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To help improve performance and security, Data Science & AI Workbench enables you to create a local copy of an online package repository so users can access the packages from a centralized, on-premises location. This copy is called a mirror. A mirror can be complete, partial, or include specific packages or types of packages. The Workbench installer contains a bootstrap executable that you can run to install conda.

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Prerequisites:

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Installing conda

  1. Use one of the following methods to obtain conda for your setup:
    • Gravity
    • BYOK8s
    Open a terminal window and navigate to the directory where you downloaded and extracted the Workbench installer:
    # Replace <VERSION> with your specific version number
cd anaconda-enterprise-<VERSION>
  2. Run the following command to verify the bzip2 package is installed: 
    which bunzip2
    If the command returns a valid package, you can run the bootstrap executable. If not, install the binary by running either yum install bzip2 or apt-get install bzip2.
  3. Make the bootstrap executable by running the following command: 
    ./conda-bootstrap.sh
  4. Type yes when prompted to accept the end user license agreement (EULA).
  5. Accept the default path, or enter an alternate path when prompted.
  6. When prompted, type yes to activate the conda command at shell initialization.
  7. Re-initialize your terminal for the previous steps to take effect: 
    source ~/.bashrc
Now that you’ve installed conda, you can configure access to the source of the packages to be mirrored, whether an online repository or a tarball (if an air-gapped installation). Then you’ll be ready to begin mirroring channels and packages.