load-shedding aspnet-core kestrel dotnet-7 dotnet-8 resilience

27 Oct 2026

Load Shedding: Dropping Requests to Save Your System

Load shedding is the deliberate act of dropping requests to protect your system under overload. Most .NET teams don't have it.

rest-api hateoas pagination rate-limiting openapi

20 Oct 2026

REST APIs in Production: Pagination, HATEOAS, and the Patterns That Actually Matter (Part 3 of 3)

Part 3 of a REST API design series: pagination, HATEOAS, filtering and search, rate limiting, idempotency keys, and the practices that separate a demo API from a production one.

rest-api api-design versioning authentication

13 Oct 2026

REST API Design: Resources, Versioning, and Auth That Hold Up (Part 2 of 3)

Part 2 of a REST API design series: naming resources so they don't need a manual, versioning without breaking clients, choosing an auth pattern, and structuring errors.

rest-api http api-design status-codes

06 Oct 2026

REST API Design: The Constraints and HTTP Semantics Everyone Skips (Part 1 of 3)

Part 1 of a REST API design series: what REST actually is, Fielding's six constraints, and the HTTP methods and status codes most APIs get subtly wrong.

outbox-pattern inbox-pattern messaging resilience distributed-systems

29 Sep 2026

What Happens to Outbox When the Database Goes Down?

Every outbox explanation assumes the broker is what breaks. Here is what actually happens when the database is the thing that goes away.

saga-pattern compensation distributed-transactions messaging distributed-systems

22 Sep 2026

Compensation Is Not Rollback

Rollback is a database primitive. Distributed systems don't have one, and treating compensation as if they did is how workflows quietly break.

idempotency concurrency messaging distributed-systems dotnet

15 Sep 2026

Your Idempotency Check Has a Race in It

Idempotency at rest is easy. Two retries arriving at the same moment is the case that breaks the version most teams wrote.

eventual-consistency cap-theorem distributed-systems data-consistency

20 Aug 2026

Eventual Consistency Explained

Your data disagreeing with itself isn't a bug. It's a trade-off. What eventual consistency guarantees, where you're already relying on it, and how to design for it instead of getting bitten by it.