Most systems today use CRUD: read the current state, modify a row, write it back. The database remembers where things
Continue readingEvent Sourcing in Practice: Building a System That Never Forgets
Distributed transactions are one of those problems that look simple until you split your monolith into services. In a single
Continue readingThe Saga Pattern: Coordinating Distributed Transactions in Microservices
Every application that updates a database and then does something else — pushes to a search index, invalidates a cache,
Continue readingChange Data Capture with PostgreSQL and Debezium: Building Reliable Event Pipelines
Most applications start with a simple mental model: one database, one set of tables, and CRUD operations that read and
Continue readingCQRS in Practice: Splitting Reads and Writes for Scalable Systems
Every developer who has worked with microservices eventually hits the same wall: a single business operation needs to touch multiple
CQRS and Event Sourcing: Building an Order System from Scratch in Go Most of us build CRUD services by default:
Continue readingCQRS and Event Sourcing: Building an Order System from Scratch in Go
When a single database holds all your data, transactions are straightforward: begin, commit, rollback. But in a microservices architecture, where
Continue readingThe Saga Pattern: Distributed Transactions Without the Pain
Most applications store data the same way: overwrite the current state and move on. A customer changes their address? Update
Event-driven architecture is the default for most microservices systems today. Services communicate by publishing events to a message broker —
Continue readingThe Outbox Pattern: Solving the Dual-Write Problem in Event-Driven Microservices