title: What is the recommended way to upgrade a dataproc cluster?
body: <p>Dataproc seems to be designed to be Stateless / Immutable. Is this assumption correct? Should we just quit right now if we are planning to deploy a Hive/Presto data warehouse?</p>
  
  <p>We are struggling to find any documentation that suggests how one should care for a cluster once has been provisioned?</p>
  
  <ul>
  <li>How to upgrade components?</li>
  <li>How to install tools (e.g. Hue etc) after a cluster was established?</li>
  <li>How to secure access to data + services once deployed?</li>
  </ul>
  
  <p>The <a href="https://cloud.google.com/dataproc/docs/resources/faq" rel="nofollow noreferrer">FAQs</a> "Can I run a persistent cluster?" don't really address this either. </p>
  
  <p>The internet 
  is suggesting we should just create a new cluster if we have a problem. As a developer I'm quite happy with the "Minimize State" argument but I work in the enterprise world that like solutions like Hive (and its metadata store), Hue and Zeppellin and want to connect external tools like Tableau into a cluster.</p>
  
  <p>The documentation should really make it clear which use-cases dataproc excels at (Batch, on-demand &amp; short lived workloads) vs things it isn't really designed for (e.g. OLAP)? </p>