Question 1

When should I NOT use microservices?

Accepted Answer

Microservices add operational complexity (deployment, monitoring, debugging across services). Avoid if: (1) small team (<10 engineers, monolith is faster), (2) low concurrency (scaling only one part isn't valuable), (3) tight latency budgets (network calls add milliseconds), (4) simple domain (CRUD app ≠ needs services). Rule of thumb: start with monolith, split when team/traffic justifies the complexity.

Question 2

Should I always start with a monolith?

Accepted Answer

Yes, 'monolith first' is the industry consensus (Sam Newman, Martin Fowler). Microservices shine when you outgrow a monolith: multiple teams, different scaling needs, separate deployment cycles. At startup stage (< 50 engineers), a well-structured monolith is faster than coordinating 10+ services. Netflix started monolith, migrated to microservices at ~300 engineers. Airbnb, Stripe, etc. kept monoliths much longer than expected.

Question 3

How do I handle distributed transactions across services?

Accepted Answer

ACID transactions don't exist across services (you can't lock rows in another service's DB). Use Saga pattern instead: (1) orchestration-based (centralized coordinator calls services sequentially) or (2) choreography-based (services emit events, other services react). Example: Order Service reserves inventory (Inventory Service), charges payment (Payment Service), if payment fails publish CompensationRequested, Inventory Service releases reservation. Eventual consistency: accept that orders may be temporarily inconsistent (payment pending) but converge within seconds/minutes.

Question 4

How do I define service boundaries?

Accepted Answer

Use domain-driven design (DDD): each service = one business capability (User Management, Order Processing, Payment). Boundaries = what would require different teams or scaling independently. Test: can two services be deployed at different schedules without coordination? If not, they're too coupled. Anti-pattern: 'Service per database table' (leads to chatty services). Pro tip: service boundaries emerge over time, start with obvious splits (auth service, API service), refine as you learn.

Question 5

How do I ensure observability in a distributed system?

Accepted Answer

Three pillars: (1) Logs (ELK, Splunk, CloudWatch), what happened where. (2) Metrics (Prometheus, Datadog), throughput, latency, error rate per service. (3) Traces (Jaeger, Zipkin, Datadog), follow one request across all services with unique trace ID. Correlation IDs essential: attach X-Trace-ID to every request header so you can join logs/metrics/traces. Without tracing, debugging '500 error in production' = nightmare in 10+ services.

Question 6

How do I coordinate deployments across microservices?

Accepted Answer

Don't coordinate, each service deploys independently (that's the point). Use blue-green deployments (new version runs alongside old, flip traffic instantly), canary deployments (1% traffic to new version, monitor, 100% if good), or feature flags (deploy code but disable feature until ready). Database migrations trickier: deploy backward-compatible migrations first (add column but don't use it), then deploy code using new column, then remove old column in next release. Tools: Kubernetes handles this via rolling updates.

Question 7

What organizational changes come with microservices (Conway's Law)?

Accepted Answer

System architecture mirrors organization structure (Conway's Law). Microservices = one service per team. Requires: (1) clear ownership (who's on-call for the payment service?), (2) async communication (don't wait for other team's code review), (3) clear APIs and SLAs (service X promises 99.9% uptime, <100ms latency). At scale, you need: platform teams (provide Kubernetes, monitoring, CI/CD), infrastructure teams (run the platform). Small team adopting microservices without org change = suffering (meetings to deploy together defeats the purpose).

प्रदेश	ज्युनियर	मध्यम	सीनियर
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UK	£80k	£125k	£170k
EU	€85k	€130k	€185k
CANADA	C$135k	C$190k	C$270k

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