Derivative Event Sourcing

Anna McDonald explains the concept of derivative event sourcing:

If you happen to be the proud owner of a single order service, then you are all set to begin.

But what if you have more than one order service?

Something that tends to happen at companies that have been around for more than a sprint is the accumulation of technical debt. Sometimes that debt takes the form of duplicate applications. Mergers happen and you adopt other applications that, for reasons beyond your control, cannot be retired or rewritten right away. In other words, sometimes you end up with more than one order service—enter derivative event sourcing!

This is a nice article for real-life scenarios where you don’t get to build nice, well-designed services from scratch.

Related Posts

Spark Streaming DStreams

Manish Mishra explains the fundamental abstraction of Spark Streaming: Before going into details of the operations available on the DStream API, let us look at the input sources from which we can start a Stream. There are multiple ways in which we can get the inputs from e.g. Kafka, Flume, etc. Or simple Idle files. […]

Read More

Multi-Region Replication with Confluent Platform

David Arthur walks us through multi-region replication of Kafka clusters in the Confluent Platform 5.4 preview: Running a single Apache Kafka® cluster across multiple datacenters (DCs) is a common, yet somewhat taboo architecture. This architecture, referred to as a stretch cluster, provides several operational benefits and unlocks the door to many uses cases. Stretch clusters provide […]

Read More

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Categories

September 2019
MTWTFSS
« Aug  
 1
2345678
9101112131415
16171819202122
23242526272829
30