#backend

Not hard, not expensive, not a premium tier. Impossible, in the proven sense, and it follows from the Two Generals problem. Every product advertising exactly-once is selling at-least-once with deduplication bolted on, which means the work was always going to land on your consumer.

The famous framing is wrong twice over. Partition tolerance was never something you choose, and the trade-off only exists while a partition is happening. Which means CAP is silent about the decision you actually make every day, and PACELC is the version that names it.

Almost every explanation frames this as being kind to a struggling downstream service. That is a side effect. Its actual job is stopping your own threads from piling up on timeouts, which is how a dependency you barely use takes down a service that does not need it.

The design detail that surprises people: Stripe caches the result of the first request under a key even when that result was a 500, and replays the failure to every retry. That is correct, and once you see why, the rest of the design follows, including where most homegrown implementations go wrong.

Everyone compares token bucket to sliding window and stops there. The decisions that actually determine whether a rate limiter works are what you key it on, whether your Retry-After header is quietly scheduling a thundering herd, and whether a client that gets a 429 can safely retry at all.

Microservices solve an org-scale problem, not a code problem. Here is how to actually decide between a monolith and microservices, and why most startups should start with the monolith.

Frontend is what you see, backend is what you don't, and full stack is doing both. Here is what each role actually builds, the tools they use, and honest career advice if you are just starting out.

Most REST vs GraphQL vs gRPC posts list features in a table and stop. The real decision isn't about features. It's about who consumes your API and what hurts at scale.

Walk through every OWASP API Security Top 10 vulnerability with real attack examples and code-level mitigations you can ship this week.

A production guide to building high-performance Python backends with FastAPI, async SQLAlchemy, Pydantic v2, and modern deployment patterns.

A pragmatic, opinionated framework for choosing between Rust and Go, with honest takes on performance, hiring, ecosystem maturity, and the workloads where each actually wins.