Picking up the right Kubernetes Monitoring Tools can be a challenging task. We compiled this list of the best K8 Monitoring Tools (with detailed reviews) to ease your work.

Kubernetes is quickly becoming the standard for container orchestration, allowing developers to quickly and easily deploy and manage applications in a distributed environment. But managing and monitoring K8s can be challenging. 

A Kubernetes cluster appears to be a single computer to a user, but it is actually a set of independent nodes and multiple services that have been connected.

To properly monitor and observe a Kubernetes cluster, you will need to change your monitoring and observability strategies—and the tools you use. Here are some of the most popular and reliable open-source, paid and free Kubernetes monitoring tools you can use.

Table of Contents

Best Kubernetes monitoring tools (Paid)

Kubernetes is a complicated system that needs careful cluster monitoring tools to spot and troubleshoot production-related problems. You can efficiently monitor your Kubernetes deployments in production with the aid of these paid Kubernetes monitoring tool.

1. Middleware

Middleware is a full-stack observability platform that also provides K8s monitoring capabilities. This Kubernetes monitoring tool helps you monitor and identify issues in your container ecosystem in real time.

K8s monitoring tool, Middleware's Dashboard

The tool uses eBPF based kernel agent which is lightweight and easy to install. Middleware also allows you to add multiple dataset in one single dashboard. 

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  • Easy to install, lightweight agent
  • Easy UI
  • Can add multiple datasets in one dashboard. 
  • You can easily transition from correlation to causation by connecting metrics, logs, traces, & network data. 
  • You can spot emerging issues in real time. 
  • Real time reports
  • You do not need to pre-configure your alerts.
  • Automatic microservice discovery
  • Automate the early detection of potential threats that could compromise your Kubernetes clusters.


  • New integrations need to be added. 

2. Sematext

For traditional and microservices architecture based applications running on Kubernetes, Sematext is a real-time monitoring solution that captures metrics and events. This data can then be organized, visualized, and analyzed; alerts can be triggered, etc.

Dashboard of K8 Monitoring tool Semetext


  • Simple to install
  • Auto-discovery identifies services and logs and keeps track of them.
  • Alerting and anomaly spotting built-in
  • Time-saving default monitoring dashboards and alert rules
  • SaaS offering with no infrastructure to maintain
  • Quite comprehensive documentation.
  • Good customer support. 
  • Easy to use UI


  • User interface takes time to get used to
  • Needs more integrations with security tools
  • A bit more expensive compared to its alternatives.
  • Poor user management

3. Datadog

With the help of Datadog’s APM solution, you can instantly retrieve logs, metrics, events, and service statuses from Kubernetes. You can use it to monitor, address issues, and improve application performance.

Datadog Dashboard

Dashboards, high-resolution metrics, and events are available in Datadog for modification and visualization. Slack and PagerDuty are just a few platforms where you can set up alerts and get notifications. Installing the Datadog Agent is simple. A DaemonSet that will be installed on each cluster node can run it.


  • 450+ built-in integrations
  • Real-time interactive dashboards to monitor metrics, traces, logs, and more
  • Monitor important user activities proactively and gather user experience data in one location.
  • Good visualization capabilities
  • Powerful alerts and warning system
  • Good customer support


  • Initial learning curve
  • It is expensive and offers limited plans
  • Doesn’t support JSON parsing on logs
  • Confusing documentation
  • Log Ingestion, Indexing and Retention process is complex
  • No dedicated mobile app for accessing alerts on the go.
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4. New Relic

New Relic Infrastructure’s on-host integration monitors Kubernetes’ container orchestration layer. This Kubernetes monitoring tool gathers metrics that keep track of data and metadata for nodes, Namespaces, Deployments, ReplicaSets, Pods, and containers, allowing you to fully keep track of the hosts and front- and back-end applications running within your Kubernetes clusters.

Kubernetes Monitoring Tool New Relic's Dashboard

Using pre-built dashboards, you can dig into Kubernetes data and metadata. In their Kubernetes setups, teams can use cluster explorer to quickly investigate errors, bottlenecks, and other strange behavior.


  • Application performance monitoring
  • Full-Stack Observability
  • AIOps capabilities provide faster issue detection, comprehension, and resolution.


  • UX/UI can be improved
  • Expensive

5. Dynatrace

For Kubernetes deployments, Dynatrace also offers a full-stack monitoring solution. This cloud monitoring tool allows you to keep tabs on the dependencies and connections between hosts, containers, and cloud instances and the availability and health of apps and processes.

