IBM TechCon is an annual online technical event for engineers, creators, and integration specialists.
One of our sessions for this year was Deploying an Apache Flink job into production:
You’ve maybe seen the low-code canvas in Event Processing or the simple expressiveness of Flink SQL, and how easy they make it to author event stream processing. A business user who understands the data in the event stream can easily describe the patterns they’re interested in or the insights they want to look for. But what comes next?
In this session, we’ll walk through the ops tasks involved in taking that event processing flow, and deploying it into Kubernetes as a Flink application ready for production.
We’ll outline the steps that are needed and describe the main decisions you need to make. This includes the sorts of values you will want to monitor to make sure that your Flink application continues to run correctly.
It was a live walk-through of the steps involved in deploying Flink jobs in Kubernetes. I used Event Processing to create the Flink job that I used for the demos, because low-code UI’s are easier to follow in a presentation, but most of what I showed is applicable however you’ve created your Flink job – and was a high-level introduction to using the Flink Kubernetes Operator.