Web·iOS·Android 화면을 WCAG 2.2에 맞춰 설계하고 점검합니다. 화면 읽기와 키보드 조작, 레이블, 대비, 조작 대상 크기를 확인합니다.
- 아이콘 버튼에 설명 추가
- 키보드 조작과 모달 초점 점검
- 대비와 조작 대상 크기 확인
Kubernetes 설정 파일 작성과 검토, 장애 원인 조사를 돕습니다. 상태 확인, 권한, 리소스 제한, 자동 확장 설정 예시와 조사 명령을 참고할 수 있습니다.
Kubernetes workload patterns, resource management, RBAC, probes, autoscaling, ConfigMap/Secret handling, and kubectl debugging for production-grade deployments. Use when writing or reviewing Kubernetes manifests, or debugging probes, RBAC, autoscaling, or resource limits.
Kubernetes에서 앱을 실행하는 설정 파일의 작성과 검토, 장애 원인 조사를 돕습니다. Deployment, Service, Ingress, Job 등의 YAML 예시로 상태 확인용 프로브, CPU·메모리 할당, RBAC 권한 제어를 정리합니다. ConfigMap과 Secret의 취급, 자동 확장, 노드 중단 시 실행 수를 유지하는 설정도 다룹니다.
운영 환경 설정을 검토하거나 컨테이너의 반복 재시작, 메모리 부족, 시작 대기의 원인을 조사할 때 유용합니다. 로그 확인과 롤백 등의 kubectl 명령, 안전성과 안정성 점검 목록을 이용해 확인할 수 있습니다.
CrashLoopBackOff의 원인을 조사하는 절차를 알려 주세요.”실제 환경을 조사하려면 Kubernetes 클러스터와 kubectl이 필요합니다. Secret의 base64 표현은 암호화가 아닙니다. TLS 예시에는 nginx와 cert-manager 설정이 포함됩니다.
이 소개문은 공개된 SKILL.md를 바탕으로 AI(OpenAI Codex)가 작성했습니다. 정확한 사양은 아래 원문을 확인하세요.
AI가 SKILL.md의 내용만을 근거로 4가지 관점에서 판정했습니다. 스타 수나 인기도는 판정에 넣지 않았습니다.
총점은 각 항목을 A=25점, B=15점, C=5점으로 더한 값입니다. 2026년 10월 19일 기준으로 AI(OpenAI Codex)가 판정했습니다. 참고용이므로 설치 전에 원문도 확인해 주세요.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Production-grade Kubernetes patterns for deploying, managing, and debugging workloads reliably.
Same as When to Activate above. This alias satisfies repo skill-format conventions. Use this skill any time you are writing, reviewing, or debugging Kubernetes YAML and workloads.
This skill provides copy-pasteable, production-grade YAML patterns and kubectl debugging commands organized by task:
Deployment with security context, rolling update strategy, all three probe types, resource limits, and environment injection from ConfigMap/Secret.failureThreshold × periodSeconds math.envFrom, file-mount, and external secrets guidance.restartPolicy.See the sections below for complete, runnable examples. Quick references:
| Task | Jump to |
|---|---|
| Full production Deployment YAML | Core Workload Patterns |
| Probe configuration | Probes |
| RBAC least-privilege setup | RBAC |
| Debug a CrashLoopBackOff | kubectl Debugging Cheatsheet |
| Autoscaling | HPA |
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app
namespace: my-namespace
labels:
app: my-app
version: "1.0.0"
spec:
replicas: 3
selector:
matchLabels:
app: my-app
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1 # Allow 1 extra pod during update
maxUnavailable: 0 # Never reduce below desired count
template:
metadata:
labels:
app: my-app
version: "1.0.0"
spec:
# Security context at pod level
securityContext:
runAsNonRoot: true
runAsUser: 1001
fsGroup: 1001
# Graceful shutdown
terminationGracePeriodSeconds: 30
containers:
- name: my-app
image: ghcr.io/org/my-app:1.0.0 # Never use :latest
imagePullPolicy: IfNotPresent
ports:
- containerPort: 8080
protocol: TCP
# Resource requests AND limits are both required
resources:
requests:
cpu: "100m"
memory: "128Mi"
limits:
cpu: "500m"
memory: "256Mi"
# Container security context
securityContext:
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
capabilities:
drop:
- ALL
# Probes (see Probes section below)
startupProbe:
httpGet:
path: /health
port: 8080
failureThreshold: 30
periodSeconds: 5
livenessProbe:
httpGet:
path: /health
port: 8080
initialDelaySeconds: 0
periodSeconds: 30
failureThreshold: 3
readinessProbe:
httpGet:
path: /ready
port: 8080
initialDelaySeconds: 5
periodSeconds: 10
failureThreshold: 2
# Environment from ConfigMap and Secret
envFrom:
- configMapRef:
name: my-app-config
env:
- name: DB_PASSWORD
valueFrom:
secretKeyRef:
name: my-app-secrets
key: db-password
# Writable tmp directory when readOnlyRootFilesystem: true
volumeMounts:
- name: tmp
mountPath: /tmp
volumes:
- name: tmp
emptyDir: {}
Understanding when to use each probe is critical:
| Probe | Failure Action | Use For |
|---|---|---|
startupProbe | Kills container if slow to start | Slow-starting apps (JVM, Python) |
livenessProbe | Restarts container | Deadlock / hung process detection |
readinessProbe | Removes from Service endpoints | Temporary unavailability (DB reconnect) |
# Correct pattern: startupProbe covers slow startup,
# then liveness/readiness take over
startupProbe:
httpGet:
path: /health
port: 8080
failureThreshold: 30 # 30 * 5s = 150s max startup time
periodSeconds: 5
livenessProbe:
httpGet:
path: /health
port: 8080
periodSeconds: 30
failureThreshold: 3 # 3 * 30s = 90s before restart
readinessProbe:
httpGet:
path: /ready # Separate endpoint: checks DB, cache, etc.
