# Migrating Monolithic Applications to a Microservices Architecture: Containerization and Orchestration Guide > Learn to migrate monoliths to microservices using containerization and orchestration. Decompose domains, containerize services, and secure with Kubernetes, CI/CD, observability, and service mesh. - Repository: [Arie Bregman/devops-exercises](https://github.com/bregman-arie/devops-exercises) - Tags: migration-guide - Published: 2026-02-28 --- **Migrating monolithic applications to a microservices architecture requires decomposing business domains into stateless, containerized services orchestrated by Kubernetes, with automated CI/CD pipelines, comprehensive observability, and service mesh security.** The `bregman-arie/devops-exercises` repository provides practical guidance for teams undertaking the complex transition from monolithic systems to distributed microservices. This article distills the repository's comprehensive coverage of containerization patterns, Kubernetes orchestration strategies, and DevOps practices into actionable considerations for your migration journey. ## Domain Decomposition and Service Boundaries Successful migration begins with identifying **bounded contexts** and splitting the codebase into independently deployable services. This reduces coupling and enables teams to own services end-to-end. The microservices sections of [[`README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/README.md#microservices) emphasize that proper domain decomposition is foundational to achieving the scalability benefits of microservices architecture. ## Stateless Application Design Refactor services so they **do not store data on the host**; externalize state to databases, caches, or object stores. According to [[`topics/devops/README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/devops/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/devops/README.md#stateless-applications), stateless applications are ideal for microservices because they scale horizontally without requiring sticky sessions or complex session replication. ## Containerization Best Practices Package each service in its own **Docker/Podman image** with a minimal base, explicit `CMD`, and health-check. The [[`topics/containers/README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/containers/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/containers/README.md) file covers Containerfile basics that guarantee consistent runtime across environments. ### Multi-Stage Image Builds Use multi-stage builds to reduce image size and improve security. As demonstrated in [[`topics/containers/multi_stage_builds.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/containers/multi_stage_builds.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/containers/multi_stage_builds.md), this approach separates build dependencies from production artifacts: ```dockerfile # ----- Build stage ----- FROM node:20-alpine AS builder WORKDIR /app COPY package*.json ./ RUN npm ci COPY . . RUN npm run build # produces dist/ # ----- Runtime stage ----- FROM node:20-alpine WORKDIR /app COPY --from=builder /app/dist ./dist COPY package*.json ./ RUN npm ci --only=production CMD ["node", "dist/index.js"] ``` ### Image Security and Scanning Limit layers, scan images with tools like *hadolint*, and keep secrets out of images. The [[`topics/containers/working_with_images.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/containers/working_with_images.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/containers/working_with_images.md) file provides steps for building, scanning, and pushing container images securely. ## Kubernetes Orchestration Deploy containers to **Kubernetes** to handle scaling, self-healing, and rollout strategies automatically. The [[`topics/kubernetes/README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/kubernetes/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/kubernetes/README.md) provides comprehensive coverage of Kubernetes fundamentals, including Deployments, Services, ConfigMaps, and Ingresses. ### Basic Deployment Manifest Define your service with proper health checks and resource specifications: ```yaml apiVersion: apps/v1 kind: Deployment metadata: name: payment-service spec: replicas: 3 selector: matchLabels: app: payment template: metadata: labels: app: payment spec: containers: - name: payment image: registry.example.com/payment-service:1.2.0 ports: - containerPort: 8080 readinessProbe: httpGet: path: /health port: 8080 initialDelaySeconds: 5 periodSeconds: 10 --- apiVersion: v1 kind: Service metadata: name: payment-service spec: selector: app: payment ports: - protocol: TCP port: 80 targetPort: 8080 type: ClusterIP ``` ### Resource Management and Scheduling Set appropriate CPU/memory **requests**, use node affinity, taints/tolerations, and pod-disruption budgets. According to [[`topics/kubernetes/README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/kubernetes/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/kubernetes/README.md#scheduler), these settings ensure predictable performance and prevent resource contention in multi-tenant clusters. ## Service Discovery and API Gateways Deploy an **API gateway** (e.g., Kong, Ambassador) or use **Ingress** objects to provide a single entry point that abstracts internal service topology. The [[`README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/README.md#api-gateways) explains that API gateways handle routing, rate limiting, and authentication concerns centrally. ## Service Mesh for Secure Communication Adopt a **service mesh** such as **Istio** for mutual TLS (mTLS), traffic policies, and observability without requiring code changes. As documented in [[`topics/kubernetes/README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/kubernetes/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/kubernetes/README.md#istio), Istio enables zero-trust communication between services. ### Istio VirtualService Example ```yaml apiVersion: networking.istio.io/v1alpha3 kind: VirtualService metadata: name: payment spec: hosts: - payment-service.default.svc.cluster.local http: - route: - destination: host: payment-service port: number: 8080 retries: attempts: 3 perTryTimeout: 2s fault: delay: percentage: value: 10 fixedDelay: 5s ``` ## Observability and Monitoring Instrument services with **Prometheus** metrics, **Grafana** dashboards, and distributed tracing (e.g., Jaeger, AWS X-Ray) to enable rapid troubleshooting of complex distributed flows. The [[`README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/README.md#prometheus) highlights Prometheus as the standard for metrics collection in cloud-native environments. ## CI/CD Pipeline Automation Create pipelines that **build**, **test**, **scan**, **push** images, and **deploy** via Helm or `kubectl`, sharing common stages across services. According to [[`topics/cicd/README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/cicd/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/cicd/README.md), sharing pipeline logic guarantees repeatable, automated delivery across multiple microservices. ### Sample GitHub Actions Pipeline ```yaml name: CI on: push: branches: [ main ] jobs: build-and-deploy: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 # Build Docker image - name: Build image run: | docker build -t ghcr.io/${{ github.repository }}:${{ github.sha }} . # Scan image (hadolint) - name: Lint Dockerfile uses: hadolint/hadolint-action@v2 with: dockerfile: Dockerfile # Push to registry - name: Login to GHCR uses: docker/login-action@v2 with: registry: ghcr.io username: ${{ github.actor }} password: ${{ secrets.GITHUB_TOKEN }} - name: Push image run: | docker push ghcr.io/${{ github.repository }}:${{ github.sha }} # Deploy to Kubernetes - name: Deploy uses: azure/k8s-deploy@v3 with: namespace: prod manifests: | k8s/deployment.yaml k8s/service.yaml images: | ghcr.io/${{ github.repository }}:${{ github.sha }} ``` ## Data Consistency and Testing Strategy Decide between **saga patterns**, **event sourcing**, or **distributed transactions** to maintain data integrity across services, keeping databases per service where possible. Include unit tests, contract tests (e.g., Pact), integration tests using *testcontainers*, and end-to-end smoke tests in CI. The [[`topics/containers/working_with_images.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/containers/working_with_images.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/containers/working_with_images.md) file provides guidance on testing containerized applications. ## Security and Governance Store secrets in Kubernetes **Secrets**, external vaults, or KMS, avoiding hard-coded credentials in images. Enforce image scanning, resource quotas, network policies, and RBAC across the cluster. According to [[`topics/kubernetes/README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/kubernetes/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/kubernetes/README.md), resource quotas maintain compliance and prevent "snowflake" clusters. ## Summary - **Domain decomposition** is the foundation: identify bounded contexts before writing code. - **Stateless services** enable horizontal scaling; externalize all state to databases or caches. - **Containerization** requires multi-stage builds, minimal base images, and continuous scanning. - **Kubernetes orchestration** handles deployment, scheduling, and self-healing through declarative manifests. - **Service mesh** (Istio) and **API gateways** provide secure, observable traffic management. - **Observability** requires Prometheus metrics, Grafana dashboards, and distributed tracing. - **CI/CD automation** ensures repeatable builds, tests, and deployments across services. - **Security** mandates secrets management, RBAC, and network policies from day one. ## Frequently Asked Questions ### How do you determine service boundaries when decomposing a monolith? Identify **bounded contexts** by mapping business capabilities and looking for natural seams in the codebase where data and transaction boundaries align. According to the microservices sections of [[`README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/README.md#microservices), each service should own its data end-to-end to reduce coupling and enable independent deployment. ### What is the difference between stateless and stateful services in microservices? **Stateless services** do not store session data on the host filesystem, allowing any instance to handle any request and enabling horizontal scaling via simple replication. As documented in [[`topics/devops/README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/devops/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/devops/README.md#stateless-applications), stateful components like databases should run as external managed services or dedicated StatefulSets, not within general application containers. ### Why use a service mesh like Istio instead of direct service communication? A **service mesh** provides **mutual TLS (mTLS)**, traffic policies, and observability without requiring changes to application code, enabling zero-trust security between services. According to [[`topics/kubernetes/README.md`](https://github.com/bregman-arie/devops-exercises/blob/main/topics/kubernetes/README.md)](https://github.com/bregman-arie/devops-exercises/blob/master/topics/kubernetes/README.md#istio), Istio handles retries, circuit breaking, and fault injection at the infrastructure layer, insulating business logic from network complexity. ### How do you handle database migrations during microservices transition? Adopt the **database-per-service** pattern and use **saga patterns** or **event sourcing** to maintain data consistency across distributed transactions, avoiding two-phase commits. While not explicitly detailed in the repository's code samples, the migration workflow implies shifting stateful components to external managed services and updating connection strings in Kubernetes ConfigMaps or Secrets, as suggested by the containerization and orchestration sections.