Key metrics for Kubernetes performance monitoring: A practical guide
Kubernetes is known to be the best container orchestration tool, but it can also add complexity to resource management, particularly as your clusters expand. Without proper monitoring, problems can rapidly worsen, resulting in subpar application performance, service interruptions, and higher expenses.
In this blog, you will learn the key metrics for monitoring Kubernetes performance and how monitoring these can assist you in maintaining optimal performance in your environment.
By monitoring the right metrics, you can:
- Identify issues before they impact users.
- Enhance resource utilization for improved cost-effectiveness.
- Make sure your apps remain quick and reactive.
- Ensure optimal availability and constant uptime.
So, what are the most important metrics to track?
Key Kubernetes metrics you should monitor
Kubernetes offers a wealth of metrics, but tracking the right ones makes all the difference. Let's break down the key metrics that matter most when it comes to Kubernetes performance monitoring.
1. Node health
Why it's important
Kubernetes clusters depend on nodes to operate your containers. If a node fails, it may impact your applications. Observing node health is essential for maintaining stability and availability.
What to check
- Node CPU and memory usage: Guarantee that no individual node is overloaded with excessive tasks.
- Node accessibility: Ensure that all your nodes are operational, available, active, and in the ready state.
- Node schedulability: Ensure that the nodes are available for application deployment at all times.
- Disk space utilization: Nodes need adequate storage capacity to manage logs, containers, and other essential information.
By monitoring node performance, you can make certain that workloads are allocated effectively and efficiently among functional nodes.
2. Pod status
Why it's important
Kubernetes employs liveness and readiness probes to assess if pods are healthy and prepared to manage traffic. If an issue arises, the system can implement automated corrective measures, but only if the probes are functioning properly. CrashLoopBackOff, OOMKilled, and ImagePullBackOff are also critical indicators to look for.
What to check
- Liveness probe failures: This metric signifies that a pod is not healthy and might require a restart.
- Readiness probe failures: This metric notifies you when a pod is unable to handle traffic, despite being technically operational.
- CrashLoopBackOff: This pinpoints when the container is struggling to start and indicates there is some reason for the failure.
- OOMKilled: This indicates when the containers are killed because the memory allocated is less than the required memory.
- ImagePullBackOff: This pinpoints when the container image is not being pulled off promptly because of inaccurate image tags, the wrong repository, or a repository that requires authentication.
Tracking these failures helps you guarantee that your applications remain accessible and responsive at all times.
3. Pod restarts
Why they're important
Regular pod restarts typically indicate a problem with the application or resource constraints. If pods are repeatedly restarting, it may indicate a more significant issue to resolve.
What to check
- Number of pod restarts: Monitor the number of times pods have rebooted within a specific timeframe.
- Restart frequency: Track the rate at which pods restart to identify trends or persistent problems.
Regular restarts signal the need for more extensive troubleshooting to enhance stability and minimize downtime.
4. CPU utilization
Why it's important
The CPU is a key resource that your workloads rely on. Elevated CPU usage can cause application lag or potentially crashes if the system lacks sufficient processing power to manage requests.
What to check
- CPU consumption (per pod or container): Check the CPU usage for each pod or container. It is also ideal to track the CPU usage at each level:
- CPU usage of clusters: Knowing the overall CPU usage of the clusters is critical to ensuring that autoscaling happens effortlessly.
- CPU usage at the namespace level: Track the CPU usage at each namespace level for better resource allocation and management.
- CPU usage of nodes and pods: Monitor the node- and pod-level CPU consumption to ensure availability.
- CPU usage of the deployments and all the workloads: Ensure that you have allocated enough resources for the proper functioning of your applications.
- CPU requests and limits: Guarantee that pods do not lack CPU resources or become excessively provisioned.
- CPU throttling: This indicates that the processes are getting slowed down because the usage is reaching its resource limits.
By tracking CPU usage, you can avoid bottlenecks and enhance your resource distribution.
5. Memory utilization
Why it's important
Similar to the CPU, memory is crucial in maintaining the health of your Kubernetes workloads. If your applications exhaust their memory, they could crash or face performance problems.
What to check
- Memory consumption (for each pod or container): Monitor the memory utilized by every pod or container. It is also ideal to track the memory usage at each level:
- Memory usage of clusters: Knowing the overall memory usage of the clusters is critical to ensuring that autoscaling happens effortlessly.
- Memory usage at the namespace level: Track the memory usage at each namespace level for better resource allocation and management.
- Memory usage of nodes and pods: Monitor the node- and pod-level memory consumption to ensure availability.
- Memory usage of the deployments and all the workloads: Ensure that you have allocated enough resources for the proper functioning of your applications.
- Memory requests versus limits: Determine whether memory is insufficiently allocated or excessively allocated.
- Memory leaks: Prolonged trends can help you recognize inefficient memory usage or leaks.
By monitoring memory usage, you can prevent your applications from facing memory shortages that affect performance.
6. Network delays and data flow
Why they're important
Kubernetes applications depend significantly on networking, both inside (among pods) and outside (to users). Inefficient network performance may lead to slow reactions, lost connections, or application failures. It is ideal to track the network usage at each level, beginning with the clusters, nodes, pods, and workloads.
What to check
- Network throughput: Monitor the volume of data entering and leaving your clusters.
- Network latency: Elevated latency may suggest problems between containers or outside systems.
- Lost packets and mistakes: When packets are missing, it indicates potential problems within the network.
Tracking network performance helps you guarantee seamless communication among pods and maintain quick response times.
7. Disk I/O and storage utilization
Why they're important
When your application relies on persistent storage (such as databases), disk I/O performance becomes a vital consideration. Slow disk read or write speeds can lead to application lags and negatively impact the user experience.
What to check
- Disk usage: Keep track of the disk space used on your nodes and persistent volumes.
- Disk I/O delay: Measure the time required to read and write data on disks.
- Persistent volume statuses: Make certain that your storage volumes are correctly allocated and functioning at their best.
Monitoring disk performance helps you guarantee that storage-intensive applications, such as databases, maintain their efficiency.
Reasons why Site24x7 is the perfect tool for monitoring Kubernetes
To fully reap the benefits of Kubernetes monitoring, you require a solution that aggregates all these metrics and delivers actionable insights. Site24x7 is designed to assist you with exactly that; featuring real-time monitoring, simple dashboards, and customizable alerts, it's the ideal solution for overseeing Kubernetes performance on a large scale.
Distinguishing attributes of Site24x7
- Real-time metric tracking: Track the CPU usage, memory usage, network performance, disk performance, and pod health of the clusters, namespaces, nodes, pods, deployments, and workloads instantly.
- Personalized dashboards: Display all your Kubernetes metrics in a single location to identify trends easily.
- Alerts and notifications: Receive alerts on critical happenings, such as resource depletion, pod malfunctions, and network problems, enabling you to act promptly.
- AI-powered anomaly detection and IT automation: Get real-time notifications on any deviations from the usual patterns and automate remedial actions before the issues go out of your hands. These features minimize manual intervention and labor.
- Analysis of historical data: Monitor the performance over time to detect possible problems before they escalate.
Site24x7 assists in optimally maintaining your Kubernetes environment, requiring little manual work while providing extensive insights.
Experience smarter, more efficient monitoring with Site24x7 today!
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