurable quantiles like the 95th percentile directly, without the need for any buckets.&nbsp;&nbsp;</p>



<p>Let&#8217;s say you&#8217;re now interested in understanding how long it takes for your web application to process a login request for a user. Using Prometheus, you can set up a summary metric called <strong><code>login_duration_seconds</code></strong>.</p>



<pre class="wp-block-code"><code> login_duration_seconds{instance="app-server-1",quantile="0.5"} 0.042
&nbsp; &nbsp; login_duration_seconds{instance="app-server-1",quantile="0.9"} 0.123
&nbsp; &nbsp; login_duration_seconds{instance="app-server-1",quantile="0.95"} 0.187
&nbsp; &nbsp; login_duration_seconds_sum{instance="app-server-1"} 75.3
&nbsp; &nbsp; login_duration_seconds_count{instance="app-server-1"} 1250</code></pre>



<p>You can see from the above summary that the average login time is 0.042 seconds (42ms). This is the median or the 50th percentile.&nbsp;</p>



<p>The trade-off here is that summaries are somewhat more resource-intensive and less flexible compared to histograms when it comes to combining data across multiple instances. </p>



<p>However, they can be incredibly useful if you want immediate, per-instance percentile calculations without having to define buckets as with histograms.</p>



<h2 class="wp-block-heading" id="h-best-practices-for-working-with-various-prometheus-metrics">Best Practices for Working with Various Prometheus Metrics</h2>



<p>We’ve seen how useful Prometheus metrics can be, but now let’s understand some best practices we can adopt when working with these metrics.&nbsp;</p>



<h3 class="wp-block-heading" id="h-1-nbsp-organize-metric-names-and-labels-clearly-nbsp">1.&nbsp; Organize Metric Names and Labels Clearly&nbsp;</h3>



<p>Ensure that your metrics follow a consistent naming convention. For instance, the metric name <code>node_cpu_usage_seconds_total</code>&nbsp; for CPU usage is self-descriptive in nature. </p>



<p>Organizing metric names and labels clearly will make it easier for anyone to understand what the metric is for. Also, avoid creating labels that can have too many values to keep your metrics database simple and reliable.&nbsp;</p>



<h3 class="wp-block-heading" id="h-2-nbsp-choosing-the-right-metric-type">2.&nbsp; Choosing the Right Metric Type</h3>



<p>Each Prometheus metric type has its own well-defined purpose. Be very strict about using the right metric type.&nbsp;</p>



<p>For a metric with continuously incrementing values, use &nbsp;Counters . For metric values that can go up or down, like current state measurements, use&nbsp; Gauges. If you need on-the-fly quantiles, for instance, use&nbsp;Summaries.&nbsp; To measure the frequency or distribution of metrics across a range of values, use Histograms.&nbsp;&nbsp;&nbsp;</p>



<h3 class="wp-block-heading" id="h-3-nbsp-avoid-overusing-histograms-nbsp-nbsp-nbsp">3.&nbsp; Avoid Overusing Histograms&nbsp;&nbsp;&nbsp;</h3>



<p>While histograms are powerful, each histogram can generate many time series based on bucket definitions. This can lead to high cardinality and storage overhead. If you don’t need bucket-based distributions, a gauge or counter might suffice.</p>



<p>Whenever you do need to use histograms, make sure you carefully select the buckets and consider using fewer buckets for less critical metrics.&nbsp;</p>



<h3 class="wp-block-heading" id="h-4-nbsp-use-clear-and-meaningful-labels">4.&nbsp; Use Clear and Meaningful Labels</h3>



<p>If a label can have thousands or millions of values, it&#8217;s probably not suitable for Prometheus. So avoid using labels for data that has large cardinality like UserID, email addresses, etc.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p>



<h3 class="wp-block-heading" id="h-5-nbsp-keep-alerting-thresholds-realistic-nbsp-nbsp-nbsp-nbsp">5.&nbsp; Keep Alerting Thresholds Realistic&nbsp;&nbsp;&nbsp;&nbsp;</h3>



