Erwan Gallen
Erwan Gallen

Feb 26, 2020 3 min read

Open Data Hub v0.5.1 release

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Open Data Hub v0.5.1 was released February 16, 2020.

Release node:

Open Data Hub includes many tools that are essential to a comprehensive AI/ML end-to-end platform. This new release integrate some bug fixes that resolve issues when deploying on OpenShift Container Platform v4.3. JupyterHub deployment and Spark cluster resources have now a greater customization. Let’s try the Data science tools JupyterHub 3.0.7 on OpenShift 4.3.

First, open an OpenShift 4.3 console.

Install the Open Data Hub Operator

Create a project “odh”: create project

Go to Operators > OperatorHub and search “open data hub”: search the operator

Click on “Install”: install

Click on “Subscribe”: Suscribe

Open data Hub v0.5.1 is installed: installed

Create a New Open Data Hub deployment

Click on “Create Instance” create an instance

Click on “Create”: create an instance

When the instance is created, you can check the running workloads in “Home” > “Projects” > “odh” > Tab “Workloads”: odh workloads

Test Jupyter Hub

Click on the workoad “jupyterhub” and the tab “Resources”, you can copy the route configured.

The route is “”, copy this URL: jupyterhub route

In a new browser tab paste and open the jupyterhub URL, click on “Sign in with OpenShift”: -

Choose the provider: -

Type your credentials: -

Authorize Access, click on “Allow selected permissions”: -

You are ready with the Jupyter Hub form to configure your first Jupyter Notebook. First launch a notebook without GPU: -

The server is starting up: -

The Notebook is available: -

Launch a Terminal: -

Check the UBI minimal image: -

Check the pods running in the odh project:

[stack@perflab-director ~]$ oc project odh
Now using project "odh" on server "".

[stack@perflab-director ~]$ oc get pods
NAME                                   READY   STATUS      RESTARTS   AGE
jupyterhub-1-cj4sw                     1/1     Running     0          119m
jupyterhub-1-deploy                    0/1     Completed   0          120m
jupyterhub-db-1-64pl4                  1/1     Running     0          119m
jupyterhub-db-1-deploy                 0/1     Completed   0          120m
jupyterhub-nb-egallen                  2/2     Running     0          88m
opendatahub-operator-59985b769-2nrpn   1/1     Running     0          127m
spark-cluster-egallen-m-ln2qz          1/1     Running     0          88m
spark-cluster-egallen-w-f8dtc          1/1     Running     0          88m
spark-cluster-egallen-w-gskm6          1/1     Running     0          88m
spark-operator-8485787fd8-z4j5m        1/1     Running     0          119m

If you don’t want to use the Terminal UI, you can rsh in the container:

[stack@perflab-director ~]$ oc rsh jupyterhub-nb-egallen 
Defaulting container name to notebook.
Use 'oc describe pod/jupyterhub-nb-egallen -n odh' to see all of the containers in this pod.
(app-root) sh-4.2$ 

Check the default jupyterhub notebook image s2i-spark-minimal-notebook:3.6:

sh-4.2$ cat /etc/os-release
NAME="Red Hat Enterprise Linux Server"
VERSION="7.6 (Maipo)"
PRETTY_NAME="Red Hat Enterprise Linux Server 7.6 (Maipo)"

REDHAT_BUGZILLA_PRODUCT="Red Hat Enterprise Linux 7"
REDHAT_SUPPORT_PRODUCT="Red Hat Enterprise Linux"

sh-4.2$ cat /etc/redhat-release
Red Hat Enterprise Linux Server release 7.6 (Maipo)

sh-4.2$ uname -a
Linux jupyterhub-nb-egallen 4.18.0-147.3.1.el8_1.x86_64 #1 SMP Wed Nov 27 01:11:44 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

sh-4.2$ python -V
Python 3.6.3

sh-4.2$ ls /etc/yum.repos.d/
redhat.repo  ubi.repo

sh-4.2$ cat /etc/yum.repos.d/ubi.repo | grep -A5 "\[ubi-7\]"
name = Red Hat Universal Base Image 7 Server (RPMs)
baseurl =$basearch/os
enabled = 1
gpgkey = file:///etc/pki/rpm-gpg/RPM-GPG-KEY-redhat-release
gpgcheck = 1

GPU Notebook

sh-4.2$ nvidia-smi
Wed Feb 26 13:37:53 2020
| NVIDIA-SMI 440.33.01    Driver Version: 440.33.01    CUDA Version: N/A      |
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|   0  Tesla V100-PCIE...  On   | 00000000:00:05.0 Off |                  Off |
| N/A   29C    P0    24W / 250W |      0MiB / 16160MiB |      0%      Default |

| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|  No running processes found                                                 |

sh-4.2$ nvidia-smi --list-gpus

sh-4.2$ whereis nvidia-smi
nvidia-smi: /usr/bin/nvidia-smi

sh-4.2$ lsmod | grep nvidia
nvidia_modeset       1114112  0
nvidia_uvm           1085440  0
nvidia              19927040  53 nvidia_uvm,nvidia_modeset
ipmi_msghandler       110592  2 ipmi_devintf,nvidia