Stream Processing

Compute that reads from your streaming platforms, transforms the data, and writes it back — continuously, at the speed the data arrives.

Platform Status In short
Apache Flink Supported Stateful stream processing: projects hold your code, deployments run it against your Kafka clusters
Kafka Streams BYO runtime A Java library, not a Streamtime-managed platform: your applications run it, Streamtime’s clusters provide the streams

Flink runs through projects: a project holds your application code and builds, and from it you roll out deployments that consume and produce on the Kafka clusters in your organization.

  1. In the sidebar, go to Flink projects and select Create project.
  2. Name the project and select the organization’s source for builds.
  3. Upload or trigger a build, then create a Deployment from the build and start it. The deployment consumes and produces on your Kafka clusters; its status appears in the project view.

Not available in this interface yet.

streamtime flink-project create --identifier orders-enrich
streamtime flink-project upload  orders-enrich <artifact>
streamtime flink create --project orders-enrich --identifier nightly-rollup
streamtime flink list

MCP reads deployment and cluster state; it does not create or start Flink deployments.

Kafka Streams

Kafka Streams is a client library inside your own Java applications — Streamtime does not deploy it. What Streamtime provides is the platform it runs against: the Kafka clusters, their authentication, and the monitoring of the topics Streams applications read and write.