Microservices

Microservices are a trade-off, and I start from the domain, not the tooling. Service boundaries follow bounded contexts from DDD so each service carries a coherent slice of the business and a single team can own it end to end.

Independent deployability is the operational payoff — small, focused rollouts instead of big-bang releases. That only holds if contracts are explicit and versioned, so I invest in API contracts, event schemas, and consumer-driven testing.

The hard part is distributed-systems discipline: idempotency, outbox patterns for reliable messaging, retries and timeouts, observability across the mesh, and graceful degradation. Microservices without that discipline just turn one incident into many.

Service boundaries are the decision that decides everything. I draw them where the language and the business data change meaning (the bounded-context line), not where a table is "too big" or two classes "feel" separate — otherwise I am just building a slower monolith.

Each service owns its data, period. No shared database tables between services, no backdoors into another service's storage. The only way in is the published contract, which is what keeps the seams clean and the services independently evolvable.

Communication is a mix of synchronous calls and events, chosen by need. Command-style calls go over REST or gRPC with retries and timeouts; facts that other services react to flow as events through the outbox — which is how I avoid the dreaded dual-write problem.

Reliability is designed for partial failure. I always know what happens when a dependency is down or slow: cached fallbacks, timeouts, circuit breakers, and a degraded-but-working experience rather than cascading failure. Chaos-tested, not hoped.

Operability is a first-class requirement from day one. Distributed tracing across the call graph, structured logs with correlation IDs, and rich metrics per service mean a non-trivial architecture stays debuggable instead of becoming an archaeology project.

And I am honest about the alternative: most teams are better served by a well-modularised monolith until the deploy cadence or the team structure genuinely demands independent services. Microservices solve an organisational problem, and I only reach for them when that problem is real.

I draw service boundaries from the domain, not from table size. Each service follows a bounded context so it carries a coherent slice of the business and one team can own it end to end.

Each service owns its data. There are no shared database tables between services and no backdoors — the only way in is the published contract.

Contracts are explicit and versioned. I invest in API contracts, event schemas, and consumer-driven testing so a service can evolve without silently breaking its callers.

Reliable messaging is the default for cross-service state. The outbox pattern keeps the event and the data change atomic, so the two never diverge into inconsistency.

Idempotency and retries are designed in. Distributed calls fail; every operation must tolerate re-execution without double-effect, and consumers use inbox/outbox patterns to stay safe.

Partial failure is the expected case. I design for a dependency being down or slow with timeouts, circuit breakers, and graceful degradation — a degraded-but-working experience beats cascading failure.

Distributed tracing and correlation IDs are set up from day one. Without them a multi-service architecture is an archaeology project; with them it stays debuggable.

Env-config and feature toggles keep the estate deploy-friendly. Each service deploys independently, so a release is small and reversible rather than a coordinated big-bang.

I am honest that most teams are better served by a well-modularised monolith until independent deploy cadence genuinely demands services. Microservices solve an organisational problem, and I only reach for them when that problem is real.