Legacy engine migration to ML Runtimes

Cloudera recommends using ML Runtimes for all new projects, and recommends the migration of existing engine-based projects to ML Runtimes. Learn about migrating the Cloudera AI workloads from legacy engines to ML Runtimes.

Create the <home-directory>/.cmlutils/import-config.ini file to populate the engine to ML Runtimes mapping. For instructions, see the Import steps.

Run the cmlutil helpers populate_engine_runtimes_mapping command to populate the mapping.

The above command creates the <home-directory>/.cmlutils/legacy_engine_runtime_constants.json file. Make sure that the tool has the necessary write permissions to create or update the file in the <home-directory>/.cmlutils/ folder.
Export the data.

The export command automatically picks up the available <home-directory>/.cmlutils/legacy_engine_runtime_constants.json file and prepares the metadata accordingly.

Import the data.

Run the import command to make sure that the Cloudera AI Workbenches with legacy engines are automatically migrated to ML Runtimes.

The following example is a sample <home-directory>/.cmlutils/legacy_engine_runtime_constants.json file:

   {
    "python3": "docker.repository.cloudera.com/cloudera/cdsw/ml-runtime-workbench-python3.9-standard:2022.11.2-b2",
    "python2": "docker.repository.cloudera.com/cloudera/cdsw/ml-runtime-workbench-python3.9-standard:2022.11.2-b2",
    "r": "docker.repository.cloudera.com/cloudera/cdsw/ml-runtime-workbench-r4.1-standard:2022.11.2-b2",
    "scala": "docker.repository.cloudera.com/cloudera/cdsw/ml-runtime-workbench-scala2.11-standard:2022.11.2-b2",
    "default": "docker.repository.cloudera.com/cloudera/cdsw/ml-runtime-workbench-python3.9-standard:2023.05.2-b7"
   }

Modify the content of the mapping if required.

The mapping in the <home-directory>/.cmlutils/legacy_engine_runtime_constants.json file can be edited to customise the ML Runtimes mapping.