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Today, I am pleased to announce the launch of Confluent Developer, the one and only portal for everything you need to get started with Apache Kafka®, Confluent Platform, and Confluent Cloud! Everything on Confluent Developer is completely free and ungated. It’s a single online source of everything you’ll need to learn Kafka: links to documentation, collections of video tutorials, links to sample code, the entire collection of guided Kafka Tutorials, an index of podcast episodes, and a link to our global network of meetups.
The Confluent DevRel Team and I are dedicated to the task of helping people get started with Apache Kafka. In almost three years of doing this, I’ve found that these are the things that consistently come up as the go-to resources for newcomers to the community:
Video tutorials. No matter what, you’ve got to read the docs, but some people like to watch the movie too. There’s something genuinely helpful about a human face explaining things to you—after all, this is how we learn most of what we learn—and a lot of the things we have to learn when we learn Kafka are inherently visual. Seeing activity in a browser or a terminal window unfold in video tends to make the material seem less mysterious.
Sample code. Sometimes you just want to clone a repo and dig into an example that shows you how to produce and consume, compute an aggregation in Kafka Streams, or configure a connector. Reading code is where the rubber meets the road. And having code to modify, rather than starting with a blank IDE tab? This is how our profession actually conducts itself.
Guided tutorials. Sample code is critical, but to understand it all, you might want a step-by-step account of what each part of that code does to keep you from having to switch back and forth between four documentation tabs and the code itself. Having tested examples with good inline explanation of each important part of the code (like what Kafka Tutorials provides) is the perfect blending of docs and sample code.
Podcast. Kafka is conceptually simple but has far-reaching architectural implications that affect just about every part of your software development life. Streaming Audio, our weekly podcast, can help you keep up with new features and concepts. ksqlDB, Kafka Streams, Kafka Connect, Cloud services, Kubernetes, interesting new Kafka features and use cases…it’s all there in an easily consumable resource. Whether you’re just getting started or you’re a seasoned Kafka user, Streaming Audio is for you.
Community events. Every developer spends time learning on his or her own. Sample code, tutorials, videos, and podcasts all support this, but at some point you have to get to know other people who are on your same journey and spend time with them in person. This is why we operate a global network of over 200 meetups and with more than 350 meetings and over 60 conference appearances per year. Getting together with other Kafka developers to learn together and support each other makes you an active member of the Kafka community.
We do all these things, but if you were to have asked me yesterday where you can go to find all of this in one place—which frankly would have been a pretty reasonable question—I wouldn’t have been able to tell you. I’d have told you how to Google things, where to find YouTube playlists, and where to go on GitHub. But today, that all changes. Today, you can visit https://developer.confluent.io/ and get it all. And keep checking back frequently for improvements in the site and new tutorials, videos, podcasts, demos, and meetups. We won’t be sitting still.
We are proud to announce the release of Apache Kafka 3.9.0. This is a major release, the final one in the 3.x line. This will also be the final major release to feature the deprecated Apache ZooKeeper® mode. Starting in 4.0 and later, Kafka will always run without ZooKeeper.
In this third installment of a blog series examining Kafka Producer and Consumer Internals, we switch our attention to Kafka consumer clients, examining how consumers interact with brokers, coordinate their partitions, and send requests to read data from Kafka topics.