---
stage: Configure
group: Configure
info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#assignments
---
# Runbooks **(FREE)**
Runbooks are a collection of documented procedures that explain how to
carry out a particular process, be it starting, stopping, debugging,
or troubleshooting a particular system.
Using [Jupyter Notebooks](https://jupyter.org/) and the
[Rubix library](https://github.com/Nurtch/rubix),
users can get started writing their own executable runbooks.
Historically, runbooks took the form of a decision tree or a detailed
step-by-step guide depending on the condition or system.
Modern implementations have introduced the concept of an "executable
runbooks", where, along with a well-defined process, operators can execute
pre-written code blocks or database queries against a given environment.
## Executable Runbooks
> [Introduced](https://gitlab.com/gitlab-org/gitlab-foss/-/issues/45912) in GitLab 11.4.
The JupyterHub app offered via the GitLab Kubernetes integration now ships
with Nurtch's Rubix library, providing a simple way to create DevOps
runbooks. A sample runbook is provided, showcasing common operations. While
Rubix makes it simple to create common Kubernetes and AWS workflows, you can
also create them manually without Rubix.
Watch this [video](https://www.youtube.com/watch?v=Q_OqHIIUPjE)
for an overview of how this is accomplished in GitLab!
## Requirements
To create an executable runbook, you need:
- **Kubernetes** - A Kubernetes cluster is required to deploy the rest of the
applications. The simplest way to get started is to connect a cluster using the
[GitLab agent](../../../clusters/agent/index.md).
- **Ingress** - Ingress can provide load balancing, SSL termination, and name-based
virtual hosting. It acts as a web proxy for your applications.
- **JupyterHub** - [JupyterHub](https://jupyterhub.readthedocs.io/) is a multi-user
service for managing notebooks across a team. Jupyter Notebooks provide a
web-based interactive programming environment used for data analysis,
visualization, and machine learning.
## Nurtch
Nurtch is the company behind the [Rubix library](https://github.com/Nurtch/rubix).
Rubix is an open-source Python library that makes it easy to perform common
DevOps tasks inside Jupyter Notebooks. Tasks such as plotting Cloudwatch metrics
and rolling your ECS/Kubernetes app are simplified down to a couple of lines of
code. See the [Nurtch Documentation](https://docs.nurtch.com/en/latest/) for more
information.
## Configure an executable runbook with GitLab
Follow this step-by-step guide to configure an executable runbook in GitLab using
the components outlined above and the pre-loaded demo runbook.
1. Create an [OAuth application for JupyterHub](../../../../integration/oauth_provider.md).
1. When [installing JupyterHub with Helm](https://zero-to-jupyterhub.readthedocs.io/en/latest/jupyterhub/installation.html),
use the following values:
```yaml
#-----------------------------------------------------------------------------
# The gitlab and ingress sections must be customized!
#-----------------------------------------------------------------------------
gitlab:
clientId:
clientSecret:
callbackUrl: http:///hub/oauth_callback,
# Limit access to members of specific projects or groups:
# allowedGitlabGroups: [ "my-group-1", "my-group-2" ]
# allowedProjectIds: [ 12345, 6789 ]
# ingress is required for OAuth to work
ingress:
enabled: true
host:
# tls:
# - hosts:
# -
# secretName: jupyter-cert
# annotations:
# kubernetes.io/ingress.class: "nginx"
# kubernetes.io/tls-acme: "true"
#-----------------------------------------------------------------------------
# NO MODIFICATIONS REQUIRED BEYOND THIS POINT
#-----------------------------------------------------------------------------
hub:
extraEnv:
JUPYTER_ENABLE_LAB: 1
extraConfig: |
c.KubeSpawner.cmd = ['jupyter-labhub']
c.GitLabOAuthenticator.scope = ['api read_repository write_repository']
async def add_auth_env(spawner):
'''
We set user's id, login and access token on single user image to
enable repository integration for JupyterHub.
