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<title>Installing JupyterHub with Kubernetes on bare metal virtual machines</title>
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<body class="article">
<div id="header">
<h1>Installing JupyterHub with Kubernetes on bare metal virtual machines</h1>
<div class="details">
<span id="author" class="author">Evert Rol</span><br>
<span id="email" class="email"><a href="mailto:e.rol@esciencecenter.nl">e.rol@esciencecenter.nl</a></span><br>
<span id="revnumber">version 1.0,</span>
<span id="revdate">2019-04-15</span>
</div>
<div id="toc" class="toc">
<div id="toctitle">Table of Contents</div>
<ul class="sectlevel1">
<li><a href="#_background">Background</a>
<ul class="sectlevel2">
<li><a href="#_current_setup">Current setup</a></li>
<li><a href="#_scaling">Scaling</a></li>
</ul>
</li>
<li><a href="#_installing_kubernetes">Installing Kubernetes</a>
<ul class="sectlevel2">
<li><a href="#_tools">Tools</a></li>
<li><a href="#_set_up_an_initial_cluster">Set up an initial cluster</a></li>
<li><a href="#_installing_docker_and_kubernetes_packages">Installing Docker and Kubernetes packages</a></li>
<li><a href="#_set_up_kubernetes">Set up Kubernetes</a></li>
<li><a href="#_calico">Calico</a></li>
</ul>
</li>
<li><a href="#_storage_space_for_pods">Storage space for pods</a></li>
<li><a href="#_setting_up_helm_and_tiller">Setting up Helm and Tiller</a></li>
<li><a href="#_installing_jupyterhub">Installing JupyterHub</a></li>
<li><a href="#_configuring_nginx_as_a_reverse_proxy">Configuring Nginx as a reverse proxy</a></li>
<li><a href="#_trying_it_out">Trying it out</a></li>
<li><a href="#_final_remarks">Final remarks</a>
<ul class="sectlevel2">
<li><a href="#_to_do">To do</a></li>
<li><a href="#_notes_about_potential_problems">Notes about potential problems</a></li>
</ul>
</li>
<li><a href="#_resources">Resources</a></li>
</ul>
</div>
</div>
<div id="content">
<div class="sect1">
<h2 id="_background">Background</h2>
<div class="sectionbody">
<div class="paragraph">
<p>The background setup is within a European climate research project; we want to provide climate scientist a place where they can perform their analyses in the cloud.
This has two goals:</p>
</div>
<div class="olist arabic">
<ol class="arabic">
<li>
<p>Provide a large amount of data next to the analysis environment, so that people do not have to download data to their local machine: the data can stay put in one place, and will not need to be manually copied multiple times.</p>
</li>
<li>
<p>Provide a setup where scientist can create <strong>reproducible</strong> analyses, with annotated and clean code, and versioned data and code.</p>
</li>
</ol>
</div>
<div class="paragraph">
<p>We have opted for Jupyter notebooks, since</p>
</div>
<div class="ulist">
<ul>
<li>
<p>these are more and more commonplace</p>
</li>
<li>
<p>they are relatively straightforward to rerun by other people.
Also, various websites allow them to be viewed, including the results (that is, the output, including figures), without having to rerun the code.
This makes it easy to point other scientist directly to a notebook to see how the analysis was done exactly.</p>
</li>
<li>
<p>notebooks allow for the use of multiple languages, making the transition for some people easier (Python will be the main language used, but people used to, for example, R, can use the notebook environment just as well</p>
</li>
</ul>
</div>
<div class="paragraph">
<p>In fact, we will not use the standard notebook setup, but the newer Jupyter Lab environment, which also provides a terminal.
This allows even more options to transition from scripts and, for example, Fortran programs, to a more standardised (Python) notebook.</p>
</div>
<div class="paragraph">
<p>The goal is to provide this Jupyter Lab setup through a Jupyter Hub in a cloud environment, with up to 100 TB parked directly next to it.