port: 8080
periodSeconds: 10
failureThreshold: 2
# WRONG: initialDelaySeconds without startupProbe
# If the app takes 60s to start, set a startupProbe instead
livenessProbe:
httpGet:
path: /health
port: 8080
initialDelaySeconds: 60 # BAD: Arbitrary wait, race condition
# ClusterIP (default) — internal-only
apiVersion: v1
kind: Service
metadata:
name: my-app
namespace: my-namespace
spec:
selector:
app: my-app
ports:
- port: 80
targetPort: 8080
protocol: TCP
type: ClusterIP
# LoadBalancer — external traffic (cloud providers)
spec:
type: LoadBalancer
ports:
- port: 443
targetPort: 8080
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: my-app
namespace: my-namespace
annotations:
nginx.ingress.kubernetes.io/ssl-redirect: "true"
cert-manager.io/cluster-issuer: "letsencrypt-prod"
spec:
ingressClassName: nginx
tls:
- hosts:
- myapp.example.com
secretName: my-app-tls
rules:
- host: myapp.example.com
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: my-app
port:
number: 80
apiVersion: v1
kind: ConfigMap
metadata:
name: my-app-config
namespace: my-namespace
data:
LOG_LEVEL: "info"
APP_ENV: "production"
MAX_CONNECTIONS: "100"
# Mount as a file for complex config
app.yaml: |
server:
port: 8080
timeout: 30s
# Mount ConfigMap as a file
volumes:
- name: config
configMap:
name: my-app-config
items:
- key: app.yaml
path: app.yaml
volumeMounts:
- name: config
mountPath: /etc/app
readOnly: true
# Create secret from literal (CLI, then store in Vault/SOPS)
kubectl create secret generic my-app-secrets \
--from-literal=db-password='s3cr3t' \
--namespace=my-namespace \
--dry-run=client -o yaml | kubectl apply -f -
apiVersion: v1
kind: Secret
metadata:
name: my-app-secrets
namespace: my-namespace
type: Opaque
# Values are base64-encoded (NOT encrypted — use Sealed Secrets or ESO for real encryption)
data:
db-password: czNjcjN0 # base64 of 's3cr3t'
Important: Raw Kubernetes Secrets are only base64-encoded, not encrypted at rest unless your cluster has encryption configured. Use Sealed Secrets or External Secrets Operator for production.
resources:
requests: # Scheduler uses this to place the pod
cpu: "100m" # 100 millicores = 0.1 CPU
memory: "128Mi"
limits: # Container is killed/throttled above this
cpu: "500m"
memory: "256Mi"
Rules of thumb:
| Workload Type | CPU Request | Memory Request | Notes |
|---|---|---|---|
| Web API | 100–250m | 128–256Mi | Set limits 2-4x requests |
| Worker/consumer | 250–500m | 256–512Mi | Memory limit = request for predictability |
| JVM app | 500m–1 | 512Mi–2Gi | Allow headroom above -Xmx for JVM overhead |
| Sidecar | 10–50m | 32–64Mi | Keep minimal |
# WRONG: No requests or limits — unpredictable scheduling, OOM evictions
containers:
- name: app
image: myapp:latest
# Missing resources: {} — this is dangerous in production
# WRONG: Limits without requests — requests default to limits, over-reserves capacity
resources:
limits:
cpu: "2"
memory: "1Gi"
# requests missing — will default to limits values
Two patterns depending on whether the app calls the Kubernetes API:
Disable token automounting on the ServiceAccount. The Role/RoleBinding are not needed.