Dynatrace Kubernetes Monitoring dashboard

You can combine and leverage information from over 500 products, including, among others, AWS, Azure, OpenShift, Google Cloud, and Kubernetes. Even better, it reveals the inner workings of Kubernetes’ apps via events, traces, metrics, and behavioral data.


  • Multiple integrations 
  • Ease of adoption


  • The management functions’ user interface could be more intuitive.
  • Takes time to get used to

Best free & open-source Kubernetes monitoring tools

Here are the most well-liked and dependable open-source Kubernetes monitoring tools.

1. Prometheus: Best free K8s monitoring tool

One of the most often used Kubernetes monitoring tools is Prometheus. It is a part of the Cloud Native Computing Foundation and is community-driven. Google Borg Monitor served as the basis for this project, which was first created by SoundCloud and then contributed to the CNCF.

All of the data that Prometheus stores are a time series. The PromQL query language can query this data, and an expression browser is built-in for visualizing it. Grafana is used by Prometheus since it lacks a dashboard and needs to visualize data.

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2. Kubernetes Dashboard

Kubernetes Dashboard is a web-based UI add-on for Kubernetes clusters. It offers a straightforward method for managing, troubleshooting, and monitoring your environment. You can check the status of workloads and view basic data such as memory and CPU use statistics across all of your nodes using the Kubernetes Dashboard. With ready-to-use YAML files, installing the Kubernetes Dashboard is simple. Check this document from Kubernetes if you feel stuck.

3. Grafana

Grafana is an open-source multi-platform tool for Kubernetes monitoring and observation.  It links to every source accessible and helps track data. Dynamic dashboards with a variety of graphs, histograms, Geo maps, and template variables are also supported. In this manner, metrics and logs can be swiftly and creatively visualized.

With the help of the tool’s integrated alert system, you can visually establish alert criteria for crucial parameters. It allows for data-source-specific searches, which aid in defining and identifying a data source for each query. This is accomplished by combining various data sources in a single graph.

4. Jaeger

Jaeger is a free tracing tool used for monitoring and troubleshooting Kubernetes deployments and other complicated distributed systems. In 2016, Uber Technologies made it available and open-source. Users of Jaeger can carry out service dependency analysis, distributed transaction monitoring, distributed context propagations, root cause analysis, performance and latency optimization, and distributed context propagations.

For Java, Node, Python, Go, and C++, as well as several data sources like Cassandra, Elasticsearch, Kafka, and RAM, Jaeger offers OpenTelemetry-based functionality. Learn more about using Jaeger as a distributed tracing system by reading this. You can use a DaemonSet configuration or the Jaeger Operator to deploy Jaeger.

5. The ELK Stack

For logging and monitoring K8s, the ELK Stack is the most widely used open-source monitoring tool. ELK, which stands for Elasticsearch, Logstash, and Kibana, also contains a fourth part called Beats, which are lightweight data shippers. Together, the stack’s components offer a complete and potent logging solution for Kubernetes. Each element in the stack handles a separate stage of the logging process.

Logs can be gathered and processed by Logstash before being sent to be stored. Elasticsearch will function well even when storing and searching through millions of pages because it was built to be scalable. Kibana covers the analysis interface required by users to interpret the data.

Why monitoring Kubernetes is Important

Proactive cluster management is made possible with the aid of Kubernetes monitoring, a type of reporting. Cluster monitoring tools make it easier to manage containerized infrastructure by keeping track of how memory, CPU, and storage are being used. When the required number of pods is not operating, resource usage is about to reach critical levels, or misconfiguration prevents nodes or pods from joining the cluster, cluster operators can monitor and get alerts.

The rapid adoption of containers in enterprise-level enterprises has benefited IT teams, DevSecOps teams, and developers globally in several ways. However, Kubernetes’ flexibility and scalability in the deployment of containerized apps also introduce additional difficulties. Without the right Kubernetes monitoring tools, it’s difficult to monitor the health of apps that have been abstracted by containers and then again by Kubernetes because there is no longer a 1-to-1 correlation between an application and the server it runs on.

1. Reliability and troubleshooting

One of the best ways to foresee issues and identify bottlenecks in a production setting is to continuously monitor an application’s condition. Cluster operators in Kubernetes monitor the cluster and provide alerts when the number of pods is running, resource consumption is getting dangerously close to a critical limit, or a failure or configuration mistake stops a pod or node from joining the cluster. Many businesses employ specific cloud-native K8s monitoring tools to get complete visibility over cluster activity besides this built-in monitoring functionality.

