DevOps 2025 — GitOps, Platform Engineering & AI (Practical Guide)

Practical, step-by-step guide to implementing GitOps + a minimal internal developer platform (IDP) and an AI-assisted observability demo. Includes a runnable GitHub repo, code snippets, and a cheat-sheet CTA.

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TL;DR

GitOps (Argo CD / Flux), Platform Engineering (IDPs), and AIOps are the highest-impact DevOps themes in 2025. This walkthrough shows a compact, practical mini-project you can run in minutes: build a sample Node microservice, deploy it via GitOps, scaffold environments with GitHub Actions, and add a simple alert -> LLM suggestion pipeline (human-in-the-loop). Repo link and assets at the end.

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Why this matters

• Repeatability: GitOps makes deployments auditable and reproducible.

• Developer velocity: A minimal IDP gives developers safe self-service.

• Reduced toil: AIOps can triage and suggest next steps so humans focus on decision-making.

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What you’ll ship (quick)

• A public GitHub repo with:

  • A sample Node app (Dockerfile + k8s manifests)

  • ArgoCD Application manifest

  • GitHub Actions workflow to build image & update manifests

  • A PrometheusRule alert and a webhook that sends alert context to an LLM

• A short GIF showing git push → ArgoCD sync → new pod

• A cheat sheet you can give subscribers

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Repo layout (what to push)

/README.md
/apps/sample-node/Dockerfile
/apps/sample-node/index.js
/apps/sample-node/k8s/deployment.yaml
/apps/sample-node/k8s/service.yaml
/gitops/argocd/application.yaml
/.github/workflows/deploy.yml
/observability/prometheus-rules.yaml
/observability/otlp-demo/README.md
/assets/cover.png
/assets/demo.gif

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Step-by-step (the core bits)

1) ArgoCD Application (paste into /gitops/argocd/application.yaml)

apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: sample-node
  labels:
    app.kubernetes.io/name: sample-node
spec:
  project: default
  source:
    repoURL: 'https://github.com/<YOUR-USER>/devops-2025-demo'
    path: apps/sample-node/k8s
    targetRevision: HEAD
  destination:
    server: 'https://kubernetes.default.svc'
    namespace: sample
  syncPolicy:
    automated:
      prune: true
      selfHeal: true

2) Minimal K8s deployment (paste into /apps/sample-node/k8s/deployment.yaml)

apiVersion: apps/v1
kind: Deployment
metadata:
  name: sample-node
  labels:
    app: sample-node
spec:
  replicas: 1
  selector:
    matchLabels:
      app: sample-node
  template:
    metadata:
      labels:
        app: sample-node
    spec:
      containers:
        - name: sample-node
          image: ghcr.io/<YOUR-USER>/sample-node:latest
          ports:
            - containerPort: 3000
          readinessProbe:
            httpGet:
              path: /health
              port: 3000
            initialDelaySeconds: 5
            periodSeconds: 5

3) GitHub Actions workflow (paste into /.github/workflows/deploy.yml)

name: GitOps Deploy
on:
  push:
    branches: [ main ]
jobs:
  build-and-push:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Set up Docker Buildx
        uses: docker/setup-buildx-action@v3

      - name: Log in to GHCR
        uses: docker/login-action@v2
        with:
          registry: ghcr.io
          username: ${{ github.repository_owner }}
          password: ${{ secrets.GITHUB_TOKEN }}

      - name: Build and push image
        run: |
          docker build -t ghcr.io/${{ github.repository_owner }}/sample-node:${{ github.sha }} ./apps/sample-node
          docker push ghcr.io/${{ github.repository_owner }}/sample-node:${{ github.sha }}
          echo "IMAGE=ghcr.io/${{ github.repository_owner }}/sample-node:${{ github.sha }}" >> $GITHUB_ENV

      - name: Update k8s manifest with new image
        run: |
          sed -i "s|image: .*|image: $IMAGE|" apps/sample-node/k8s/deployment.yaml

      - name: Commit updated manifest
        uses: EndBug/add-and-commit@v9
        with:
          message: 'ci: update image'
          add: 'apps/sample-node/k8s/deployment.yaml'

4) Observability alert (example /observability/prometheus-rules.yaml)

apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
  name: sample-node-rules
spec:
  groups:
    - name: sample-node.rules
      rules:
        - alert: HighErrorRate
          expr: rate(http_server_errors_total[2m]) > 0.05
          for: 2m
          annotations:
            summary: "High error rate for sample-node"
            description: "Error rate > 5% for 2 minutes"

5) Simple AIOps webhook (concept)

• Create a tiny serverless function (AWS Lambda / Cloud Run) that:

  • Receives Prometheus Alert manager webhook.

  • Gathers context (service name, last 5 error logs/traces, recent deploys).

  • Calls an LLM with prompt: “Given these metrics and context, list 3 likely causes and 3 prioritized next actions.”

  • Sends the suggestion to Slack/Jira but requires a human approval step before automation.

Important: Always keep humans in the loop for remediation — show AI suggestions as guidance.

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CTA

Repo & cheat sheet: https://github.com/eknathdj/devops-2025-demo
Subscribe for a downloadable cheat sheet and weekly practical guides: https://eknathdj.substack.com

Author

Eknath D J — DevOps engineer. I publish project-first tutorials on GitOps, Platform Engineering, and cloud cost optimization. Subscribe for the repo + cheat sheet: https://eknathdj.substack.com