Spring Boot Best Practices (from learnteachmaster

✅ Spring Boot Best Practices (from learnteachmaster

1. Core Design & Abstraction

• Leverage abstractions: Use Spring Boot’s built-in abstractions (like @RestController, @ConfigurationProperties) to reduce boilerplate and enforce consistency.

• Understand annotations: Master frequently used annotations (@Component, @Service, @Repository, @Transactional) to properly separate concerns.

• Apply OO techniques: Embrace dependency injection, interface-driven design, and modularity to keep code clean and flexible.

2. REST APIs & Integration

• Keep APIs consistent: Use clear naming conventions and response formats (JSON by default).

• Client resilience: Build robust REST clients with RestTemplate or WebClient — add retries, timeouts, and error handling.

• Specialized APIs: For image or heavy processing, decide upfront between synchronous (blocking) vs. asynchronous approaches.

• Repository patterns: Adopt parent/child repository abstractions to streamline persistence and reduce duplication.

3. Data, Persistence & Transactions

• Lifecycle awareness: Be intentional about when data is persisted (@PrePersist, @PostLoad) to avoid confusion.

• Transactional boundaries: Use @Transactional at the service layer, not the controller, for atomic business logic.

• JPA integration: Align your entity design with Spring Data JPA repositories — avoid overusing native queries.

• Enums wisely: Store enums as STRING in DB for readability and forward compatibility.

• Validation: Apply @Valid and custom validators to DTOs and entities to catch issues early.

4. Observability & Logging

• Actuator first: Enable Actuator endpoints for health, metrics, and readiness probes — integrate with Prometheus/Grafana or CloudWatch.

• Structured logging: Use MDC (Mapped Diagnostic Context) for correlation IDs; prefer JSON logging for downstream analysis.

• Centralized monitoring: Aggregate logs in ELK/EFK or equivalent — don’t rely on local console.

5. Cloud, Serverless & Modern Architectures

• Serverless fit: Use Spring Boot with AWS Lambda / Azure Functions only for state-light, event-driven workloads. Keep startup times optimized with GraalVM/native images where needed.

• Cloud engineer mindset: Understand cloud-native configs (Config Server, Secrets Manager, Key Vault) and distributed tracing (Zipkin, OpenTelemetry).

• Scalability: For microservices, apply Spring Cloud Gateway or Kubernetes ingress to handle high traffic gracefully.

6. Patterns & Best Practices

• Builder pattern: Use builders in combination with Lombok (@Builder) for cleaner object creation.

• AOP wisely: Apply aspects for cross-cutting concerns (logging, auditing, security) without polluting business logic.

• Async APIs: Offload heavy work using @Async or message queues (Kafka, RabbitMQ) — never block threads unnecessarily.

• Refactor continuously: Apply OpenRewrite/ArchUnit rules to keep architecture clean and consistent across repos.

7. Specialized Use Cases

• Data strategy: “Be smart about data” — cache effectively, use connection pools, and avoid N+1 queries.

• Hasura integration: When bridging GraphQL (Hasura) with Spring Boot, let Spring handle business logic and security while Hasura handles query efficiency.

• AI + Spring Boot: Treat AI features as sidecar services; use Spring Boot to provide APIs, orchestration, and guardrails around LLM calls.

📌 Overall Golden Rules

1. Keep controllers thin, services thick — business logic belongs in services.

2. Validate early, fail fast — at the boundary of your system.

3. Observe everything — metrics, logs, traces.

4. Make it cloud-ready — 12-factor app principles, externalized config, statelessness.

5. Refactor continuously — prevent tech debt by enforcing rules with automated tools.

👉 This guide is now a consolidated Spring Boot Best Practices Playbook directly based on learnteachmaterʼs blog’s sitemap.