1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
|
---
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 **(CORE)**
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.
<i class="fa fa-youtube-play youtube" aria-hidden="true"></i>
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 add a cluster using one
of the [GitLab integrations](../add_remove_clusters.md#create-new-cluster).
- **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](http://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. Add a Kubernetes cluster to your project by following the steps outlined in
[Create new cluster](../add_remove_clusters.md#create-new-cluster).
1. Click the **Install** button next to the **Ingress** application to install Ingress.
![install ingress](img/ingress-install.png)
1. After Ingress has been installed successfully, click the **Install** button next
to the **JupyterHub** application. You need the **Jupyter Hostname** provided
here in the next step.
![install JupyterHub](img/jupyterhub-install.png)
1. After JupyterHub has been installed successfully, open the **Jupyter Hostname**
in your browser. Click the **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.
![authorize Jupyter](img/authorize-jupyter.png)
1. Click **Authorize**, and GitLab redirects you to the JupyterHub application.
1. Click **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.
![demo runbook](img/demo-runbook.png)
1. Double-click the `Nurtch-DevOps-Demo.ipynb` runbook.
![sample runbook](img/sample-runbook.png)
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 = '<your_access_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.
![GitLab variables](img/gitlab-variables.png)
1. Click **Save variables**.
1. In Jupyter, click the **Run SQL queries in Notebook** heading, and then click
**Run**. The results are displayed inline as follows:
![PostgreSQL query](img/postgres-query.png)
You can try other operations, such as running shell scripts or interacting with a
Kubernetes cluster. Visit the
[Nurtch Documentation](http://docs.nurtch.com/) for more information.
|