Watch any whiteboard system-design session and you'll see candidates reach for Kafka in the first 60 seconds. Most of the time, the right answer is much smaller — and far more impressive to a senior interviewer. Here's how to argue for boring infrastructure without sounding lazy.
Modern Postgres on a managed instance handles 5–20K writes per second comfortably. Most products never hit that ceiling. Adding a queue, a stream processor, and a NoSQL store before you have to is the engineering equivalent of buying a forklift to carry your groceries.
Job queue, notifications, audit log, retries, idempotency — all of it can ride on a single `events` table with a tiny outbox pattern. Postgres LISTEN/NOTIFY is enough for low-latency fanout. Add a worker that polls FOR UPDATE SKIP LOCKED, and you have a queue that never loses a message.
Real-time pricing, telemetry firehoses, multi-region active-active — yes, those need specialised systems. But before you reach for them, ask: can the same problem be solved with stronger schema and better indexes? It usually can.
Don't say 'I would just use Postgres.' Say: 'Given the SLO and traffic profile, here's why a single Postgres primary with a read replica meets every requirement, and here's the migration path if scale 10x's.' Interviewers love the second version.
Full StackSix months ago we ripped out 14 REST endpoints. Here's the type-safety dividend, the cold-start gotcha, and the migration plan that didn't break a single learner login.
Data ScienceIf you can grok dot products, you can grok embeddings. Build a movie-recommender from scratch in 60 lines — no PyTorch, no TensorFlow, no jargon.
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