Event Endpoint Management continues to be enhanced

Event Endpoint Management continues to be available and enhanced as part of IBM's integration platforms.

End of Marketing announcement for IBM Event Automation

Event Streams and Event Processing are deprecated and no enhancements will be provided. Support and security fixes will be provided in line with published support lifecycle policies. Future event-driven solutions that make use of Apache Kafka and Apache Flink will be delivered by IBM Confluent.

For more information, see the support lifecycle transition and software ordering completion announcement.

Introduction to authoring

The Event Processing authoring UI is a space to explore ideas and prove hypotheses, providing a rapid feedback loop. You can export authored flows for deployment into other more resilient environments.

When to use the UI

You can use the authoring UI for the following purposes:

  • Developing and testing ideas.
  • Testing resiliency with longer duration tests, where you can evaluate qualities of a long-running flow such as:
    • Consumer lag: does the flow have bottlenecks that are causing the source nodes to struggle to keep up?
    • Watermark progression: are new events progressing a source watermark so that temporal operations can function?
    • Checkpoint progression: can the flow checkpoint the state (store the sequence of events) for fault tolerance while keeping up under a given load?
  • Creating applications that are not mission critical. For example, applications that can be stopped and restarted, and so miss some messages or read them twice, without that being a problem.

When to export a job from the UI

Many applications reach a point where they are better managed outside of the authoring environment. Consider exporting a job from the UI in the following situations:

  • You have a development, test, staging, or production pipeline, and it is time to move to the test environment.
  • Your job must keep running across a change in the version of Flink (for example, across multiple Event Processing releases).
  • Your job is consuming a lot of memory or disk, or requires a different state backend. In general, it requires a higher quality of service than those offered in the shared authoring environment.
  • Your flow must be isolated so that other flows cannot impact it negatively.

If one or more of these conditions are true, consider deploying that flow as a customized job.

Note: Other deployment methods are also available for development and testing purposes: by using the Flink SQL client and by using the Apache SQL Runner sample. However, for production deployments that require full control and customization, deploy your flow as a customized job.