agentleFS
uprinteruprinter/ai-agents-team/.claude/skills/k8s-debug/SKILL.md

k8s-debug

Skill1 starsChanged 22 days agoMITView on GitHub

Diagnose and fix Kubernetes pods, CrashLoopBackOff, Pending, DNS, networking, storage, and rollout failures with kubectl.

3 other projects use a version of this, 1 of them edited.

Adopted by

Most recently taken up by

The file

Show its rules and text

We split this skill into the rules it gives an agent

13 rules. 0 are common, 8 are distinctive, and 5 are very specific to this project.

  • 0

    Common

    Most of the 3 edited versions we read keep these.

  • 8

    Distinctive

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when requests resemble:

    line 14
  2. Very specific:

    Run from the skill directory (devops-skills-plugin/skills/k8s-debug) so relative script paths work as written.

    line 24
  3. Distinctive:

    Read access to namespaces, pods, events, services, and nodes.

    line 29
  4. Distinctive:

    If optional tools are missing, scripts continue and print warnings with reduced output.

    line 46
  5. Very specific:

    If kubectl top is unavailable, continue with kubectl describe and events.

    line 47
  6. Distinctive:

    Use this skill for:

    line 51
  7. Distinctive:

    Default mode is read-only diagnosis first.

    line 63
  8. Distinctive:

    Follow this systematic approach for any Kubernetes issue:

    line 112
  9. Distinctive:

    If preflight fails, stop and fix access/context first.

    line 122
  10. Distinctive:

    Use the appropriate diagnostic script based on scope:

    line 137
  11. Very specific:

    Use ./scripts/pod_diagnostics.py for comprehensive pod analysis:

    line 140
  12. Very specific:

    Use ./scripts/cluster_health.sh for overall cluster diagnostics:

    line 161
  13. Very specific:

    Use ./scripts/network_debug.sh for connectivity issues:

    line 179

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Kubernetes Debugging Skill

Overview

Systematic toolkit for debugging Kubernetes clusters, workloads, networking, and storage with a deterministic, safety-first workflow.

Trigger Phrases

Use this skill when requests resemble:

  • "My pod is in CrashLoopBackOff; help me find the root cause."
  • "Service DNS works in one pod but not another."
  • "Deployment rollout is stuck."
  • "Pods are Pending and not scheduling."
  • "Cluster health looks degraded after a change."
  • "PVC is pending and pods cannot mount storage."

Prerequisites

Run from the skill directory (devops-skills-plugin/skills/k8s-debug) so relative script paths work as written.

Required

  • kubectl installed and configured.
  • An active cluster context.
  • Read access to namespaces, pods, events, services, and nodes.

Quick preflight:

kubectl config current-context
kubectl auth can-i get pods -A
kubectl auth can-i get events -A
kubectl get ns

Optional but Recommended

  • jq for more precise filtering in ./scripts/cluster_health.sh.
  • Metrics API (metrics-server) for kubectl top.
  • In-container debug tools (nslookup, getent, curl, wget, ip) for deep network tests.

Fallback behavior:

  • If optional tools are missing, scripts continue and print warnings with reduced output.
  • If kubectl top is unavailable, continue with kubectl describe and events.

When to Use This Skill

Use this skill for:

  • Pod failures (CrashLoopBackOff, ImagePullBackOff, Pending, OOMKilled)
  • Service connectivity or DNS resolution issues
  • Network policy or ingress problems
  • Volume and storage mount failures
  • Deployment rollout issues
  • Cluster health or performance degradation
  • Resource exhaustion (CPU/memory)
  • Configuration problems (ConfigMaps, Secrets, RBAC)

Safety Rules for Disruptive Commands

Default mode is read-only diagnosis first. Only execute disruptive commands after confirming blast radius and rollback.

Commands requiring explicit confirmation:

  • kubectl delete pod ... --force --grace-period=0
  • kubectl drain ...
  • kubectl rollout restart ...
  • kubectl rollout undo ...
  • kubectl debug ... --copy-to=...

Before disruptive actions:

# Snapshot current state for rollback and incident notes
kubectl get deploy,rs,pod,svc -n <namespace> -o wide
kubectl get pod <pod-name> -n <namespace> -o yaml > before-<pod-name>.yaml
kubectl get events -n <namespace> --sort-by='.lastTimestamp' > before-events.txt

Reference Navigation Map

Load only the section needed for the observed symptom.

