Single Data Science VM

This project demonstrates launching the Microsoft Azure Data Science VM as a standalone node. The Data Science VM may be used as the base image in most CycleCloud clusters.

License

To use the Microsoft DataScience VM, you must first accept the license agreement. The simplest way to do so is to run the following Azure CLI commands:

    az vm image accept-terms --publisher microsoft-ads --offer linux-data-science-vm --plan linuxdsvm
    az vm image accept-terms --publisher microsoft-ads --offer linux-data-science-vm-ubuntu --plan linuxdsvmubuntu
    az vm image accept-terms --publisher microsoft-ads --offer windows-data-science-vm --plan windows2016

Pre-Requisites

This sample requires the following:

1. CycleCloud must be installed and running.

   a. If this is not the case, see the CycleCloud QuickStart Guide for assistance.

2. The CycleCloud CLI must be installed and configured for use.

3. You must have access to log in to CycleCloud.

4. You must have access to upload data and launch instances in your chosen Cloud Provider account.

5. You must have access to a configured CycleCloud "Locker" for Project Storage (Cluster-Init and Chef).

6. Optional: To use the cyclecloud project upload <locker> command, you must have a Pogo configuration file set up with write-access to your locker.

   a. You may use your preferred tool to interact with your storage "Locker" instead.

Configuring the Project

The first step is to configure the project for use with your storage locker:

1. Open a terminal session with the CycleCloud CLI enabled.

2. Switch to the data-science-vm project directory.

Deploying the Project

To upload the project (including any local changes) to your target locker, run the cyclecloud project upload command from the project directory. The expected output looks like this:

   $ cyclecloud project upload my_locker
   Sync completed!

IMPORTANT

For the upload to succeed, you must have a valid Pogo configuration for your target Locker.

Importing the Cluster Template

To import the cluster:

1. Open a terminal session with the CycleCloud CLI enabled.

2. Switch to the data-science-vm project directory.

3. Run cyclecloud import_template Data-Science-VM -f templates/data-science-vm.txt. The expected output looks like this:

   
   $ cyclecloud import_template Data-Science-VM -f templates/data-science-vm.txt --force
   Importing template Data-Science-VM....
   ----------------------------
   Data-Science-VM : *template*
   ----------------------------
   Keypair:
   Cluster nodes:
   dsvm: off
   Total nodes: 1
   

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.