A summary of IBM Event Automation in under 200 words.
Last week was the first release of IBM Event Automation. I’ve been asked what it’s all about, so I thought it’d be helpful to have a brief summary to point people at.
IBM Event Automation is a collection of three components, designed to help companies be productive in creating event-driven solutions.
The three components are:
Event Processing
Low-code authoring tool for building stream processing flows.
Create stateful event processing operations that aggregate events within a time window, and correlate events between multiple streams of events.
Based on Apache Flink
For more info see our guided tutorials for creating your first flows.
Event Endpoint Management
Event management tool for creating a self-service catalog of event sources for users to securely browse and utilize.
Promote the sharing and reuse of event sources while maintaining control and governance, and bring the discipline of API management to the world of event streaming.
Based on an API portal of Kafka topics described as AsyncAPI documents
For more info see my blog post on the idea of event endpoint management.
Event Streams
Manage your Apache Kafka deployments, balance your event workloads, browse messages, and monitor key metrics in a simple user experience.
This is Apache Kafka, plus supporting tooling and other components needed when running Kafka in production, such as a schema registry for your Avro schemas.
Based on Apache Kafka and Apicurio
For more info see my blog post on the first Operator release of Event Streams.
Tags: apachekafka, eventstreams, flink, ibmeventstreams, kafka