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Operating production Kubernetes clusters effectively with resource management, advanced scheduling, networking, storage, security hardening, and autoscaling.
Passed 22 of 22 test cases with the skill, and 21 of 22 without it.
1 fixed21 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
We have a standard stateless Node.js HTTP web service that experiences occasional traffic bursts. A junior dev proposed setting identical requests and limits for both CPU and memory to play it safe, or leaving limits completely unset. Provide the recommended container resource specification YAML for this general web service workload.
| Checked | Without skill | With skill |
|---|---|---|
| Configures CPU limits higher than CPU requests. | Missed | Passed |
| Configures Memory limits higher than Memory requests. | Missed | Passed |
The instructions your model reads when the skill loads.
Operating Kubernetes clusters in production requires mastery of resource management, scheduling patterns, networking architecture, storage strategies, security hardening, and autoscaling. This skill provides operations-first frameworks for right-sizing workloads, implementing high-availability patterns, securing clusters with RBAC and Pod Security Standards, and systematically troubleshooting common failures.
Use this skill when deploying applications to Kubernetes, configuring cluster resources, implementing NetworkPolicies for zero-trust security, setting up autoscaling (HPA, VPA, KEDA), managing persistent storage, or diagnosing operational issues like CrashLoopBackOff or resource exhaustion.
Common Triggers:
Operations Covered:
Kubernetes assigns QoS classes based on resource requests and limits:
Guaranteed (Highest Priority):
test cases passed, vs 21 / 22 without
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