DataOps challenges us to build data experiences in a repeatable way. For those with Kafka, this means finding a means of deploying flows in an automated and consistent fashion.
The challenge is to make the deployment of Kafka flows consistent across different technologies and systems: the topics, the schemas, the monitoring rules, the credentials, the connectors, the stream processing apps. And ideally not coupled to a particular infrastructure stack.
In this talk we will discuss the different approaches and benefits/disadvantages to automating the deployment of Kafka flows including Git operators and Kubernetes operators. We will walk through and demo deploying a flow on AWS EKS with MSK and Kafka Connect using GitOps practices: including a stream processing application, S3 connector with credentials held in AWS Secrets Manager.