Category
How distributed systems stay up when traffic moves from hundreds to hundreds of thousands of requests per second — the architectural decisions, trade-offs, and failure modes that actually matter at scale.
What actually breaks when a Java backend grows from hundreds of users to hundreds of thousands — and the concrete patterns, code, and trade-offs that keep it standing.
A field guide to the microservices patterns that earn their keep — what problem each one solves, when to reach for it, and what it looks like in Java code.
Transactional outbox and Change Data Capture solve the same problem differently. The practical trade-offs, and how to decide between them for your system.
The most-preached and least-followed rule of microservices. Why teams bend it, what breaks when they do, and the practical patterns for keeping services data-independent.
The BFF pattern, why it often beats a single generic API, and how to avoid turning your BFFs into a new kind of monolith.