K3s Pods are being evicted unexpectedly.

Pods are evicted due to resource constraints or node pressure.

Understanding K3s and Its Purpose

K3s is a lightweight Kubernetes distribution designed for resource-constrained environments and edge computing. It provides a simplified and efficient way to deploy Kubernetes clusters with minimal overhead. K3s is particularly popular for IoT and CI/CD pipelines due to its ease of use and reduced resource requirements.

Identifying the Symptom: Evicted Pods

One common issue users encounter in K3s is the eviction of pods. This symptom is observed when pods are unexpectedly terminated and rescheduled, often accompanied by messages indicating resource constraints or node pressure. This can disrupt application availability and performance.

Exploring the Root Cause: Resource Constraints

Pod eviction in K3s typically occurs due to insufficient resources on a node. This can be caused by high CPU or memory usage, disk pressure, or other resource limitations. When a node is unable to meet the resource demands of its pods, Kubernetes may evict some pods to maintain overall cluster stability.

Common Causes of Resource Constraints

  • Overcommitted CPU or memory resources.
  • Insufficient disk space or I/O pressure.
  • Misconfigured resource requests and limits for pods.

Steps to Resolve Pod Evictions

To address pod eviction issues in K3s, follow these actionable steps:

Step 1: Monitor Node Resources

Use the following command to check the resource usage on your nodes:

kubectl top nodes

This command provides an overview of CPU and memory usage, helping you identify nodes under pressure.

Step 2: Adjust Pod Resource Requests and Limits

Ensure that your pods have appropriate resource requests and limits defined. This helps Kubernetes make informed scheduling decisions. Update your pod specifications as follows:

resources:
requests:
memory: "64Mi"
cpu: "250m"
limits:
memory: "128Mi"
cpu: "500m"

Learn more about setting resource requests and limits in the Kubernetes documentation.

Step 3: Scale Your Cluster

If resource constraints persist, consider adding more nodes to your cluster. This can be done by deploying additional K3s agents or servers. Refer to the K3s documentation for guidance on scaling your cluster.

Step 4: Optimize Node Configuration

Review and optimize your node configuration to ensure efficient resource utilization. This may involve tuning kernel parameters or adjusting node-level resource allocations.

Conclusion

By understanding the causes of pod eviction and implementing these resolution steps, you can maintain a stable and efficient K3s environment. Regularly monitoring resource usage and adjusting configurations as needed will help prevent future eviction issues.

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