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Setting up the Compute Targets

Prerequisites

To run through this workshop, you will need an Azure subscription and an Azure ML workspace. See instructions on how to create a workspace here and make sure to select Enterprise edition.

⭐ If you want to have this workshop go smooth, then:

  • Name your AzureML workspace aml-workshop
  • Name the resource group of the workshop aml-workshop

Navigate to https://ml.azure.com/ and select your newly created workspace.

Creating an AzureML compute cluster

We will do a number of actions that require a compute target to be exectuted on. We will start by creating a cluster of CPU VMs.

  1. Navigate to Compute > Training Clusters in the Manage section and click New.

  2. Call the cluster cpu-cluster.

    • For machine size choose Standard_D2_v2 (that is an inexpensive general purpose VM size at about $0.11/hour in eastus2).
    • Set the Minimum number of nodes to 0 and the the Maximum number of nodes to 4. That way the cluster will scale automatically to up to 4 nodes as jobs require them.
    • Set the Idle seconds before scale down to 10800. That means that nodes will be kept around for 3 hours before they are spun down. That way, during our workshop, jobs won't have to wait for spin-up. Make sure that number is lower if you are using a more expensive VM size.

Creating an AzureML Compute Instance

Next, we will create an Compute Instance. The Compute Instance will serve as an interactive workstation in the cloud that serves as a Jupyter server, but also hosts and instance of RStudio server and can run TensorBoard, Bokeh, Shiny or other apps used during the developement work of a Data Scientist.

  1. Navigate to Compute Instances tab in the Compute section and click on New.

  2. Choose some sufficiently unique name, keep the default VM type (STANDARD_D3_V2 - a fairly inexpensive machine type costing about $0.22/hour in eastus2) and click Create:

⭐ Use an unique name for the compute instance, as it needs to be globally unique.

See here for details on creating Compute Instances.

Note that this machine will keep running until you stop it!