moai-domain-backend-architecture

Scalable backend architecture uses layered or modular patterns with API design (REST, GraphQL, gRPC), repository layers for data access, caching strategies, and horizontal scaling via Kubernetes. Start by decomposing your service into logical layers, then apply cloud-native patterns and observability instrumentation to monitor performance as load increases.

Database optimization combines ORM usage, migration strategies, and caching approaches. Apply repository patterns to abstract data access, use query optimization and connection pooling, and layer caching strategies between your API and database to reduce latency and improve throughput at scale.

Observability requires monitoring and tracing instrumentation across your services. Use tools like OpenTelemetry and Prometheus to collect metrics, traces, and logs from your API and infrastructure. Instrument your code to emit telemetry, then aggregate signals to detect bottlenecks and troubleshoot failures.

Kubernetes orchestrates containerized backend services for horizontal scaling and resilience. Istio provides service mesh capabilities for traffic management, security, and observability between services. Use them together when you need reliable, observable deployment of multiple interdependent APIs at scale.

REST is simple and cacheable but verbose; GraphQL reduces over-fetching with client-driven queries but adds server complexity; gRPC uses binary protocols for high-performance service-to-service communication. Choose based on client needs, latency requirements, and ecosystem maturity for your use case.