Stepping into the world of Apache Kafka® can feel a bit daunting at first. I know this firsthand—while I have a background in real-time messaging systems, shifting into Kafka’s terminology and concepts seemed dense and complex. There’s a wealth of information out there, and it’s sometimes difficult to find the best (and, ideally, free) resources.

Hello there! My name is Maciej Mensfeld, and some of you might recognize me from my involvement in RubyGems Security, OSS commitments, or perhaps from Karafka: a multi-threaded, efficient Kafka processing framework tailored for Ruby and Rails. While I generally pen my thoughts on my personal blog, today's post is unique. This article results from a collaborative effort with the brilliant people over at AppSignal. To set the record straight, I don't work for AppSignal.

Realtime data is rapidly becoming a standard in many consumer applications. From responsive chat applications to low latency financial applications, nobody wants to refresh their browser for new data. With lots of data bouncing around Kafka behind a firewall, it begs the question of how you can serve this information to your users without sacrificing on latency. Ably provides a seamless way to serve this data to your end users devices, globally, through a direct integration with Confluent Cloud.

At this year’s Current, we introduced the public preview of our serverless Apache Flink® service, making it easier than ever to take advantage of stream processing without the complexities of infrastructure management. This first iteration of the service offers the Flink SQL API, which adheres to the ANSI standard and enables any user familiar with SQL to use Flink.