Backend Engineering

Posts on backend engineering — the language-agnostic patterns and decisions that define a great backend. API design, caching, queues, observability, system design tradeoffs, and the lessons that apply whether you write Python, Go, or anything else.

Kafka vs NATS vs RabbitMQ in 2026 — How to Pick a Message Broker

When to pick Kafka vs NATS vs RabbitMQ. Semantics, throughput numbers, ordering and persistence guarantees, operational cost, and a decision tree based on what you’re actually building.

Designing REST APIs That Don't Suck

How to design REST APIs that age well: resource modeling, HTTP method semantics, status codes, structured errors, pagination, idempotency, and versioning.

Rate Limiting Strategies for APIs

A practical comparison of rate limiting algorithms (fixed window, sliding window, leaky bucket, token bucket), production-ready Redis implementations, and the headers your API should return.

Redis Caching Strategies for Backend Developers

How to use Redis as a cache properly — patterns (cache-aside, read-through, write-behind), key design, TTLs, invalidation, and the production gotchas to avoid.