title: Trying Dask on AWS
body: <p>I am a scientist who is exploring the use of Dask on Amazon Web Services. I have some experience with Dask, but none with AWS.  I have a few large custom task graphs to execute, and a few colleagues who may want to do the same if I can show them how.  I believe that I should be using <a href="https://dask.pydata.org/en/latest/setup/kubernetes-helm.html" rel="nofollow noreferrer">Kubernetes with Helm</a> because I fall into the <a href="https://dask.pydata.org/en/latest/setup/kubernetes.html" rel="nofollow noreferrer">"Try out Dask for the first time on a cloud-based system like Amazon, Google, or Microsoft Azure"</a> category.</p>
  
  <ol>
  <li>I also fall into the "Dynamically create a personal and ephemeral deployment for interactive use" category.  Should I be trying native Dask-Kubernetes instead of Helm?  It seems simpler, but it's hard to judge the trade-offs.</li>
  <li>In either case, how do you provide Dask workers a uniform environment that includes your own Python packages (not on any package index)?  <a href="https://dask.pydata.org/en/latest/setup/docker.html" rel="nofollow noreferrer">The solution I've found</a> suggests that packages need to be on a <code>pip</code> or <code>conda</code> index.</li>
  </ol>
  
  <p>Thanks for any help!</p>