19. System Design Quick Notes

Default to simple, scalable architectures with backpressure, idempotency, and solid observability.

Question: You need to design a reliable, high-throughput API service from scratch. What would be your default Python-based architecture?

Answer: My default would be a horizontally scalable service built with FastAPI, running on Uvicorn. Data would be stored in PostgreSQL, accessed asynchronously with SQLAlchemy. A Redis instance would be used for caching and managing distributed locks. For background tasks and event publishing, I would integrate a task queue like Celery or a streaming platform like Kafka, depending on the need for replayability.

Explanation: This stack is modern, highly performant, and leverages asyncio for efficient I/O.

• Reliability: The design would incorporate timeouts and retries with jitter on all external calls, a circuit breaker for failing services, and the transactional outbox pattern to ensure events are published reliably.

• Data Integrity: I would enforce idempotency on all state-changing endpoints using an idempotency key.

• Deployment: The service would be containerized with Docker using a multi-stage build, deployed to a container orchestrator like Kubernetes, and employ a canary or blue/green deployment strategy with database migration gates to ensure zero-downtime releases. Full observability (logs, metrics, traces) would be integrated from the start using OpenTelemetry.