Skip to content

Confluent Platform Demo including Apache Kafka, KSQL, Control Center, Replicator, Confluent Schema Registry, Security

License

Notifications You must be signed in to change notification settings

pgibert/cp-demo

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Kafka Event Streaming Applications

This demo and accompanying playbook show users how to deploy an Apache Kafka® event streaming application using KSQL and Kafka Streams for stream processing. All the components in the Confluent platform have security enabled end-to-end. Run the demo with the playbook.

Table of Contents

Overview

The use case is an event streaming application that processes live edits to real Wikipedia pages. Wikimedia Foundation has IRC channels that publish edits happening to real wiki pages (e.g. #en.wikipedia, #en.wiktionary) in real time. Using Kafka Connect, a Kafka source connector kafka-connect-irc streams raw messages from these IRC channels, and a custom Kafka Connect transform kafka-connect-transform-wikiedit transforms these messages and then the messages are written to a Kafka cluster. This demo uses KSQL and Kafka Streams for data enrichment. Then a Kafka sink connector kafka-connect-elasticsearch streams the data out of Kafka, applying another custom Kafka Connect transform called NullFilter. The data is materialized into Elasticsearch for analysis by Kibana. Use Confluent Control Center for management and monitoring.

image

Documentation

You can find the documentation for running this demo and its accompanying playbook at https://docs.confluent.io/current/tutorials/cp-demo/docs/index.html.

Additional Examples

For additional examples that showcase streaming applications within an event streaming platform, please refer to the examples GitHub repository.

About

Confluent Platform Demo including Apache Kafka, KSQL, Control Center, Replicator, Confluent Schema Registry, Security

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Shell 88.2%
  • Python 11.8%