Introduction
After working in multiple projects involving Batch ETL through polling data sources, I started working on Streaming ETL. Streaming computation is necessary for use cases where real or near real-time analysis is required. For example, in IT Operations Analytics, it is paramount that Ops get critical alert information in real-time or within acceptable latency (near real-time) to help them mitigate downtime or any errors caused due to misconfiguration.
While there are many introductory articles on Flink (my personal favorite are blogs from Ivan Mushketyk), not many have been into details of streaming ETL and advanced aspects of the Flink framework, which are useful in a production environment.