Understand the use case

As a basic analytical use case, you can use Streaming Analytics clusters connected to the Streams Messaging cluster to build an end-to-end streaming analytics application with Kafka as source and sink.

When choosing Kafka as a connector for a Flink application, you can create a scalable communication channel. Kafka, as a source and sink, is responsible for delivering input records to Flink, and receiving the transformed data from Flink.

This use case details the steps to connect a Streaming Analytics cluster with a Streams Messaging cluster, and to submit your Flink jobs and monitor the correct behaviour of your application in the Data Hub environment. The Stateful Flink Application Tutorial is used as an example to guide you through the basic steps to analyze your data with Kafka in CPD Public Cloud.

The Stateful Flink Application Tutorial details an inventory use case for an e-commerce site. The business logic in the application includes handling transactions and managing queries that are later summarized to monitor the state of the inventory.