title: Custom Machine Types in Python Dataflow SDK
body: <p>According to <a href="https://stackoverflow.com/questions/35606172/is-it-possible-to-use-a-custom-machine-for-dataflow-instances">Is it possible to use a Custom machine for Dataflow instances?</a> you can set the custom machine type for a dataflow operation by specifying the name as <code>custom-&lt;number of cpus&gt;-&lt;memory in mb&gt;</code></p>
  
  <p>But that answer is for the Java Api and the old Dataflow version, not the new Apache Beam implementation and Python.</p>
  
  <p>If I supply <code>--worker_machine_type custom-8-5376</code>in the 2.0.0 google-cloud-dataflow python API, I get the following error:</p>
  
  <blockquote>
    <p>"(4092fe7df5a10577): The workflow could not be created. Please try again in a few minutes. If you are still unable to create a job please contact customer support. Causes: (4092fe7df5a10596): Unable to get machine type information for machine type custom-8-5376 in zone us-central1-f. Please check that machine type and zone are correct."</p>
  </blockquote>
  
  <p>I also tried defining a new instance template in the compute engine and supplying the name of that template in the <code>--worker_machine_type</code> parameter, but that doesn't work, either.</p>
  
  <p>How can you run a workflow on Dataflow 2.0.0 with a custom machine type?</p>