Category: Engineering Decisions

The Azure OpenAI bill surprises most teams. Not because of the obvious costs — but because of the ones nobody documented.

Kafka tutorials show the happy path. This is the other one — the production failures, the trade-offs, and the honest answer to when you shouldn’t use Kafka at all.

Distributed systems fail in ways that are hard to reproduce and harder to explain. Here’s the debugging workflow I’ve built from years of production incidents — no tools survey, just what actually works.

Entity Framework is the default. It’s also the source of most database performance fires I’ve debugged. Here’s when the ORM loses and what I reach for instead.

API versioning sounds solved until you break a consumer in production. Here’s what actually matters when you manage versions at scale.

Every architecture decision I’ve regretted had the same root cause: complexity I didn’t need. This is what I learned building backend systems at a Canadian development bank.

he .NET solution structure decisions you make on day one don’t hurt on day one. They start hurting around month six. Here’s what I enforce on every project.

Adding a message queue feels like a safe architectural choice. Here’s why it’s not a default — and what the tutorials don’t tell you about running them in production.