# ServiceAccount with token disabled — safest default
apiVersion: v1
kind: ServiceAccount
metadata:
name: my-app-sa
namespace: my-namespace
automountServiceAccountToken: false # No K8s API token injected into pods
# Reference in Deployment — no token, no API access
spec:
template:
spec:
serviceAccountName: my-app-sa
automountServiceAccountToken: false # Belt-and-suspenders: also set at pod level
Enable the token and grant only the permissions actually required.
# 1. ServiceAccount — enable token for this SA
apiVersion: v1
kind: ServiceAccount
metadata:
name: my-app-sa
namespace: my-namespace
automountServiceAccountToken: true # Token required: app calls K8s API
# 2. Role — grant only what the app needs (namespace-scoped)
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: my-app-role
namespace: my-namespace
rules:
- apiGroups: [""]
resources: ["configmaps"]
verbs: ["get", "list", "watch"] # Read-only, specific resource
- apiGroups: [""]
resources: ["secrets"]
resourceNames: ["my-app-secrets"] # Restrict to specific secret by name
verbs: ["get"]
# 3. Bind Role to ServiceAccount
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: my-app-rolebinding
namespace: my-namespace
subjects:
- kind: ServiceAccount
name: my-app-sa
namespace: my-namespace
roleRef:
kind: Role
apiGroup: rbac.authorization.k8s.io
name: my-app-role
# 4. Reference SA in Deployment
spec:
template:
spec:
serviceAccountName: my-app-sa
# automountServiceAccountToken defaults to true from SA — token is injected
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: my-app-hpa
namespace: my-namespace
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app
minReplicas: 2 # Always at least 2 for HA
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70 # Scale up when avg CPU > 70%
- type: Resource
resource:
name: memory
target:
type: Utilization
averageUtilization: 80
HPA requires
resources.requeststo be set on all containers — it calculates utilization ascurrent / request.
Prevent too many pods going down during node drains or rolling updates:
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
name: my-app-pdb
namespace: my-namespace
spec:
minAvailable: 2 # OR use maxUnavailable: 1
selector:
matchLabels:
app: my-app
# Create namespace with resource quotas
kubectl create namespace my-namespace
# Apply ResourceQuota to limit namespace consumption
kubectl apply -f - <<EOF
apiVersion: v1
kind: ResourceQuota
metadata:
name: my-namespace-quota
namespace: my-namespace
spec:
hard:
requests.cpu: "4"
requests.memory: 4Gi
limits.cpu: "8"
limits.memory: 8Gi
pods: "20"
EOF
# One-off Job (DB migration, data processing)
apiVersion: batch/v1
kind: Job
metadata:
name: db-migrate
namespace: my-namespace
spec:
backoffLimit: 3 # Retry up to 3 times on failure
ttlSecondsAfterFinished: 3600 # Auto-delete after 1h
template:
spec:
restartPolicy: OnFailure # Never for Jobs (not Always)
containers:
- name: migrate
image: ghcr.io/org/my-app:1.0.0
command: ["python", "manage.py", "migrate"]
resources:
requests:
cpu: "100m"
memory: "256Mi"
# CronJob
apiVersion: batch/v1
kind: CronJob
metadata:
name: cleanup-job
namespace: my-namespace
spec:
schedule: "0 2 * * *" # 2am daily
concurrencyPolicy: Forbid # Don't run if previous still running
successfulJobsHistoryLimit: 3
failedJobsHistoryLimit: 1
jobTemplate:
spec:
template:
spec:
restartPolicy: OnFailure
containers:
- name: cleanup
image: ghcr.io/org/cleanup:1.0.0
resources:
requests:
cpu: "50m"
memory: "64Mi"
# --- Pod status and logs ---
kubectl get pods -n my-namespace
kubectl get pods -n my-namespace -o wide # Show node assignment
kubectl describe pod <pod-name> -n my-namespace # Events and state details
kubectl logs <pod-name> -n my-namespace # Current logs
kubectl logs <pod-name> -n my-namespace --previous # Logs from crashed container
kubectl logs <pod-name> -n my-namespace -c <container> # Multi-container pod
# --- Execute into a running container ---
kubectl exec -it <pod-name> -n my-namespace -- sh
kubectl exec -it <pod-name> -n my-namespace -- bash