<p>Poorly defined alerts will defeat their purpose. Define sensible thresholds that account for known fluctuations. For instance, setting an alert for CPU usage above 50% might be too sensitive. A reasonable alert threshold might be close to 90% or even 95%.&nbsp;</p>



<p>Also, you should combine multiple metrics for more accurate alerting. For example, CPU usage and memory usage can be combined into a single alert.</p>



<h2 class="wp-block-heading" id="h-collecting-and-visualizing-prometheus-metrics-with-middleware">Collecting and Visualizing Prometheus Metrics with Middleware</h2>



<p>You can integrate Prometheus into your own system. A lot of teams prefer to use external tools for Prometheus custom metrics dashboards and visualizations of their Prometheus metrics. You can use an observability tool like Middleware to create custom visualizations and dashboards for common metrics like CPU, memory, disk I/O, etc.&nbsp;</p>



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<h3 class="wp-block-heading" id="h-prometheus-integration-with-middleware">Prometheus Integration with Middleware</h3>



<p>Integrating Prometheus with Middleware is a breeze. You can follow along with this setup guide or refer to the <a href="https://docs.middleware.io/integrations/prometheus-integration?_gl=1*1vlajmz*_ga*MTY1NTAxODc3MS4xNzIxNjMxODU2*_ga_2KBHR7YB2G*MTc0MTYyNjU3MC40NDQuMS4xNzQxNjI2NjQzLjAuMC4w">official docs</a> as well.&nbsp;</p>



<p>Login to Middleware and go to the installation page from the left-hand bottom side of the home screen.</p>



<p>Then, go to the <a href="https://app.middleware.io/installation#integration/allintegration">Integration Section</a></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="2339" height="1168" src="https://middleware.io/backend/wp-content/uploads/2025/03/Prometheus-Integration-with-Middleware.jpg" alt="Prometheus Integration with Middleware" class="wp-image-9659"/></figure>



<p>Search for &#8220;Prometheus Integration&#8221; and click on the Prometheus card from inside the &#8220;Available&#8221; tab.&nbsp; Here, you can select the host and configure your cluster. You’ll need to add the required Prometheus annotations in your Kubernetes deployment’s metadata as mentioned in the instructions.</p>



<p>Let&#8217;s go with &#8220;Annotation Based Scraping&#8221; for now. Click on the &#8220;Save&#8221; button.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="2319" height="1138" src="https://middleware.io/backend/wp-content/uploads/2025/03/Annotation-Based-Scraping-in-prometheus.jpg" alt="Annotation Based Scraping in Prometheus" class="wp-image-9656"/></figure>



<p>Next, we&#8217;ll create a dashboard. You can create a dashboard from scratch or simply add a new widget to any of your custom dashboards.</p>



<p>Add a custom widget using the &#8220;Add Widget button&#8221;. The Integration Widget can be used to collect data from Prometheus.&nbsp;</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="2299" height="1103" src="https://middleware.io/backend/wp-content/uploads/2025/03/collect-data-metrics-from-Prometheus.jpg" alt="collect data metrics from Prometheus" class="wp-image-9657"/></figure>



<p>&nbsp;Next, we&#8217;ll need to mention the details of our widget.&nbsp;</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="2320" height="1113" src="https://middleware.io/backend/wp-content/uploads/2025/03/update-widget-for-prometheus-integration.jpg" alt="update widget for prometheus integration" class="wp-image-9661"/></figure>



<p>&nbsp;Once you click &#8220;Save&#8221;, you should see the data in the widget.</p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="2322" height="1048" src="https://middleware.io/backend/wp-content/uploads/2025/03/prometheus-metrics-visibility.jpg" alt="prometheus metrics visibility" class="wp-image-9660"/></figure>



<p>Your metrics from Prometheus will be automatically discovered and rendered here on your Middleware dashboard.&nbsp;</p>



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