2. Kubernetes performance tuning

Data on the number, condition, and accessibility of different Kubernetes objects, such as pods, are released by the Kubernetes API server. Internal Kubernetes processes and components use this data to monitor whether pods are launched, maintained, and correctly scheduled for new pods. You may get a high-level overview of your cluster’s state using these cluster state metrics. They can reveal problems with nodes or pods, alerting you to the likelihood that you need to scale back your cluster or look into a bottleneck.

3. Cost management 

You can identify what services cost your company the most by checking that resources in your Kubernetes cluster are properly tagged using labels or namespaces. Monitoring is frequently the best place to start when figuring out the return on investment of various cost-cutting measures.

Setting up an overall framework is highly advised. You must make sure that you are informed if anything unusual occurs. For instance, you’ll want to be informed if a product or service unexpectedly increases in price so that you may investigate the cause and implement changes.

4. Security

By actively monitoring clusters, containers, and namespace resource allocation, Kubernetes monitoring can assist you in enhancing security. You can monitor a variety of KPIs to maintain Kubernetes security. Kubernetes monitoring tools like Prometheus may monitor some Kubernetes metrics you can use for security. To ensure you don’t miss any security threats, tools like Grafana present metrics on many dashboards.

What should you be monitoring in Kubernetes 

You can monitor a variety of KPIs to maintain Kubernetes security. They are typically broken down into three primary categories: resource monitoring, services monitoring, and infrastructure monitoring.

1. Infrastructure performance

You must monitor the metrics below to determine how well your Kubernetes infrastructure performs.

CPU usage-You may gain valuable insight into cluster performance by monitoring the amount of CPU your pods are using with regards to their configured requests and limitations, as well as CPU utilization at the node level. A lack of available CPU at the node level can cause the node to restrict the amount of CPU allotted to each pod, much as a pod exceeding its CPU limits.

Kubernetes Resource Metrics View - Datadog

Disk usage– Disk space is a non-compressible resource, just like RAM; hence scheduling issues with pods may arise if a kubelet detects low disc space on its root volume. A node will be marked as being under disc pressure if its remaining disc capacity exceeds a predetermined resource threshold. You should monitor the amounts of volume usage used by your pods besides node-level disc utilization. You can avoid issues at the application or service level by doing this.

Pod resources– Resource requests and limits, along with resource consumption, will provide you with a more detailed analysis of your cluster’s ability to handle existing workloads and accept new ones. It’s critical to monitor resource utilization throughout your cluster, especially for your nodes and the pods they support.

2. Services

The best KPIs for identifying microservice concerns quickly are those related to APIs, like request rate, call error, and latency. These matrices make it easy to find degradations in a microservice component.

Automatic detection of REST API request irregularities makes it simple to find service-level metrics. These metrics provide uniform visibility across the clusters by measuring each Kubernetes service in the same way.

3. Resources

To evaluate whether the cluster is underutilized or at capacity, monitor how the infrastructure and resources are used. It is crucial to keep track of node health and availability to determine whether there are enough resources and nodes accessible to replicate applications. Finally, monitor resource or chargeback utilization for each project or team.

How to choose the right k8s monitoring tool

Given all the options at your disposal, how can you choose the best tool for your organization? Your organization’s needs will ultimately determine your choice, as was already indicated. It’s crucial to consider both your existing environments and the future state of your Kubernetes while making these choices. To maintain efficient operations and get the most out of your monitoring and analytics, you must select a K8 monitoring strategy that will scale as your business expands.

Recommended Read: Top 5 Kubernetes challenges & their solutions

For your Kubernetes monitoring requirements, you have a wide range of alternatives and technologies at your disposal, all of which have robust capabilities, whether you opt for an à la carte or a platform approach. The most crucial thing is to strive for comprehensive visibility into your systems and application. By doing this, you can maximize the potential of Kubernetes and position IT for long-term success.

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FAQs about K8s monitoring tools

Which monitoring tool is best for Kubernetes?

There are many tools for monitoring Kubernetes; based on our research and considering a few unbiased reviews, Middleware, Datadog, and Prometheus are the best tools for monitoring Kubernetes.

How can I monitor Kubernetes performance?

You can monitor Kubernetes performance by examining the containers, pods, their services, and other characteristics of the clusters. You can also use a monitoring tool like Middleware.

How can you monitor your Kubernetes infrastructure?

The easiest and most straightforward way to monitor your Kubernetes infrastructure is using a K8s monitoring tool like Middleware. Other options include using Heapster to collect metrics, InfluxDB to store it (in a time series database), and Grafana to visually present and aggregate the data.