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.
Before we explain the pros and cons and our takes on the best Kubernetes monitoring tools, let’s first know a bit about K8s.
A production-ready open-source platform called Kubernetes was created using best-of-breed suggestions from the community and the collective knowledge of Google in container orchestration. Its purpose is to automate application container deployment, scaling, and management.
Cluster monitoring tools now need to manage more services and server instances because of businesses’ growing popularity of containers and microservices. Even though the infrastructure landscape has changed, operations teams still need to monitor the same KPIs, including CPU, RAM, file system, network, and service endpoint availability. In this article, we’ll look at a few of the available Kubernetes monitoring tools.
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 the Kubernetes monitoring tool.
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.
- 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
- User interface takes time to get used to
- Needs more integrations with security tools
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.
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.
- Initial learning curve
- It is expensive and offers limited plans
Get end-to-end visibility for containerized applications.
3. 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.
Using pre-built dashboards, you can dig into Kubernetes data and metadata. In their Kubernetes setups, teams can use cluster explorer to investigate errors, bottlenecks, and other strange behavior more quickly.
- Application performance monitoring
- Full-Stack Observability
- AIOps capabilities provide faster issue detection, comprehension, and resolution.
- UX/UI can be improved
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.
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.
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.
Get real-time metrics, traces and logs in one place with Middleware’s unified dashboard.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.