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Testing is one of the hardest parts of building reliable distributed systems. Kafka has long had a set of system tests that cover distributed operation but this is an area that is simply never good enough.
At Confluent and Cloudera we’ve both been working on improving the testing capabilities for Kafka.
An area of particular importance is compatibility. Companies that want to build reliable data real-time data flow and processing around Kafka need to be able to do so without fear of incompatibilities that could arise release to release or between versions of Kafka from different vendors.
We’re announcing today a project with the folks at Cloudera and the rest of the open source community to develop high quality tests to certify API and protocol compatibility between versions and distributions.
We’ll be doing this as part of the normal Apache development process, much as we do any other Kafka development.
We think ensuring this kind of compatibility is one of the key aspects of building a healthy ecosystem of systems, applications, and processing frameworks, that is the core of our stream data platform goal.
Companies are looking to optimize cloud and tech spend, and being incredibly thoughtful about which priorities get assigned precious engineering and operations resources. “Build vs. Buy” is being taken seriously again. And if we’re honest, this probably makes sense. There is a lot to optimize.
Operating Kafka at scale can consume your cloud spend and engineering time. And operating everyday tasks like scaling or deploying new clusters can be complex and require dedicated engineers. This post focuses on how Confluent Cloud is 1) Resource Efficient, 2) Fully Managed, and 3) Complete.