Scientists can log in, write and fire up their analysis script, and let it crunch through all the necessary data.</p>
</div>
<div class="sect2">
<h3 id="_current_setup">Current setup</h3>
<div class="paragraph">
<p>We use the SURFSara <a href="https://userinfo.surfsara.nl/systems/hpc-cloud">high-performance computing cloud (HPC Cloud) facility</a>.
This uses OpenNebula to orchestrate itself.
We have a virtual machine (VM) running in this cloud, with a JupyterHub.
Next to the VM, we have currently 40 TB of data storage, in the form of <a href="https://ceph.com/">Ceph storage</a>, which holds the necessary scientific data.
On the same VM, we run a data server that provides a (web) interface to the data on Ceph.</p>
</div>
<div class="paragraph">
<p>Users also have a standard home directory on the VM itself, and can access this through <code>ssh</code> if so wanted.
The preferred method is the JupyterLab interface, which provides more installed scientific software in its Docker container.
Inside JupyterLab, there are two "exit" points out of the container: one to the data directory, and one to the users (<code>/home</code>) directory on the VM.
Thus, from with the JupyterHub/Lab, the data can be accessed either with a URL, or if so wanted, with a file path.
Users can also more easily share files through a simply <code>cp</code> from another users home directory (though using a file upload to a cloud service, for example something as simple as a git repository, would be the more natural way inside a JupyterHub. Again, this is done to ease the transition for scientists used to working on local systems).</p>
</div>
</div>
<div class="sect2">
<h3 id="_scaling">Scaling</h3>
<div class="paragraph">
<p>There is one problem with the above setup: it doesn’t scale very well.
At the moment, the VM has access to eight CPU cores.
If, at some point, multiple scientists want to run some intensive analysis on the data, they may stress out all the cores, and things will slow down.
Ideally, the VM should scale with the activity on it, but this would require bringing down the VM, and starting a new VM with extra CPU cores.
This, obviously, doesn’t work: currently running processes are lost, and there is extra downtime, with all the inconveniences.
Yes, the SURFSara HPC Cloud info page (linked above) does mention "Dynamically scalable HPC on the cloud", but as far as I can tell, this means you can choose your favourite VM with regards to cores and memory; it does not involve scaling a live VM.</p>
</div>
<div class="paragraph">
<p>Hence, I have been looking at Kubernetes, which appears to be somewhat the de facto setup for scaling a cloud environment.
Unfortunately, Kubernetes is not installed on the HPC Cloud facility.
Below is my attempt and guide at installing Kubernetes on the SURFSara HPC Cloud facility, and the JupyterHub on top of that (including access to permanent user home directories and a Ceph disk with 100 TB of data).</p>
</div>
<div class="paragraph">
<p>(There is another option: let each scientist start their own VM when needed.
This would require a less common setup, where scientists have to learn to handle the HPC Cloud.
While a default VM for climate scientist can be created (just like a Docker container), all in all, I feel this creates to many barriers for use.)</p>
</div>
</div>
</div>
</div>
<div class="sect1">
<h2 id="_installing_kubernetes">Installing Kubernetes</h2>
<div class="sectionbody">
<div class="sect2">
<h3 id="_tools">Tools</h3>
<div class="paragraph">
<p>The tool for setting up the bare VMs with the necessary software is <a href="https://www.ansible.com/">Ansible</a>.</p>
</div>
</div>
<div class="sect2">
<h3 id="_set_up_an_initial_cluster">Set up an initial cluster</h3>
<div class="paragraph">
<p>I have started with three VMs, all based on the default Ubuntu 18.04.02 Long Term Service (LTS) (code-named Bionic Beaver, or simply Bionic, which is used from hereon).
These are all two cores and 3 GB memory.
One will serve as a controller, and the other two nodes are the workers.
All Kubernetes pods will be running on the workers, nothing on the controller.
A standard VM is set up such that my public key will be installed in the <code>ubuntu</code> administrator account, so I have passwordless access into that account, and from there I can install anything with <code>sudo</code>.
