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1. Quick Start

The objective is to configure your client environment (your laptop, CLI shell, Notebook or other environments) to talk to Infinstor MLFlow server. Use the steps below:

  1. Infinstor MLflow server configuration:
    • for the free MLflow service, use the following
    • for the SaaS version purchased from the AWS Marketplace, use the following
    • for the special SaaS version provided to certain users (we would have let you know this), use the following
    • for Enterprise version (single tenant version), please contact your administrator for the above configuration details.
  2. Install infinstor-mlflow-plugin
  3. Configure environment variable MLFLOW_TRACKING_URI
  4. Obtain a token file for authentication
  5. Configure MLFLOW_EXPERIMENT_ID environment variable
  6. Use MLflow cli or run python code with MLflow python api calls.
  7. Use MLflow UI to view the MLflow runs under the above MLflow experiment

1.1. Install infinstor-mlflow-plugin

  • pip install --upgrade infinstor-mlflow-plugin
    • Installs infinstor-mlflow-plugin in your client environment

1.2. Configure MLFLOW_TRACKING_URI environment variable

InfinStor MLflow backend is activated by setting the environment variable MLFLOW_TRACKING_URI to the value provided by your administrator. See configuration details above for details. Example

> export MLFLOW_TRACKING_URI=<admin_provided_tracking_uri>

1.3. Obtain a Token file for authentication

Use these steps to obtain and place the token file in the right location.

1.4. Configure MLFLOW_EXPERIMENT_ID environment variable

The environment variable MLFLOW_EXPERIMENT_ID must be set in order to record runs in the correct experiment ID. If this environment variable is not set, then runs will be recorded to the default experiment id 0. This is particularly important when Authorization is enabled, because the user may not have access to experiment id 0. The following example sets the experiment id to 7


1.5. Use MLFlow cli or MLFlow python api to use MLFlow

Use MLflow cli or MLflow python api calls to communicate with the Infinstor MLFlow server

1.6. MLflow UI

The MLflow UI is available at the URL provided by your administrator. See configuration details above for details. Use the MLflow UI to see the tracked MLflow experiments and MLflow runs.