👀 Views: 31 💬 Answers: 1 📅 Created: 2025-06-14

kubernetes jobs resource-management yaml

I'm trying to figure out I've searched everywhere and can't find a clear answer. I'm experiencing an scenario with a Kubernetes Job that doesn't seem to complete successfully. The Job is supposed to run a data processing task but it keeps failing with the behavior message `Back-off restarting failed container` in the pod logs. I have defined the Job with specific resource limits that seem appropriate for the task, but it appears that the Job is running out of memory or CPU. Here is the relevant YAML for the Job: ```yaml apiVersion: batch/v1 kind: Job metadata: name: data-processor spec: template: spec: containers: - name: processor image: my-docker-repo/data-processor:latest resources: limits: memory: "512Mi" cpu: "500m" restartPolicy: Never ``` I've tried increasing the memory limit to `1Gi` and the CPU limit to `1` but that didn't resolve the scenario. The logs indicate that the application receives a `SIGKILL` signal, which suggests it's being terminated by the OOM killer. I also verified that the node has enough resources available, so I suspect it's related to the resource limits of the container itself. To troubleshoot further, I ran `kubectl describe pod data-processor-<pod-id>` and saw that it was indeed hitting the memory limit. What are the best practices to determine appropriate resource requests and limits for a Kubernetes Job in this scenario? Is there a way to monitor the resource usage during the Job execution to help fine-tune these values? Any suggestions or similar experiences would be greatly appreciated! My development environment is macOS. Thanks in advance! The stack includes Yaml and several other technologies.