title: Connecting to AMLS workspace with private endpoint using Python SDK and proxy
body: <p>I have created an AMLS workspace with a private endpoint in a vnet that is peered into a company's network. I would like to access the AMLS workspace using a company VM (Windows) to add compute, add datastores, deploy models, etc. using the Azure ML Python SDK.</p>
  <p>The company VM has a proxy in place which initially was blocking my ability to even log in to the AMLS workspace. After adding an HTTPS_PROXY environment variable and configuring the powershell profile for the proxy server, I can now log in to Azure from powershell (<code>az login</code>) and I can access the AMLS workspace using Python (<code>ws = Workspace.get()</code>, <code>ws.get_details()</code>, etc.). However, as soon as I try to access any of the resources (e.g.<code> ws.get_default_datastore()</code>, <code>cluster = ComputeTarget(workspace=ws, name=cluster_name)</code>) I get SSL certificate verification errors:</p>
  <pre><code>requests.exceptions.SSLError: HTTPSConnectionPool(host='&lt;WORKSPACE_ID&gt;.workspace.canadacentral.api.azureml.ms', port=443): Max retries
   exceeded with url: /discovery/workspaces/&lt;WORKSPACE_ID&gt; (Caused by SSLError(SSLCertVerificationError(1,
   '[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:1091)')))
  </code></pre>
  <p>There is a similar problem mentioned here: <a href="https://github.com/Azure/azure-sdk-for-python/issues/1089" rel="nofollow noreferrer">https://github.com/Azure/azure-sdk-for-python/issues/1089</a>, but I'm still unsure how to solve this. What is the best approach here? Should I turn off certificate validation in the Azure ML Python SDK? If so, how?</p>