Apache Kafka

“And you know, it actually took a while, you know, probably the first year, it mostly sat on the shelf as a open source project, which we were quite disappointed about.”

“What was it that it took us probably several years to discover was basically product marketing. You know, in an open source context was, yeah, you gotta tell people why it's interesting.”

“I think initially just picking up Kafka, Spark, those are still so heavily in use that even if they go out in the next three to five years, it's going to take time to migrate and things of that nature.”

“We actually began by researching the market to see if anyone had built something like that. So definitely wasn't the preference to build Apache Kafka, but when we realized that nothing else existed, we decided to take the leap and start Apache Kafka, open sour…”

“So this conference started four years after Apache Kafka was open sourced and became successful and It was very much an organic decision.”

“Confluent kind of started with a proven technology that was used at, you know, roughly 50% of Fortune 500 companies at that point in time.”

“The first one was operational ease, you know, offering tools and enhancements to simplify the deployment, management, and scaling of Kafka clusters, which is actually, I think, the right starting point for many open source companies.”

“Kafka, you know, that was one of the reasons why we couldn't or we didn't sort of narrowly focus on an ICP like traditional companies do for good reason. It was because, you know, the Kafka adoption base was so broad and for Confluent to quickly convert those …”

“Features that directly Enabled the end users of the open source product. We believe should ideally remain open source or be open source.”

“We kept the foundational teams the same. So there was only one team ever working on Apache Kafka and the foundation. There was only one team that was ever developing a specific proprietary feature set. So we never split, you know, specific teams or individual …”

“At Confluent, we could lean on the brand of a very popular Open source projects, so the zero to one branding phase was actually really easy. With Ocelor, you're, you know, humbled that you're starting with something that people don't really know about.”

“They were saying, I'm faster than Kafka, which is what a business wants to hear. Higher efficiency, lower cost, et cetera. And the developer experience is better. There's a single statically linked C++ binary. It's easier to work with it on your laptop, lower …”

“We run them in shadow mode, which means, like, they do all the evaluation, but the results are logged to Kafka, and we see if the time to response, if the sort of distribution of predictions are different or not.”