Kubernetes Dashboard CPU Usage

Kubernetes has become the de facto standard for container orchestration, allowing developers and operators to manage and scale containerized applications efficiently. The Kubernetes Dashboard is a web-based user interface that provides a visual overview of the Kubernetes cluster. One of the crucial aspects that users often monitor through the dashboard is CPU usage. Understanding CPU usage in the Kubernetes Dashboard helps in optimizing resource allocation, detecting performance bottlenecks, and ensuring the smooth operation of applications running in the cluster.

Table of Contents

  1. Core Concepts
  2. Typical Usage Example
  3. Common Practices
  4. Best Practices
  5. Conclusion
  6. References

Core Concepts

CPU Resources in Kubernetes

In Kubernetes, CPU resources are defined as a quantity of compute units. Each unit is equivalent to one virtual CPU core, and fractional values are also supported. For example, 0.5 CPU represents half of a virtual CPU core. Pods can request and limit CPU resources. A request is the amount of CPU that the scheduler guarantees to the pod, while a limit is the maximum amount of CPU that the pod can use.

Metrics in the Kubernetes Dashboard

The Kubernetes Dashboard displays CPU usage metrics for various resources such as nodes, pods, and containers. These metrics are collected by the Kubernetes Metrics Server, which aggregates resource usage data from the kubelet running on each node. The dashboard presents the CPU usage as a percentage of the total available CPU resources.

CPU Throttling

When a pod exceeds its CPU limit, Kubernetes may throttle the pod’s CPU usage. Throttling means that the pod’s CPU time is restricted, which can lead to performance degradation. Monitoring CPU usage in the dashboard helps in identifying pods that are being throttled.

Typical Usage Example

Step 1: Access the Kubernetes Dashboard

First, you need to access the Kubernetes Dashboard. You can do this by running the following command to start a proxy:

kubectl proxy

Then, open your web browser and navigate to http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/.

Step 2: Navigate to the Pods Section

Once you are in the dashboard, click on the “Pods” option in the left sidebar. This will display a list of all the pods running in the cluster.

Step 3: View CPU Usage

Select a pod from the list, and you will see detailed information about the pod, including its CPU usage. The dashboard will show the current CPU usage as a percentage and may also provide a historical graph of CPU usage over time.

Step 4: Analyze CPU Usage

If you notice that a pod is using a high percentage of CPU resources, you can further investigate the cause. You can check the container logs, review the application code, or adjust the pod’s CPU requests and limits.

Common Practices

Monitoring Node CPU Usage

Monitoring the CPU usage of nodes is essential to ensure that the cluster has enough resources to run all the pods. If a node’s CPU usage is consistently high, it may be a sign that the node is overloaded, and you may need to add more nodes to the cluster or adjust the resource requests of the pods running on that node.

Monitoring Pod CPU Usage

Monitoring the CPU usage of individual pods helps in identifying resource-intensive pods. You can use this information to optimize the resource allocation of pods. For example, if a pod is using significantly less CPU than its requested amount, you can reduce the request to free up resources for other pods.

Setting CPU Requests and Limits

When deploying pods, it is a good practice to set appropriate CPU requests and limits. A proper request ensures that the pod gets enough resources to run, while a limit prevents the pod from consuming excessive resources and causing performance issues for other pods.

Best Practices

Use Horizontal Pod Autoscaling (HPA)

Horizontal Pod Autoscaling (HPA) is a Kubernetes feature that automatically adjusts the number of pod replicas based on the CPU utilization of the pods. By using HPA, you can ensure that your application has enough resources to handle the incoming traffic without overprovisioning resources.

Regularly Review and Adjust Resource Requests and Limits

As your application evolves, its resource requirements may change. Regularly reviewing and adjusting the CPU requests and limits of your pods helps in optimizing resource utilization and improving the performance of your application.

Use Prometheus and Grafana for Advanced Monitoring

While the Kubernetes Dashboard provides basic CPU usage monitoring, for more advanced monitoring and analysis, you can use Prometheus and Grafana. Prometheus is a powerful monitoring and alerting toolkit, and Grafana is a visualization tool that can be used to create detailed dashboards for CPU usage and other metrics.

Conclusion

Monitoring CPU usage in the Kubernetes Dashboard is a crucial aspect of managing a Kubernetes cluster. By understanding the core concepts, following typical usage examples, and implementing common and best practices, you can optimize resource allocation, detect performance bottlenecks, and ensure the smooth operation of your applications. Regular monitoring and analysis of CPU usage help in making informed decisions about resource management and scaling your applications.

References