Deploying and operating the Stream service
The Stream service enables asynchronous flow of data between processes in Pega Platform. The Stream service is a multinode component that is based on Apache Kafka.
You can use this service, for example, to pass correspondence data to delivery channels in Pega Marketing, process customer responses for the Adaptive Decision Manager (ADM), or initiate background processes in any Pega application.
The Stream service ingests, routes, and delivers high volumes of low-latency data such as web clicks, transactions, sensor data, work objects, data pages, and customer interaction history. As a resiliency mechanism for operations, the same data is replicated to other nodes in the cluster.
The Stream service is built on the Apache Kafka platform. To better understand Kafka-related terminology, see the Apache Kafka documentation.
To successfully deploy and operate the Stream service, follow the guidelines provided in these topics:
- Configuring the Stream service
Configure the Stream service to ingest, route, and deliver high volumes of data such as web clicks, transactions, sensor data, and customer interaction history.
- Monitoring the Stream service
Ensure that your Stream service operates without causing any errors by regularly monitoring the status of your Stream nodes, partitions, disk space, CPU usage, and database availability.
- Operating the Stream service
Learn how to do a rolling and full restart of your Stream service, to manually scale up and scale down the service, and to recover the service after a failure.
- Understanding pr_data_stream_* tables
Identify health issues with your Stream service by reviewing the data tables that provide information about Kafka sessions and clusters.