Anti-Patterns

Microservices Design Patterns and Anti‑Patterns Microservices promise autonomy, scalability, and resilience, but they also add complexity. Patterns help teams build solid blocks, while anti-patterns warn about common traps. This guide covers practical patterns, with clear notes on when to use them and what to watch for in real projects. Common Design Patterns Decomposition by business capability (bounded context): align services to real domains; avoid too many tiny services or ill‑defined boundaries. API Gateway: a single entry point for routing, auth, rate limits, and cross‑cutting concerns. Database per service with data ownership: each service owns its data; use events or APIs to synchronize interesting changes. Saga for distributed transactions: choose choreography or orchestration to keep data consistent without distributed locks. Event‑driven architecture: services publish and react to events, increasing decoupling and resilience. Asynchronous messaging: queues and streams absorb bursts and failures, with clear delivery guarantees. Service discovery and load balancing: services find each other, scale, and recover gracefully. Resilience patterns: circuit breakers, bulkheads, timeouts to limit cascading failures. Observability by design: structured logs, metrics, tracing to debug and optimize. Anti‑Patterns to Avoid Shared database across services: creates tight coupling and data drift. Chatty inter‑service calls: many small requests add latency and failure risk. God services: large, multifunction components slow to evolve and hard to test. Tight coupling via contracts without versioning: breaking changes disrupt consumers. Hidden data stores and unclear ownership: teams argue over who controls what. Circular calls and leaked dependencies: tight loops escalate latency and faults. Ignoring observability: incidents become mysterious and slow to fix. Unmanaged eventual consistency: soft guarantees without a plan cause data surprises. Practical tips for teams Start with domain‑driven decomposition; define clear bounded contexts. Create stable API contracts and plan versioning; use consumer‑driven contracts when possible. Favor event sources to align state changes across services. Implement basics of resilience early: timeouts, retries, circuit breakers. Build observability from day one: trace IDs, correlated logs, dashboards. Test at multiple levels: unit, contract, and end‑to‑end tests that cover failure scenarios. Key Takeaways Choose a few core patterns aligned with your domain; scale patterns as teams grow. Avoid shared databases and noisy inter‑service calls to keep services independent. Prioritize observability and contracts to detect issues quickly and safely evolve your system.

Secure Web Applications: Patterns and Anti-patterns Building secure web apps starts with patterns you can reuse, and it avoids risky habits that slip in during tight deadlines. This guide highlights practical patterns and common anti-patterns, with simple checks you can apply today. Think of security as defense in depth. Patterns focus on reliable designs, while anti-patterns show what to avoid. By combining server-side validation, strong identities, and careful data handling, you reduce the chance of major flaws. ...