The default VM has ports 22 (ssh) inbound and ports 53 (dns), 67 and 68 (dhcp) open to the outside world; all other ports are blocked by default.</p>
</div>
<div class="sect3">
<h4 id="_hostname">Hostname</h4>
<div class="paragraph">
<p>If your VM system does as mine does, then every node will have the same hostname (named partly after the OS: <code>packer-Ubuntu-18</code>).
This is going to cause problems with Kubernetes, at least in my experience.
I have changed the hostnames on each node (simply to <code>node0</code>, <code>node1</code> etc), and altered the <code>/etc/hosts</code> accordingly:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>export hostname=node0
sed -i.bck -E 's/^127\.0\.1\.1..*(packer\-Ubuntu\-[[:digit:]][[:digit:]]*)$/127.0.1.1 \1-Server node0/' /etc/hosts
sed -i.bck -E 's/^127\.0\.0\.1\s\s*(packer\-Ubuntu\-[[:digit:]][[:digit:]]*)$/127.0.0.1 node0/' /etc/hosts</code></pre>
</div>
</div>
</div>
</div>
<div class="sect2">
<h3 id="_installing_docker_and_kubernetes_packages">Installing Docker and Kubernetes packages</h3>
<div class="paragraph">
<p>There is no officially supported Kubernetes package for Bionic yet: this installation uses the 16.04 (Xenial) version, which so far, works fine on Bionic.
I have opted to install Kubernetes version 1.13.5, even though 1.14.0 is just out.
This had one slightly unfortunate side effect: the Docker package in Ubuntu seems to have gotten updated, and Kubernetes will complain the standard package is a non-supported version.
Thus, I had to add both the Kubernetes and Docker Ubuntu repositories to the Ubuntu package manager.</p>
</div>
<div class="paragraph">
<p>First update apt:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>apt update</code></pre>
</div>
</div>
<div class="paragraph">
<p>If your version of apt is less than 1.5, you need to install the <code>apt-transport-https</code> package (for details, see <a href="https://whydoesaptnotusehttps.com/" class="bare">https://whydoesaptnotusehttps.com/</a>):</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>apt install apt-transport-https</code></pre>
</div>
</div>
<div class="paragraph">
<p>On Bionic, the version of apt is 1.6, so there is no need for this.</p>
</div>
<div class="paragraph">
<p>Next, get the keys for Google’s and Docker’s package repositories and add them to apt:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add -
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | apt-key add -</code></pre>
</div>
</div>
<div class="paragraph">
<p>Add the repositories to the list of apt repositories:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>cat > /etc/apt/sources.list.d/docker.list <<EOF
deb http://download.docker.com/linux/ubuntu xenial stable
EOF
cat > /etc/apt/sources.list.d/kubernetes.list <<EOF
deb http://apt.kubernetes.io/ kubernetes-xenial main
EOF
apt update</code></pre>
</div>
</div>
<div class="paragraph">
<p>(That is, any file with valid repository entry in <code>/etc/apt/sources.list.d/</code> will be picked up and its contents added to the apt repositories.)</p>
</div>
<div class="sect3">
<h4 id="_install_docker">Install Docker</h4>
<div class="paragraph">
<p>Install docker (nowadays, the package is called <code>docker-ce</code>. Don’t use <code>docker.io</code>, <code>docker-engine</code> or other variants.):</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo apt install docker-ce=18.06.3~ce~3-0~ubuntu</code></pre>
</div>
</div>
</div>
<div class="sect3">
<h4 id="_extra_disk_space_for_docker_images">Extra disk space for Docker images</h4>
<div class="paragraph">
<p>Here, I had to take an extra step: the disk images of the VMs are not large enough to store all the images that Docker pulls from its repository.
Hence, I had to point the Docker system directory elsewhere, as follows:</p>
</div>
<div class="paragraph">
<p>Stop Docker:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo systemctl stop docker</code></pre>
</div>
</div>
<div class="paragraph">
<p>Create a <code>/etc/docker/daemon.json</code> with a single entry:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo cat > /etc/docker/daemon.json <<EOF
{
"graph":"/mnt/data/docker"
}
EOF</code></pre>
</div>
</div>
<div class="paragraph">
<p>That will point Docker to look in the <code>/mnt/data/docker</code> directory. Docker will ensure the subdirectory is made, you just have to make sure the mount point <code>/mnt/data</code> is correct.
