https://blog.dask.org 2026-03-05T15:05:22.933031+00:00 ABlog https://blog.dask.org/2020/08/31/helm_daskhub/ 2020-08-31T00:00:00+00:00 Tom Augspurger <p>Today we’re announcing the release of the <a class="reference external" href="https://github.com/dask/helm-chart/blob/master/daskhub/README.md"><code class="docutils literal notranslate"><span class="pre">daskhub</span></code></a> helm chart. This is a <a class="reference external" href="https://helm.sh/">Helm</a> chart to easily install <a class="reference external" href="https://jupyter.org/hub">JupyterHub</a> and Dask for multiple users on a Kubernetes Cluster. If you’re managing deployment for many people that needs interactive, scalable computing (say for a class of students, a data science team, or a research lab) then <code class="docutils literal notranslate"><span class="pre">dask/daskhub</span></code> might be right for you.</p> <p>You can install <code class="docutils literal notranslate"><span class="pre">dask/daskhub</span></code> on a Kubernetes cluster today with</p> <div class="highlight-console notranslate"><div class="highlight"><pre><span></span><span class="go">helm repo add dask https://helm.dask.org/</span> <span class="go">helm repo update</span> <span class="go">helm upgrade --install dhub dask/daskhub</span> </pre></div> </div> <aside class="system-message"> <p class="system-message-title">System Message: WARNING/2 (<span class="docutils literal">/opt/build/repo/2020/08/31/helm_daskhub.md</span>, line 26)</p> <p>Document headings start at H2, not H1 [myst.header]</p> </aside> <section id="history"> <p>The <code class="docutils literal notranslate"><span class="pre">dask/daskhub</span></code> helm chart is an evolution of the <a class="reference external" href="http://pangeo.io/">Pangeo</a> helm chart, which came out of that community’s attempts to do big data geoscience on the cloud. We’re very grateful to have years of experience using Dask and JupyterHub together. Pangeo was always aware that there wasn’t anything geoscience-specific to their Helm chart and so were eager to contribute it to Dask to share the maintenance burden. In the process of moving it over to Dask’s chart repository we took the opportunity to clean up a few rough edges.</p> <p>It’s interesting to read the <a class="reference external" href="https://blog.dask.org/2018/01/22/pangeo-2">original announcement</a> of Pangeo’s JupyterHub deployment. A lot has improved, and we hope that this helm chart assists more groups in deploying JupyterHubs capable of scalable computations with Dask.</p> <aside class="system-message"> <p class="system-message-title">System Message: WARNING/2 (<span class="docutils literal">/opt/build/repo/2020/08/31/helm_daskhub.md</span>, line 41)</p> <p>Document headings start at H2, not H1 [myst.header]</p> </aside> </section> <section id="details"> <h1>Details</h1> <p>Internally, the DaskHub helm chart is relatively simple combination of the <a class="reference external" href="https://github.com/jupyterhub/zero-to-jupyterhub-k8s">JupyterHub</a> and <a class="reference external" href="https://github.com/dask/dask-gateway/">Dask Gateway</a> helm charts. The only additional magic is some configuration to</p> <ol class="arabic simple"> <li><p>Register Dask Gateway as a <a class="reference external" href="https://jupyterhub.readthedocs.io/en/stable/reference/services.html">JupyterHub service</a>.</p></li> <li><p>Set environment variables to make using Dask Gateway easy for your users.</p></li> </ol> <p>With the default configuration, your users will be able to create and connect to Dask Clusters, including their dashboards, with a simple</p> <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="kn">from</span><span class="w"> </span><span class="nn">dask_gateway</span><span class="w"> </span><span class="kn">import</span> <span class="n">GatewayCluster</span> <span class="gp">&gt;&gt;&gt; </span><span class="n">cluster</span> <span class="o">=</span> <span class="n">GatewayCluster</span><span class="p">()</span> <span class="gp">&gt;&gt;&gt; </span><span class="n">client</span> <span class="o">=</span> <span class="n">cluster</span><span class="o">.</span><span class="n">get_client</span><span class="p">()</span> </pre></div> </div> <p>Check out the <a class="reference external" href="https://docs.dask.org/en/latest/setup/kubernetes-helm.html">documentation</a> for details and let us know if you run into any difficulties.</p> </section>

Today we’re announcing the release of the daskhub helm chart. This is a Helm chart to easily install JupyterHub and Dask for multiple users on a Kubernetes Cluster. If you’re managing deployment for many people that needs interactive, scalable computing (say for a class of students, a data science team, or a research lab) then dask/daskhub might be right for you.

2020-08-31T00:00:00+00:00