# --- Check resource usage ---
kubectl top pods -n my-namespace
kubectl top nodes
# --- Deployment operations ---
kubectl rollout status deployment/my-app -n my-namespace
kubectl rollout history deployment/my-app -n my-namespace
kubectl rollout undo deployment/my-app -n my-namespace # Rollback
kubectl rollout undo deployment/my-app --to-revision=2 -n my-namespace
# --- Scale manually ---
kubectl scale deployment my-app --replicas=5 -n my-namespace
# --- Inspect events (cluster-wide issues) ---
kubectl get events -n my-namespace --sort-by='.lastTimestamp'
# --- Port-forward for local debugging ---
kubectl port-forward pod/<pod-name> 8080:8080 -n my-namespace
kubectl port-forward svc/my-app 8080:80 -n my-namespace
# --- Dry-run to validate YAML ---
kubectl apply -f deployment.yaml --dry-run=client
kubectl apply -f deployment.yaml --dry-run=server # Validates against live cluster
# CrashLoopBackOff: container keeps crashing
kubectl logs <pod-name> --previous -n my-namespace # Check crash logs
kubectl describe pod <pod-name> -n my-namespace # Check exit code & OOMKilled
# ImagePullBackOff: can't pull image
kubectl describe pod <pod-name> -n my-namespace # Check Events section
# Causes: wrong image tag, missing imagePullSecret, private registry
# Pending pod: not scheduled
kubectl describe pod <pod-name> -n my-namespace
# Causes: insufficient resources, no matching node selector, taint/toleration mismatch
# OOMKilled: out of memory
# Increase memory limits, check for memory leaks
kubectl describe pod <pod-name> -n my-namespace | grep -A5 "Last State"
# BAD: Using :latest tag — non-deterministic deployments
image: myapp:latest
# GOOD: Pin to a specific immutable tag (SHA or semver)
image: ghcr.io/org/myapp:1.4.2
# or
image: ghcr.io/org/myapp@sha256:abc123...
# ---
# BAD: Running as root
securityContext: {} # Defaults to root
# GOOD: Non-root with explicit UID
securityContext:
runAsNonRoot: true
runAsUser: 1001
# ---
# BAD: No resource limits — one pod can starve the entire node
containers:
- name: app
image: myapp:1.0.0
# No resources defined
# GOOD: Always set requests and limits
resources:
requests:
cpu: "100m"
memory: "128Mi"
limits:
cpu: "500m"
memory: "256Mi"
# ---
# BAD: Storing plaintext secrets in ConfigMaps
apiVersion: v1
kind: ConfigMap
data:
DB_PASSWORD: "mysecretpassword" # NEVER — use Secret or external secrets manager
# ---
# BAD: ClusterAdmin for application service accounts
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
roleRef:
kind: ClusterRole
name: cluster-admin # Grants god-mode to your app
# ---
# BAD: minAvailable: 0 in PDB — defeats the purpose
spec:
minAvailable: 0
# ---
# BAD: restartPolicy: Always in a Job (causes infinite restart loop)
spec:
restartPolicy: Always # Use OnFailure or Never for Jobs
runAsNonRoot: true, runAsUser set)readOnlyRootFilesystem: true with emptyDir for writable pathsallowPrivilegeEscalation: falsecapabilities.drop: [ALL])defaultautomountServiceAccountToken: false unless neededRole, not ClusterRole unless needed)minReplicas: 2+ for any production workloadRollingUpdate strategy with maxUnavailable: 0/health (liveness) and /ready (readiness) endpointsapp, version, environmentdocker-patterns — Multi-stage Dockerfiles and image securitydeployment-patterns — CI/CD pipelines, rollback strategy, health check endpointssecurity-review — Broader security hardening contextgit-workflow — GitOps integration with K8s (ArgoCD / Flux patterns)아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Web·iOS·Android 화면을 WCAG 2.2에 맞춰 설계하고 점검합니다. 화면 읽기와 키보드 조작, 레이블, 대비, 조작 대상 크기를 확인합니다.
인공지능 에이전트의 문제를 지시, 기억, 도구 실행, 화면 표시 등 12개 계층에서 조사합니다. 코드와 로그를 근거로 원인을 정리하고 심각도에 따른 지적 사항과 수정안을 제시합니다.
실제 개발 과제로 여러 코딩 에이전트를 비교합니다. 성공률, 확인 가능한 API 비용, 소요 시간과 반복 실행의 안정성을 측정해 도입 결정과 업데이트 후 평가에 활용합니다.
AI 에이전트의 도구 구성, 입력과 출력 형식, 오류 복구 절차를 설계합니다. 문맥 정보량을 관리하고 완료율, 재시도 횟수, 성공한 작업당 비용으로 개선을 평가합니다.
오류와 실행 환경을 바탕으로 AI 에이전트가 실패하거나 같은 작업을 반복하는 원인을 조사합니다. 작은 복구 작업을 시험하고 결과와 근거를 인계용 보고서로 정리합니다.
AI 에이전트의 반복 실패와 도구 사용을 기록하고 원인을 좁힙니다. 영향이 제한된 복구 작업과 결과 보고를 통해 근거 있는 재시도를 돕습니다.