Programming Tutorials

  You have successfully implemented Event Sourcing using the Axon Framework. Your event store is immutable, capturing every state change your application has ever seen. It works perfectly until your domain logic evolves. You add a new mandatory field to an existing event class. You deploy the new version. Suddenly, your replay fails, or your projection groups stall. The logs are flooded with serialization exceptions: com.fasterxml.jackson.databind.exc.MismatchedInputException: Missing required creator property 'currency' This is the "Schema Evolution" problem. Since you cannot modify the historical events in your append-only store, you must bridge the gap between the old data structure and your new Java class definition. The solution is not to relax your serialization rules, but to implement  Upcasters . The Root Cause: The Immutability Paradox In a CRUD-based system, schema changes are handled via database migration scripts (e.g., Flyway or Liquibase). You simply run...

  The "Grey Screen" of Replays You have a mature Event Sourced system. The  UserRegistered  event has been production-stable for two years. Today, you decided to refactor. The  fullName  string field in the payload is technically debt; you need structured data. You split it into  firstName  and  lastName , update your domain models, run the tests, and deploy. Ten minutes later, your projection replay service crashes. Error: Validation Failed. Path: ['firstName'] - Required Path: ['lastName'] - Required Source: { "fullName": "John Doe", ... } You just broke the cardinal rule of Event Sourcing:  The Event Store is an immutable ledger.  You cannot simply run an  UPDATE  SQL statement to migrate historical JSON blobs to the new schema because that corrupts the cryptographic or logical integrity of the log. Yet, your new code cannot understand the old language. The Root Cause: Immutable Facts vs. Mutable Code The core conflict lies...