Monolith Decomposition isn’t a refactor—it’s an organizational reset. Carve along the business seams—code follows. Principled Microservices Playbook This article is a standalone deep dive on how to properly decompose a monolith and is a chapter in our comprehensive series. You don’t need any prior context to get the full value from this post. To explore…
Most developers see @Transactional as a magic spell for data integrity. But a deeper understanding reveals it’s a powerful policy enforced by a proxy. This perspective immediately leads to a critical design question that is often overlooked: where should this policy be declared? This is not a simple coding convention. This decision directly impacts your…
We’ve all seen it. A critical operation fails halfway through, leaving data in a corrupted, inconsistent state. The @Transactional annotation was supposed to be the safety net, but it failed. The problem isn’t the tool. It’s the blind faith we place in it. To build truly resilient systems, we can’t just trust the magic. We…
Two-Pizza Team Myth says small squads unlock endless agility—until the invoice shows up. Principled Microservices Playbook This article is a standalone deep dive on how to properly decompose a monolith and is a chapter in our comprehensive series. You don’t need any prior context to get the full value from this post. To explore all…
A lesson in finding the root cause when everyone is fighting symptoms. One afternoon, a developer on my team deployed a new feature to our staging server. Five minutes later, that server was dead in the water. The QA team was completely blocked. All other development work ground to a halt. I’m the Tech Lead…
When microservices each own their own database, a single global transaction across multiple services is typically unfeasible. Rather than forcing a “one-shot” commit or rollback (like 2PC), the SAGA pattern coordinates each service’s local transaction in a way that either all services complete successfully or any partial changes are undone by compensating transactions. This part…
In a monolithic system—where you likely have a single database—transaction handling can be straightforward: a single @Transactional boundary often suffices to guarantee atomicity (all-or-nothing). However, once you split your application into multiple microservices, each with its own local database or data store, old assumptions break down. Atomic updates across services become much harder, and the…
Even in microservices, where each service has its own database and a SAGA or TCC pattern coordinates commits, every service still relies on local transactions internally. Meanwhile, many applications remain monolithic or partially modular, handling multiple DAOs or repositories within a single DB connection. In both worlds, Spring’s @Transactional is the bedrock for ensuring atomic…
In-memory database tests with @Transactional are great for quick feedback, but they don’t fully capture real concurrency or vendor-specific behaviors in MySQL, PostgreSQL, or Oracle. Plus, if your app calls external services—like a payment gateway—you can’t rely on local rollback to undo a “live” network call. That’s where Testcontainers and mocks come in. By spinning…
Have you ever run a test that inserted some data, crashed, and then left your database in a weird state for the next test? Or spent hours resetting your DB every time you ran your suite, just to avoid leftover rows cluttering the tables? These headaches arise when we fail to test our transactional logic…
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