Confluent Platform Demo (cp-demo)

The cp-demo example builds a full Confluent Platform deployment with an Apache Kafka® event streaming application using ksqlDB and Kafka Streams for stream processing, and all the components have security enabled end-to-end. The tutorial includes a module to extend it into a hybrid deployment that runs Replicator to copy data from a local on-prem Kafka cluster to Confluent Cloud, a fully-managed service for Apache Kafka®. Follow the accompanying guided tutorial, broken down step-by-step, to learn how Kafka and Confluent Cloud work with Connect, Confluent Schema Registry, Confluent Control Center, Replicator, and security enabled end-to-end.


Use Case

The use case is an Apache Kafka® event streaming application that processes real-time edits to real Wikipedia pages.


The full event streaming platform based on Confluent Platform is described as follows. Wikimedia’s EventStreams publishes a continuous stream of real-time edits happening to real wiki pages. A Kafka source connector kafka-connect-sse streams the server-sent events (SSE) from, and a custom Connect transform kafka-connect-json-schema extracts the JSON from these messages and then are written to a Kafka cluster. This example uses ksqlDB and a Kafka Streams application for data processing. Then a Kafka sink connector kafka-connect-elasticsearch streams the data out of Kafka and is materialized into Elasticsearch for analysis by Kibana. Confluent Replicator is also copying messages from a topic to another topic in the same cluster. All data is using Confluent Schema Registry and Avro, and Confluent Control Center is managing and monitoring the deployment.

Data Pattern

Data pattern is as follows:

Components Consumes From Produces To
SSE source connector Wikipedia wikipedia.parsed
ksqlDB wikipedia.parsed ksqlDB streams and tables
Kafka Streams application wikipedia.parsed wikipedia.parsed.count-by-domain
Confluent Replicator wikipedia.parsed wikipedia.parsed.replica
Elasticsearch sink connector WIKIPEDIABOT (from ksqlDB) Elasticsearch/Kibana

How to use this tutorial

We suggest following the cp-demo tutorial in order:

  1. Module 1: On-Prem Tutorial: bring up the on-prem Kafka cluster and explore the different technical areas of Confluent Platform
  2. Module 2: Hybrid Deployment to Confluent Cloud Tutorial: run Replicator to copy data from a local on-prem Kafka cluster to Confluent Cloud, and use the Metrics API to monitor both
  3. Teardown: clean up your on-prem and Confluent Cloud environment