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
Apache Kafka 3.5 - Kafka Core, Connect, Streams, & Client Updates
A Special Announcement from Streaming Audio
How to use Data Contracts for Long-Term Schema Management
How to use Python with Apache Kafka
Next-Gen Data Modeling, Integrity, and Governance with YODA
Migrate Your Kafka Cluster with Minimal Downtime
Real-Time Data Transformation and Analytics with dbt Labs
What is the Future of Streaming Data?
What can Apache Kafka Developers learn from Online Gaming?
Apache Kafka 3.4 - New Features & Improvements
How to use OpenTelemetry to Trace and Monitor Apache Kafka Systems
What is Data Democratization and Why is it Important?
Git for Data: Managing Data like Code with lakeFS
Using Kafka-Leader-Election to Improve Scalability and Performance
Real-Time Machine Learning and Smarter AI with Data Streaming
The Present and Future of Stream Processing
Top 6 Worst Apache Kafka JIRA Bugs
Learn How Stream-Processing Works The Simplest Way Possible
Building and Designing Events and Event Streams with Apache Kafka
Rethinking Apache Kafka Security and Account Management
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