In principle, data mesh architecture should liberate teams to build their systems and gather data in a distributed way, without having to explicitly coordinate. Data is the thing that can and should decouple teams, but proper implementation has its challenges.
In this episode, Kris talks to Florian Albrecht (Solution Architect, Hermes Germany) about Galapagos, an open-source DevOps software tool for Apache Kafka® that Albrecht created with his team at Hermes, a German parcel delivery company.
After Hermes chose Kafka to implement company-wide event-driven architecture, Albrecht’s team created rules and guidelines on how to use and really make the most out of Kafka. But the hands-off approach wasn’t leading to greater independence, so Albrecht’s team tried something different to documentation— they encoded the rules as software.
This method pushed the teams to stop thinking in terms of data and to start thinking in terms of events. Previously, applications copied data from one point to another, with slight changes each time. In the end, teams with conflicting data were left asking when the data changed and why, with a real impact on customers who might be left wondering when their parcel was redirected and how. Every application would then have to be checked to find out when exactly the data was changed. Event architecture terminates this cycle.
Events are immutable and changes are registered as new domain-specific events. Packaged together as event envelopes, they can be safely copied to other applications, and can provide significant insights. No need to check each application to find out when manually entered or imported data was changed—the complete history exists in the event envelope. More importantly, no more time-consuming collaborations where teams help each other to interpret the data.
Using Galapagos helped the teams at Hermes to switch their thought process from raw data to event-driven. Galapagos also empowers business teams to take charge of their own data needs by providing a protective buffer. When specific teams, providers of data or events, want to change something, Galapagos enforces a method which will not kill the production applications already reading the data. Teams can add new fields which existing applications can ignore, but a previously required field that an application could be relying on won’t be changeable.
Business partners using Galapagos found they were better prepared to give answers to their developer colleagues, allowing different parts of the business to communicate in ways they hadn’t before. Through Galapagos, Hermes saw better success decoupling teams.
EPISODE LINKS
Building Real-Time Data Governance at Scale with Apache Kafka ft. Tushar Thole
Handling 2 Million Apache Kafka Messages Per Second at Honeycomb
Why Data Mesh? ft. Ben Stopford
Serverless Stream Processing with Apache Kafka ft. Bill Bejeck
The Evolution of Apache Kafka: From In-House Infrastructure to Managed Cloud Service ft. Jay Kreps
What’s Next for the Streaming Audio Podcast ft. Kris Jenkins
On to the Next Chapter ft. Tim Berglund
Intro to Event Sourcing with Apache Kafka ft. Anna McDonald
Expanding Apache Kafka Multi-Tenancy for Cloud-Native Systems ft. Anna Povzner and Anastasia Vela
Apache Kafka 3.1 - Overview of Latest Features, Updates, and KIPs
Optimizing Cloud-Native Apache Kafka Performance ft. Alok Nikhil and Adithya Chandra
From Batch to Real-Time: Tips for Streaming Data Pipelines with Apache Kafka ft. Danica Fine
Real-Time Change Data Capture and Data Integration with Apache Kafka and Qlik
Modernizing Banking Architectures with Apache Kafka ft. Fotios Filacouris
Running Hundreds of Stream Processing Applications with Apache Kafka at Wise
Lessons Learned From Designing Serverless Apache Kafka ft. Prachetaa Raghavan
Using Apache Kafka as Cloud-Native Data System ft. Gwen Shapira
ksqlDB Fundamentals: How Apache Kafka, SQL, and ksqlDB Work Together ft. Simon Aubury
Explaining Stream Processing and Apache Kafka ft. Eugene Meidinger
Handling Message Errors and Dead Letter Queues in Apache Kafka ft. Jason Bell
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