devops-automation
CI/CD pipeline design with GitHub Actions, Docker, Kubernetes, Helm, and GitOps patterns
Works with
---
name: devops-automation
description: CI/CD pipeline design with GitHub Actions, Docker, Kubernetes, Helm, and GitOps patterns
license: Apache-2.0
---
# DevOps Automation
## GitHub Actions Workflow Structure
```yaml
name: CI/CD
on:
push:
branches: [main]
pull_request:
branches: [main]
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
lint:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: 22
cache: 'npm'
- run: npm ci
- run: npm run lint
test:
runs-on: ubuntu-latest
needs: lint
strategy:
matrix:
node-version: [20, 22]
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: ${{ matrix.node-version }}
cache: 'npm'
- run: npm ci
- run: npm test -- --coverage
- uses: actions/upload-artifact@v4
with:
name: coverage-${{ matrix.node-version }}
path: coverage/
deploy:
runs-on: ubuntu-latest
needs: test
if: github.ref == 'refs/heads/main'
environment: production
steps:
- uses: actions/checkout@v4
- run: ./deploy.sh
```
Key patterns:
- Use `concurrency` to cancel outdated runs
- Cache dependencies with setup action's `cache` option
- Use `needs` for job dependencies
- Gate deploys with `environment` protection rules
- Use matrix for cross-version testing
## Docker Multi-Stage Builds
```dockerfile
FROM node:22-alpine AS deps
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci --production
FROM node:22-alpine AS builder
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci
COPY . .
RUN npm run build
FROM node:22-alpine AS runner
WORKDIR /app
RUN addgroup -g 1001 appgroup && adduser -u 1001 -G appgroup -S appuser
COPY --from=deps /app/node_modules ./node_modules
COPY --from=builder /app/dist ./dist
COPY --from=builder /app/package.json ./
USER appuser
EXPOSE 3000
HEALTHCHECK --interval=30s --timeout=3s CMD wget -qO- http://localhost:3000/health || exit 1
CMD ["node", "dist/server.js"]
```
Rules:
- Use specific image tags, never `latest`
- Run as non-root user
- Copy only necessary files into final stage
- Add `HEALTHCHECK` for orchestrator integration
- Use `.dockerignore` to exclude `node_modules`, `.git`, tests
## Kubernetes Deployment Manifest
```yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: api-server
labels:
app: api-server
spec:
replicas: 3
selector:
matchLabels:
app: api-server
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
template:
metadata:
labels:
app: api-server
spec:
containers:
- name: api
image: registry.example.com/api:v1.2.3
ports:
- containerPort: 3000
resources:
requests:
cpu: 100m
memory: 128Mi
limits:
cpu: 500m
memory: 512Mi
readinessProbe:
httpGet:
path: /health
port: 3000
initialDelaySeconds: 5
periodSeconds: 10
livenessProbe:
httpGet:
path: /health
port: 3000
initialDelaySeconds: 15
periodSeconds: 20
env:
- name: DATABASE_URL
valueFrom:
secretKeyRef:
name: api-secrets
key: database-url
```
Always set resource requests and limits. Always define readiness and liveness probes. Use `maxUnavailable: 0` for zero-downtime deploys.
## Helm Chart Structure
```
chart/
Chart.yaml
values.yaml
values-staging.yaml
values-production.yaml
templates/
deployment.yaml
service.yaml
ingress.yaml
hpa.yaml
_helpers.tpl
```
```yaml
# values.yaml
replicaCount: 2
image:
repository: registry.example.com/api
tag: latest
pullPolicy: IfNotPresent
resources:
requests:
cpu: 100m
memory: 128Mi
limits:
cpu: 500m
memory: 512Mi
ingress:
enabled: true
host: api.example.com
autoscaling:
enabled: true
minReplicas: 2
maxReplicas: 10
targetCPUUtilization: 70
```
Use `values-{env}.yaml` overrides per environment. Lint charts with `helm lint`. Test with `helm template` before deploying.
## ArgoCD GitOps Pattern
```yaml
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
name: api-server
namespace: argocd
spec:
project: default
source:
repoURL: https://github.com/org/k8s-manifests
targetRevision: main
path: apps/api-server
destination:
server: https://kubernetes.default.svc
namespace: production
syncPolicy:
automated:
prune: true
selfHeal: true
syncOptions:
- CreateNamespace=true
```
GitOps principles:
- Git is the single source of truth for cluster state
- All changes go through PRs (no `kubectl apply` in production)
- ArgoCD auto-syncs from Git to cluster
- Enable `selfHeal` to revert manual cluster changes
- Separate app code repos from deployment manifest repos
## Monitoring Stack
```yaml
# Prometheus ServiceMonitor
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: api-server
spec:
selector:
matchLabels:
app: api-server
endpoints:
- port: metrics
interval: 15s
path: /metrics
```
Key metrics to expose:
- `http_request_duration_seconds` (histogram) - request latency by route and status
- `http_requests_total` (counter) - request count by route and status
- `process_resident_memory_bytes` (gauge) - memory usage
- `db_query_duration_seconds` (histogram) - database query latency
Alert on: error rate >1%, P99 latency >2s, memory >80% of limit, pod restarts >3 in 10 minutes.
## Pipeline Best Practices
1. Keep CI under 10 minutes (parallelize jobs, cache aggressively)
2. Run linting and type checking before tests
3. Use ephemeral environments for PR previews
4. Pin all action versions to SHA, not tags
5. Store secrets in GitHub Secrets, never in workflow files
6. Use OIDC for cloud provider authentication (no long-lived keys)
7. Tag images with git SHA, not `latest`
8. Run security scans (Trivy, Snyk) on container images in CIMore Deployment & CI/CD skills
azure-enterprise-infra-planner
microsoft/azure-skills
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.
azure-kubernetes-app-deploy
microsoft/azure-skills
Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
finetuning
microsoft/azure-skills
Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).

