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Case Study: Migrating a Monolith to Cloud-Native Microservices

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Case Study: Monolith to Cloud-Native

The most common enterprise task is not building new apps, but Modernizing old ones. Migrating a 10-year-old Monolith to Microservices without downtime is the ultimate test of a Cloud Architect.

1. The "Strangler Fig" Pattern

Don't try a "Big Bang" migration. It always fails. Instead, use the Strangler Fig Pattern:

  1. Put an **API Gateway** in front of the Monolith.
  2. Take ONE small feature (e.g., Notifications) and build it as a new Microservice.
  3. Route all new notification traffic to the Microservice at the Gateway.
  4. Repeat until the Monolith is reduced to a tiny shell and can be turned off.

2. Handling Data Consistency

Moving from a single SQL DB to many Microservice DBs is hard. We use **Event Sourcing**. The Monolith publishes an event (e.g., `UserCreated`) to a Message Queue, and the new Microservices consume that event to stay in sync during the transition period.

4. Interview Mastery

Q: "How do you handle 'Shared Libraries' across microservices?"

Architect Answer: "Avoid them if possible. Shared libraries create **Deployment Coupling**—if you update the library, you have to redeploy 50 services. We prefer 'Duplication over Coupling.' If a tiny bit of logic is needed in two places, we copy it. If it's a massive, complex piece of logic, we turn it into its own **Service** and call it via gRPC. Microservices are about independence, and shared libraries are the enemy of independence."

DevOps & Cloud Architect Mastery
Course syllabus
1. Containerization with Docker Docker Internals: Namespaces, Cgroups, and UnionFS Optimizing Dockerfiles: Multi-stage builds and layer caching Docker Compose: Managing multi-container localized environments Security in Containers: Rootless mode and Image scanning
2. Orchestration with Kubernetes (K8s) K8s Architecture: Control Plane, Nodes, and Kubelet Pods, Deployments, and Services: The core building blocks Ingress Controllers & Service Mesh (Istio) integration Helm Charts: Package management for Kubernetes
3. CI/CD Pipelines GitHub Actions: Automating build, test, and deploy Jenkins Architecture: Master-Agent distributed builds Deployment Strategies: Blue-Green vs Canary vs Rolling The 'Shift Left' Philosophy: Integrating security and testing early
4. Infrastructure as Code (IaC) Terraform: Declarative infrastructure on any cloud Terraform State Management: S3 backends and State locks Ansible: Configuration management vs Infrastructure provision Pulumi: IaC using real programming languages (TS, Python)
5. Cloud Platforms Deep Dive (Azure/AWS) Virtual Networks (VPC): Subnets, Gateways, and Peering Identity & Access Management (IAM): The principle of least privilege Cloud Databases: Managed SQL vs Cosmos DB vs DynamoDB Cost Optimization: Savings Plans, Spot Instances, and FinOps
6. Serverless & Scaling AWS Lambda / Azure Functions: Event-driven scaling API Gateways: Exposing serverless functions securely Cold Starts: Understanding and mitigating latency Serverless Orchestration: Step Functions and Logic Apps
7. Security & Reliability (DevSecOps) Secrets Management: Azure Key Vault vs HashiCorp Vault Compliance as Code: Policy engines (OPA) and Audit logs Site Reliability Engineering (SRE): Error Budgets and SLOs Logs & Metrics: Setting up ELK and Prometheus in the cloud
8. FAANG Cloud Architect Interview Case Study: Migrating a Monolith to Cloud-Native Microservices Case Study: Designing a Global, Multi-Region Cloud Infrastructure
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