If you need this extra space at all, of course: my VM disk sizes are 10 GB, and a single Jupyter datascience notebook Docker image is already some 6.22 GB.</p>
</div>
<div class="paragraph">
<p>Now, restart Docker and verify it’s running correctly:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo systemctl start docker
systemctl status docker
sudo ls /mnt/data/docker</code></pre>
</div>
</div>
</div>
<div class="sect3">
<h4 id="_kubernetes_package_installation">Kubernetes package installation</h4>
<div class="paragraph">
<p>Kubernetes is a straightforward install:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo apt install kubeadm=1.13.5-00 kubelet=1.13.5-00 kubectl=1.13.5-00</code></pre>
</div>
</div>
</div>
</div>
<div class="sect2">
<h3 id="_set_up_kubernetes">Set up Kubernetes</h3>
<div class="paragraph">
<p>On the controller node, you’ll need to open some ports.
The following steps need only to be done on your controller node, thus, ssh into your controller.
I use ufw, install it with <code>sudo apt install ufw</code> if it’s not there (ufw is the abbreviation of uncomplicated firewall, and is a frontend for <code>iptables</code>).
I restrict the access to the necessary Kubernetes ports to hosts within the cloud network, which has (roughly) the subnet of <code>145.100.56.0/22</code>:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo ufw allow proto tcp from 145.100.56.0/22 to any port 6443,2379,2380,10250,10251,10252
sudo ufw status</code></pre>
</div>
</div>
<div class="paragraph">
<p>Now, initialise the cluster at your controller:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo kubeadm init --pod-network-cidr {{ 192.168.64.0/18 }} --service-cidr {{ 192.168.0.0/18 }}</code></pre>
</div>
</div>
<div class="admonitionblock note">
<table>
<tr>
<td class="icon">
<div class="title">Note</div>
</td>
<td class="content">
I specify both the pod network Classless Inter-Domain Routing (CIDR), and that of the services.
Most guides and examples only specify the <code>--pod-network-cidr</code> option.
I also do not use the standard <code>10.244.0.0/16</code> for the pod network, given in most examples.
The reason for this is that there is an internal network in the HPC Cloud that falls close to, if not overlaps with, this subnet.
I want to avoid any clashes between these networks, hence I’m using a different network, both for the pods and the services.
As an extra, in the near future, I hope to be able to use the internal network addresses as external IPs within the Kubernetes cluster.
That way, the outward facing public IPs (the ones in the <code>145.100.0.0/22</code> range) will only have the <code>ssh</code> port open.
.
The disadvantage, from what I have figured so far, is that this limits the number of setups, in particular the network fabric options.
Flannel, a popular option for this, is preconfigured to use the default subnets.
Until I can figure out if I can and how to adjust Flannel, I can’t use it.
</td>
</tr>
</table>
</div>
<div class="paragraph">
<p>With the Kubernetes controller now running, we can copy the config to a non-root account.
I’m using the standard <code>ubuntu</code> account, which, as an admin account, is nearly not as good as a dedicated Kubernetes account, but it works for now.</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>mkdir $HOME/.kube
sudo cp /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown ubuntu:ubuntu $HOME/.kube/config</code></pre>
</div>
</div>
<div class="admonitionblock note">
<table>
<tr>
<td class="icon">
<div class="title">Note</div>
</td>
<td class="content">
if you want to reset the actions of <code>kubeadm</code>, then use <code>kubeadm reset</code>.
This also works on the nodes after joining the Kubernetes network.