See: https://gitlab.com/gitlab-org/gitlab-foss/issues/47138#note_154294790
'''
auth_state = await spawner.user.get_auth_state()
if not auth_state:
spawner.log.warning("No auth state for %s", spawner.user)
return
spawner.environment['GITLAB_ACCESS_TOKEN'] = auth_state['access_token']
spawner.environment['GITLAB_USER_LOGIN'] = auth_state['gitlab_user']['username']
spawner.environment['GITLAB_USER_ID'] = str(auth_state['gitlab_user']['id'])
spawner.environment['GITLAB_USER_EMAIL'] = auth_state['gitlab_user']['email']
spawner.environment['GITLAB_USER_NAME'] = auth_state['gitlab_user']['name']
c.KubeSpawner.pre_spawn_hook = add_auth_env
auth:
type: gitlab
state:
enabled: true
singleuser:
defaultUrl: "/lab"
image:
name: registry.gitlab.com/gitlab-org/jupyterhub-user-image
tag: latest
lifecycleHooks:
postStart:
exec:
command:
- "sh"
- "-c"
- >
git clone https://gitlab.com/gitlab-org/nurtch-demo.git DevOps-Runbook-Demo || true;
echo "https://oauth2:${GITLAB_ACCESS_TOKEN}@${GITLAB_HOST}" > ~/.git-credentials;
git config --global credential.helper store;
git config --global user.email "${GITLAB_USER_EMAIL}";
git config --global user.name "${GITLAB_USER_NAME}";
jupyter serverextension enable --py jupyterlab_git
proxy:
service:
type: ClusterIP
```
1. After JupyterHub has been installed successfully, open the **Jupyter Hostname**
in your browser. Select **Sign in with GitLab** button to log in to
JupyterHub and start the server. Authentication is enabled for any user of the
GitLab instance with OAuth2. This button redirects you to a page at GitLab
requesting authorization for JupyterHub to use your GitLab account.
1. Select **Authorize**, and GitLab redirects you to the JupyterHub application.
1. Select **Start My Server** to start the server in a few seconds.
1. To configure the runbook's access to your GitLab project, you must enter your
[GitLab Access Token](../../../profile/personal_access_tokens.md)
and your Project ID in the **Setup** section of the demo runbook:
1. Double-click the **DevOps-Runbook-Demo** folder located on the left panel.
1. Double-click the `Nurtch-DevOps-Demo.ipynb` runbook.
Jupyter displays the runbook's contents in the right-hand side of the screen.
The **Setup** section displays your `PRIVATE_TOKEN` and your `PROJECT_ID`.
Enter these values, maintaining the single quotes as follows:
```sql
PRIVATE_TOKEN = ''
PROJECT_ID = '1234567'
```
1. Update the `VARIABLE_NAME` on the last line of this section to match the name of
the variable you're using for your access token. In this example, our variable
name is `PRIVATE_TOKEN`.
```sql
VARIABLE_VALUE = project.variables.get('PRIVATE_TOKEN').value
```
1. To configure the operation of a runbook, create and configure variables.
For this example, we are using the **Run SQL queries in Notebook** section in the
sample runbook to query a PostgreSQL database. The first four lines of the following
code block define the variables that are required for this query to function:
```sql
%env DB_USER={project.variables.get('DB_USER').value}
%env DB_PASSWORD={project.variables.get('DB_PASSWORD').value}
%env DB_ENDPOINT={project.variables.get('DB_ENDPOINT').value}
%env DB_NAME={project.variables.get('DB_NAME').value}
```
1. Navigate to **Settings > CI/CD > Variables** to create
the variables in your project.
1. Select **Save variables**.
1. In Jupyter, select the **Run SQL queries in Notebook** heading, and then select
**Run**. The results are displayed inline as follows:
You can try other operations, such as running shell scripts or interacting with a
Kubernetes cluster. Visit the
[Nurtch Documentation](https://docs.nurtch.com/) for more information.