Configure Kubernetes resource limits, probes, selectors, and RBAC correctly.
npx skills add https://github.com/openocta/openocta --skill kubernetes-openocta
Please help me install this Agent Skill. Skill: Kubernetes Source: https://github.com/openocta/openocta/tree/main/src/embed/skills/k8s Command: npx skills add https://github.com/openocta/openocta --skill kubernetes-openocta
This Skill helps users avoid common and costly mistakes in Kubernetes deployments, focusing on resource management, probe configuration, selector mismatches, and RBAC pitfalls.
requests and limits for CPU and memory to prevent OOMKilled or throttling.readinessProbe, livenessProbe, and startupProbe to ensure application availability and stability.ServiceAccount, Role, and RoleBinding.Use the Kubernetes skill to explain the difference between requests and limits for resource management.
High-intent search queries and answers about installing and using this skill.
Prevent Kubernetes pods from getting OOMKilled or CPU throttled by correctly configuring resource `requests` and `limits` for CPU and memory. This ensures stable scheduling and avoids unexpected container terminations during peak workload loads.
In Kubernetes, a `readinessProbe` determines if a pod is ready to receive network traffic, while a `livenessProbe` checks if the application is running and restarts the container upon failure. Properly configuring both ensures high application availability.
A Kubernetes Service has no available endpoints when its label selector fails to match the target pod labels. Ensuring exact matching between Service selectors and Pod labels guarantees network connectivity and proper traffic routing to your workload.
To configure RBAC for least privilege in Kubernetes, correctly define `ServiceAccount`, `Role`, and `RoleBinding` objects. This grants only the specific permissions required by your application, ensuring secure access control within the cluster.
Yes, setting resource `requests` and `limits` for every Kubernetes deployment is a best practice to prevent resource starvation. Without these boundaries, your applications risk unstable scheduling and potential node failure under heavy load.
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