</td>
</tr>
</table>
</div>
<div class="admonitionblock tip">
<table>
<tr>
<td class="icon">
<div class="title">Tip</div>
</td>
<td class="content">
<div class="paragraph">
<p>if you have <code>kubectl</code> installed on your local machine (desktop, laptop), you can copy the configuration file to your <code>$HOME/.kube/config</code> file there, and run all the kubectl commands from there: no need for sudo, no need to ssh into the controller!</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code># From local machine
scp controller:.kube/config ~/.kube/config</code></pre>
</div>
</div>
<div class="paragraph">
<p>This assumes an entry like</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>host controller
HostName 145.100.x.y
IdentityFile ~/.ssh/id_rsa
User ubuntu</code></pre>
</div>
</div>
<div class="paragraph">
<p>in your <code>~/.ssh/config</code> file on your local machine.</p>
</div>
<div class="paragraph">
<p>Ensure your control machine has proper access to your controller node, with regards to the firewall settings.
The simplest way is to get its IP and on the controller, open the firewall for that machine:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo ufw allow from <control-machine-ip></code></pre>
</div>
</div>
<div class="paragraph">
<p>or if you want to be more restrictive:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo ufw allow from <control-machine-ip> to any \
port 6443,2379,2380,10250,10251,10252</code></pre>
</div>
</div>
</td>
</tr>
</table>
</div>
<div class="sect3">
<h4 id="_hooking_up_the_workers">Hooking up the workers</h4>
<div class="paragraph">
<p>First, print the command necessary to join the controller (on your controller): this will contain some security tokens:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>kubeadm token create --print-join-command</code></pre>
</div>
</div>
<div class="paragraph">
<p>This will output a line like (no need for <code>sudo</code> here):</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>kubeadm join 145.100.x.y:6443 --token gmdirx.udxjw6amqtp2soq0 --discovery-token-ca-cert-hash sha256:6ee755599276cfd015eb005e395e0d26a6fccbabf30600f0ecb15f5675620634</code></pre>
</div>
</div>
<div class="paragraph">
<p>Copy this line, ssh into a worker, and execute this in the worker:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo kubeadm join 145.100.57.220:6443 --token dmgurz.udxjw5masft2soq0 --discovery-token-ca-cert-hash sha256:d015eb005e395e0d26a6fccbabf30600f0ecb15f56756206346ee755599276cf</code></pre>
</div>
</div>
</div>
</div>
<div class="sect2">
<h3 id="_calico">Calico</h3>
<div class="paragraph">
<p>Since I am using Calico for the pod network, I also need to enable port 179 (Border Gateway Protocol, bgp):</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>sudo ufw allow proto tcp from 145.100.56.0/22 to any port 179
sudo ufw status</code></pre>
</div>
</div>
<div class="paragraph">
<p>Of course, Calico also needs to be installed.
And the value of <code>CALICO_IPV4POOL_CIDR</code> in its configuration file needs to be changed to match the pod network used above.</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>curl -O https://docs.projectcalico.org/v3.6/getting-started/kubernetes/installation/hosted/kubernetes-datastore/calico-networking/1.7/calico.yaml
sed -i.bck 's#192\\.168\\.0\\.0/16#192.168.64.0/18#' calico.yaml
kubectl apply -f calico.yaml</code></pre>
</div>
</div>
<div class="paragraph">
<p>(The comments in the calico.yaml mention <code>--cluster-cidr</code> instead of <code>--pod-network-cidr.
This is because `kubeadm</code> is a front-end for other tools that use <code>--cluster-cidr</code>.
