Scaling Limits (CE)

Our free HPE Machine Learning Data Management Community Edition contains built-in scaling limitations and parallelism thresholds. To scale beyond these limits, request a Enterprise trial token and enjoy unlimited scaling, and more.


You might qualify for a free Enterprise license.

HPE Machine Learning Data Management offers activation keys for proofs-of-concept, startups, academic, nonprofit, or open-source projects. Tell us about your project!.

Scaling Limits

Number of concurrent pipelines deployed Number of workers for each pipeline
Community Users can deploy up to 16 pipelines. Community Users can run up to 8 workers in parallel on each pipeline.

What happens when you exceed those limits?

As a general rule, HPE Machine Learning Data Management provides an error message in the STDERR whenever a limit is encountered that prevents you from successfully running a command. In that case, the alert message links to a free trial request form.

Limit on the number of pipelines

When exceeding the number of pipelines:

  • pachctl create pipeline fails once the maximum number of pipelines is reached.

  • pachctl update pipeline and pachctl edit pipeline succeed on existing pipelines, fail when attempting to create pipelines beyond the limit.

    If update pipeline fails for any other reason, it does not log any message related to pipeline limits.

All of the commands listed above create a distinct message to STDERR and to the pachd logs. This message includes information such as the limit on the number of pipelines in the Community Edition, the total number of pipelines deployed, and provides a link to request an Enterprise key to lift those limitations.

  • all other list, run, start, stop pipeline commands’ behavior remains unchanged.

Limit on the number of workers per pipeline

When constant parallelism > 8:

  • pachctl create pipeline and pachctl update pipeline fail. A message to STDERR and pachd logs is generated. You will need to update your pipeline specification file accordingly or activate an Enterprise license.

What happens when your license expires?

If your Enterprise License has expired and you have more than 16 pipelines, all existing pipelines continue to work. However, you will not be able to create additional pipelines. Same behavior if you upgrade your cluster.

Restoring or installing HPE Machine Learning Data Management with an expired license will fail.
Pipelines automatically generated by the system (for example cron…) are not considered when assessing the total number of pipelines deployed. The limit applies to user-created pipelines only.