Symptom / NeedOpenStart section
You need an end-to-end diagnosis path./references/troubleshooting_workflow.mdGeneral Debugging Workflow
Pod state is Pending, CrashLoopBackOff, or ImagePullBackOff./references/troubleshooting_workflow.mdPod Lifecycle Troubleshooting
Service reachability or DNS failure./references/troubleshooting_workflow.mdNetwork Troubleshooting Workflow
Node pressure or performance regression./references/troubleshooting_workflow.mdResource and Performance Workflow
PVC / PV / storage class issues./references/troubleshooting_workflow.mdStorage Troubleshooting Workflow
Quick symptom-to-fix lookup./references/common_issues.mdmatching issue heading
Post-mortem fix options for known issues./references/common_issues.mdSolutions sections

Scripts Overview

ScriptPurposeRequired argsOptional argsOutputFallback behavior
./scripts/cluster_health.shCluster-wide health snapshot (nodes, workloads, events, common failure states)None--strict, K8S_REQUEST_TIMEOUT env varSectioned report to stdoutContinues on check failures, tracks them in summary and exit code
./scripts/network_debug.shPod-centric network and DNS diagnostics<pod-name> (<namespace> defaults to default)--strict, --insecure, K8S_REQUEST_TIMEOUT env varSectioned report to stdoutUses secure API probe by default; insecure TLS requires explicit --insecure
./scripts/pod_diagnostics.pyDeep pod diagnostics (status, describe, YAML, events, per-container logs, node context)<pod-name>-n/--namespace, -o/--outputSectioned report to stdout or fileFails fast on missing access; skips optional metrics/log blocks with clear messages

Script Exit Codes

./scripts/cluster_health.sh and ./scripts/network_debug.sh share the same contract:

  • 0: checks completed with no check failures (warnings allowed unless --strict is set).
  • 1: one or more checks failed, or warnings occurred in --strict mode.
  • 2: blocked preconditions (for example: missing kubectl, no active context, inaccessible namespace/pod).

Deterministic Debugging Workflow

Follow this systematic approach for any Kubernetes issue:

1. Preflight and Scope

kubectl config current-context
kubectl get ns
kubectl auth can-i get pods -n <namespace>

If preflight fails, stop and fix access/context first.

2. Identify the Problem Layer

Categorize the issue:

  • Application Layer: Application crashes, errors, bugs
  • Pod Layer: Pod not starting, restarting, or pending
  • Service Layer: Network connectivity, DNS issues
  • Node Layer: Node not ready, resource exhaustion
  • Cluster Layer: Control plane issues, API problems
  • Storage Layer: Volume mount failures, PVC issues
  • Configuration Layer: ConfigMap, Secret, RBAC issues

3. Gather Diagnostics with the Right Script

Use the appropriate diagnostic script based on scope:

Pod-Level Diagnostics

Use ./scripts/pod_diagnostics.py for comprehensive pod analysis:

python3 ./scripts/pod_diagnostics.py <pod-name> -n <namespace>

This script gathers:

  • Pod status and description
  • Pod events
  • Container logs (current and previous)
  • Resource usage
  • Node information
  • YAML configuration

Output can be saved for analysis:

python3 ./scripts/pod_diagnostics.py <pod-name> -n <namespace> -o diagnostics.txt

Cluster-Level Health Check

Use ./scripts/cluster_health.sh for overall cluster diagnostics:

./scripts/cluster_health.sh > cluster-health-$(date +%Y%m%d-%H%M%S).txt

This script checks:

  • Cluster info and version
  • Node status and resources
  • Pods across all namespaces
  • Failed/pending pods
  • Recent events
  • Deployments, services, statefulsets, daemonsets
  • PVCs and PVs
  • Component health
  • Common error states (CrashLoopBackOff, ImagePullBackOff)

Network Diagnostics

Use ./scripts/network_debug.sh for connectivity issues:

./scripts/network_debug.sh <namespace> <pod-name>
# or force warning sensitivity / insecure TLS only when explicitly needed:
./scripts/network_debug.sh --strict <namespace> <pod-name>
./scripts/network_debug.sh --insecure <namespace> <pod-name>

This script analyzes:

  • Pod network configuration
  • DNS setup and resolution
  • Service endpoints
  • Network policies
  • Connectivity tests
  • CoreDNS logs

4. Follow Issue-Specific Reference Workflow

Based on the identified issue, consult ./references/troubleshooting_workflow.md:

  • Pod Pending: Resource/scheduling workflow
  • CrashLoopBackOff: Application crash workflow
  • ImagePullBackOff: Image pull workflow
  • Service issues: Network connectivity workflow
  • DNS failures: DNS troubleshooting workflow
  • Resource exhaustion: Performance investigation workflow
  • Storage issues: PVC binding workflow
  • Deployment stuck: Rollout workflow

5. Apply Targeted Fixes

Refer to ./references/common_issues.md for symptom-specific fixes.

6. Verify and Close

Run final verification:

kubectl get pods -n <namespace> -o wide
kubectl get events -n <namespace> --sort-by='.lastTimestamp' | tail -20
kubectl rollout status deployment/<name> -n <namespace>

Issue is done when user-visible behavior is healthy and no new critical warning events appear.

Example Flows

Example 1: CrashLoopBackOff in payments Namespace

python3 ./scripts/pod_diagnostics.py payments-api-7c97f95dfb-q9l7k -n payments -o payments-diagnostics.txt
kubectl logs payments-api-7c97f95dfb-q9l7k -n payments --previous --tail=100
kubectl get deploy payments-api -n payments -o yaml | grep -A 8 livenessProbe

Then open ./references/common_issues.md and apply the CrashLoopBackOff solutions.

Example 2: Service DNS/Connectivity Failure

./scripts/network_debug.sh checkout checkout-api-75f49c9d8f-z6qtm
kubectl get svc checkout-api -n checkout
kubectl get endpoints checkout-api -n checkout
kubectl get networkpolicies -n checkout

Then follow Service Connectivity Workflow in ./references/troubleshooting_workflow.md.

Essential Manual Commands

Pod Debugging

# View pod status
kubectl get pods -n <namespace> -o wide

# Detailed pod information
kubectl describe pod <pod-name> -n <namespace>

# View logs
kubectl logs <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace> --previous  # Previous container
kubectl logs <pod-name> -n <namespace> -c <container>  # Specific container

# Execute commands in pod
kubectl exec <pod-name> -n <namespace> -it -- /bin/sh

# Get pod YAML
kubectl get pod <pod-name> -n <namespace> -o yaml

Service and Network Debugging

# Check services
kubectl get svc -n <namespace>
kubectl describe svc <service-name> -n <namespace>

# Check endpoints
kubectl get endpoints -n <namespace>

# Test DNS
kubectl exec <pod-name> -n <namespace> -- nslookup kubernetes.default

# View events
kubectl get events -n <namespace> --sort-by='.lastTimestamp'

Resource Monitoring

# Node resources
kubectl top nodes
kubectl describe nodes

# Pod resources
kubectl top pods -n <namespace>
kubectl top pod <pod-name> -n <namespace> --containers

Emergency Operations

# Restart deployment
kubectl rollout restart deployment/<name> -n <namespace>

# Rollback deployment
kubectl rollout undo deployment/<name> -n <namespace>

# Force delete stuck pod
kubectl delete pod <pod-name> -n <namespace> --force --grace-period=0

# Drain node (maintenance)
kubectl drain <node-name> --ignore-daemonsets --delete-emptydir-data

# Cordon node (prevent scheduling)
kubectl cordon <node-name>

Completion Criteria

Troubleshooting session is complete when all are true:

  • Cluster context and namespace are confirmed.
  • Relevant diagnostic script output is captured.
  • Root cause is identified and tied to evidence (events/logs/config/state).
  • Any disruptive action was preceded by snapshot and rollback plan.
  • Fix verification commands show healthy state.
  • Reference path used (./references/troubleshooting_workflow.md or ./references/common_issues.md) is documented in notes.

Related Tools

Useful additional tools for Kubernetes debugging:

  • kubectl-debug: Advanced debugging plugin
  • stern: Multi-pod log tailing
  • kubectx/kubens: Context and namespace switching
  • k9s: Terminal UI for Kubernetes
  • lens: Desktop IDE for Kubernetes
  • Prometheus/Grafana: Monitoring and alerting
  • Jaeger/Zipkin: Distributed tracing

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.