If you explicitly want to see the <code>cluster-cidr</code>, use</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>kubectl cluster-info dump | grep cluster-cidr</code></pre>
</div>
</div>
<div class="paragraph">
<p>Now that Calico is installed and the workers are connected to the controller, you should be able to see the pods up and running (give it a minute before everything runs fully):</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>$ kubectl get pods --all-namespaces --output wide
NAMESPACE NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
kube-system calico-kube-controllers-55df754b5d-rj687 1/1 Running 0 84m 192.168.75.2 node2 <none> <none>
kube-system calico-node-cz5rw 1/1 Running 0 84m 145.100.57.36 node1 <none> <none>
kube-system calico-node-fcqwm 1/1 Running 0 84m 145.100.57.38 node2 <none> <none>
kube-system calico-node-jjjtp 1/1 Running 0 84m 145.100.57.33 controller <none> <none>
kube-system coredns-86c58d9df4-6hj4w 1/1 Running 0 84m 192.168.75.1 node2 <none> <none>
kube-system coredns-86c58d9df4-m7hsg 1/1 Running 0 84m 192.168.75.3 node2 <none> <none>
kube-system etcd-controller 1/1 Running 0 83m 145.100.57.33 controller <none> <none>
kube-system kube-apiserver-controller 1/1 Running 0 83m 145.100.57.33 controller <none> <none>
kube-system kube-controller-manager-controller 1/1 Running 0 83m 145.100.57.33 controller <none> <none>
kube-system kube-proxy-9dckf 1/1 Running 0 84m 145.100.57.38 node2 <none> <none>
kube-system kube-proxy-v4dqg 1/1 Running 0 84m 145.100.57.33 controller <none> <none>
kube-system kube-proxy-wbgff 1/1 Running 0 84m 145.100.57.36 node1 <none> <none>
kube-system kube-scheduler-controller 1/1 Running 0 83m 145.100.57.33 controller <none> <none></code></pre>
</div>
</div>
<div class="paragraph">
<p>Note that they are all listed in the <code>kube-system</code> namespace, as they should.
Hence I use the <code>--all-namespaces</code> flag (the short version is <code>-A</code>).
I have also used the <code>--output wide</code> option (short: <code>-o</code>), to get some extra information about the pods, including their IP addresses.
You’ll notice a mix of internal (192.168.x.y) and external (145.100.57.z) addresses.
The RESTARTS column is good to pay attention to if you notice a pod is not 1/1 READY: it there area lot of restarts in its uptime, that pod clearly has a problem.
Try and use <code>kubectl logs <podname> [-n <namespace>]</code> for a debugging start.</p>
</div>
<div class="paragraph">
<p>You can also list the available services:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>$ kubectl get svc -A
NAMESPACE NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
default kubernetes ClusterIP 192.168.0.1 <none> 443/TCP 83m
kube-system kube-dns ClusterIP 192.168.0.10 <none> 53/UDP,53/TCP 82m</code></pre>
</div>
</div>
</div>
</div>
</div>
<div class="sect1">
<h2 id="_storage_space_for_pods">Storage space for pods</h2>
<div class="sectionbody">
<div class="paragraph">
<p>We’ll want some storage space for the Jupyter pods that will be running later.
Ideally, this means using a storage space provided by the cloud setup, but since there is none, I’m using fixed storage.
This is obviously not ideal, but works for our demonstration case.</p>
</div>
<div class="paragraph">
<p>In Kubernetes, there is the concept of a <code>PersistentVolume</code> for providing storage.
Here, I tie these persistent volumes to a directory on disk.
The CEPH data disk is mounted at <code>/mnt/data</code>, with each node having one disk mounted.
I made three directories, an identical one on each node (not necessary, for demonstration purposes), which ise the one for user storage, and another on node 2 other for JupyterHub’s database.</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code># on node1:
sudo mkdir /mnt/data/pv-user
# on node2:
sudo mkdir /mnt/data/pv-user
sudo mkdir /mnt/data/pv-hub</code></pre>
</div>
</div>
<div class="paragraph">
<p>Note that node1 is the first worker, and node2 is the second worker.
I am not using the controller for volumes, since pods are not running on the controller.
Root access is fine, since you’ve started <code>kubeadm</code> as root as well.</p>
</div>
<div class="paragraph">
<p>Now, create a <code>pv.yaml</code> file, as follows:</p>
</div>
<div class="listingblock">
<div class="content">
<pre class="highlight"><code>apiVersion: v1
kind: PersistentVolume
metadata:
name: pv-user
namespace: jhub
labels:
hub: jhub
type: hubdb
spec:
capacity:
storage: 50Gi
accessModes:
- ReadWriteOnce
persistentVolumeReclaimPolicy: Retain
storageClassName: hub-user-storage
local:
path: /mnt/data/pv-user
nodeAffinity:
required:
nodeSelectorTerms:
- matchExpressions:
- key: kubernetes.io/hostname
operator: In
values:
- node1
- node2