Microservices Architecture: Designing Scalable Distributed Systems

Microservices Architecture memecah aplikasi monolithic menjadi small, independent services. Setiap service: owns its data (database per service), independently deployable, organized around business capabilities, communicates via well-defined APIs. Benefits: Scalability (scale services independently based on demand), Technology Diversity (use different tech stacks per service), Fault Isolation (one service failure tidak bring down entire system), Team Autonomy (small teams own services end-to-end), Faster Deployment (deploy services independently). Challenges: Distributed System Complexity (network latency, partial failures), Data Consistency (CAP theorem, eventual consistency), Testing Difficulty (integration testing complex), Operational Overhead (monitoring multiple services), Service Discovery. Design principles: Single Responsibility (each service one business capability), Loose Coupling (minimize dependencies), High Cohesion (related functionality together), API-first Design, Stateless Services (enable horizontal scaling). Communication patterns: Synchronous (REST, gRPC) untuk request-response, Asynchronous (message queues: RabbitMQ, Kafka) untuk event-driven. Service mesh: Istio, Linkerd handle cross-cutting concerns (service discovery, load balancing, authentication, monitoring). API Gateway: single entry point, request routing, authentication/authorization, rate limiting, response aggregation. Tools: Kong, AWS API Gateway, Azure API Management. Data management: Database per service (polyglot persistence), avoid distributed transactions (use Saga pattern), Event Sourcing untuk audit trails, CQRS (Command Query Responsibility Segregation). Observability critical: Distributed Tracing (Jaeger, Zipkin), Centralized Logging (ELK stack), Metrics (Prometheus, Grafana), Health Checks. Deployment: Containerization (Docker) dengan orchestration (Kubernetes), CI/CD pipelines per service, Blue-Green/Canary deployments. Security: authentication (JWT, OAuth2), authorization (role-based, policy-based), API security, secrets management (Vault). Testing strategy: unit tests, contract testing (Pact), integration testing, chaos engineering (Chaos Monkey). When to use microservices: complex applications, need for scalability, large teams, rapid iteration. When to avoid: simple applications, small teams, uncertain requirements. Migration strategy: start with monolith, identify service boundaries via Domain-Driven Design, strangler pattern (gradually extract services). Anti-patterns: distributed monolith, chatty services, shared database. Real-world examples: Netflix, Uber, Amazon extensively use microservices. Microservices adalah powerful architecture tapi increases complexity, only adopt jika benefits outweigh costs.