Event-Driven Systems
Events vs commands, pub/sub, event sourcing intro.
Theory
Event-driven architecture uses immutable events as the integration contract between services. Producers emit facts ("OrderPlaced", "PaymentCaptured") without knowing which services will react — enabling loose coupling and independent evolution.
Choreography lets each service subscribe and react independently; orchestration uses a central coordinator (saga manager) to sequence steps. Choreography scales better; orchestration is easier to visualize and debug.
Schema versioning and a schema registry (Avro, Protobuf) prevent breaking consumers when event shapes evolve. Combine with distributed tracing so a single user action's event chain remains observable across services.
Production rollouts require idempotent automation, peer review, staged apply, and documented rollback — treat changes as production code.
Interviewers want STAR stories linking Event-Driven Systems to measurable outcomes: fewer outages, faster deploys, lower cost, or reduced toil.
Architecture Diagram
Users / clients
|
Event-Driven Systems
|
Core services
|
Data + observabilityExamples
# Event-Driven Systems
# Events vs commands, pub/sub, event sourcing intro.
# Validate in staging before production rollout.Interview Questions
What problem does Event-Driven Systems solve?
It addresses the core use case described in production architecture — map features to reliability, scale, or velocity outcomes.
Key components of Event-Driven Systems?
Identify inputs, outputs, control plane, data plane, and failure domains — interviewers want structured decomposition.
Common production pitfalls?
Misconfiguration, missing observability, no rollback path, and scaling bottlenecks under peak load.
How do you test changes safely?
Staging parity, canary/gradual rollout, automated health checks, and documented rollback.
Metrics to prove success?
Error rate, latency percentiles, throughput, cost, and toil reduction — pick one primary SLO.
Beginner vs advanced concern?
Beginners focus on setup; advanced teams focus on blast radius, security boundaries, and operability at 10× scale.
Best Practices
- Treat Event-Driven Systems config as code with review and CI validation.
- Define SLOs and dashboards before production cutover.
- Document rollback and ownership for on-call.
- Use least privilege for credentials.
Common Mistakes
- Adopting Event-Driven Systems without measurable success criteria.
- No staging environment mirroring production constraints.
- Missing rollback path during incidents.
- Undocumented on-call expectations.
Trade-off Analysis
Event-Driven Systems improves events vs commands, pub/sub, event sourcing intro. but adds operational and cognitive complexity — justify with load and team size.
Favor simplicity until metrics (p99 latency, error rate, cost) prove the pattern necessary.
Every redundancy layer trades capital/operational cost for availability — align with explicit SLO targets.
Document accepted inconsistency windows and recovery behavior before production cutover.
Cheat Sheet
Practical Exercises
Stand up Event-Driven Systems locally or in free tier; document commands and failure recovery.
Introduce misconfiguration; practice detection and rollback under time limit.