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6 KiB
Markdown
137 lines
No EOL
6 KiB
Markdown
# Runbooks
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Runbooks are a collection of documented procedures that explain how to
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carry out a particular process, be it starting, stopping, debugging,
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or troubleshooting a particular system.
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## Overview
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Historically, runbooks took the form of a decision tree or a detailed
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step-by-step guide depending on the condition or system.
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Modern implementations have introduced the concept of an "executable
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runbooks", where, along with a well-defined process, operators can execute
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pre-written code blocks or database queries against a given environment.
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## Nurtch Executable Runbooks
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> [Introduced](https://gitlab.com/gitlab-org/gitlab-ce/issues/45912) in GitLab 11.4.
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The JupyterHub app offered via GitLab’s Kubernetes integration now ships
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with Nurtch’s Rubix library, providing a simple way to create DevOps
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runbooks. A sample runbook is provided, showcasing common operations.
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**<i class="fa fa-youtube-play youtube" aria-hidden="true"></i>
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Watch this [video](https://www.youtube.com/watch?v=Q_OqHIIUPjE)
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for an overview of how this is acomplished in GitLab!**
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## Requirements
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To create an executable runbook, you will need:
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1. **Kubernetes** - A Kubernetes cluster is required to deploy the rest of the applications.
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The simplest way to get started is to add a cluster using [GitLab's GKE integration](https://docs.gitlab.com/ee/user/project/clusters/#adding-and-creating-a-new-gke-cluster-via-gitlab).
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1. **Helm Tiller** - Helm is a package manager for Kubernetes and is required to install
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all the other applications. It is installed in its own pod inside the cluster which
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can run the helm CLI in a safe environment.
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1. **Ingress** - Ingress can provide load balancing, SSL termination, and name-based
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virtual hosting. It acts as a web proxy for your applications.
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1. **JupyterHub** - JupyterHub is a multi-user service for managing notebooks across
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a team. Jupyter Notebooks provide a web-based interactive programming environment
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used for data analysis, visualization, and machine learning.
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## Nurtch
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Nurtch is the company behind the [Rubix library](https://github.com/Nurtch/rubix). Rubix is
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an open-source python library that makes it easy to perform common DevOps tasks inside Jupyter Notebooks.
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Tasks such as plotting Cloudwatch metrics and rolling your ECS/Kubernetes app are simplified
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down to a couple of lines of code. See the [Nurtch Documentation](http://docs.nurtch.com/en/latest)
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for more information.
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## Configure an executable runbook with GitLab
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Follow this step-by-step guide to configure an executable runbook in GitLab using
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the components outlined above and the preloaded demo runbook.
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### 1. Add a Kubernetes cluster
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Follow the steps outlined in [Adding and creating a new GKE cluster via GitLab](https://docs.gitlab.com/ee/user/project/clusters/#adding-and-creating-a-new-gke-cluster-via-gitlab)
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to add a Kubernetes cluster to your project.
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### 2. Install Helm Tiller, Ingress, and JupyterHub
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Once the cluster has been provisioned in GKE, click the **Install** button next to the **Helm Tiller** app.
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Once Tiller has been installed successfully, click the **Install** button next to the **Ingress** app.
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Once Ingress has been installed successfully, click the **Install** button next to the **JupyterHub** app.
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### 3. Login to JupyterHub and start the server
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Once JupyterHub has been installed successfully, navigate to the displayed **Jupyter Hostname** URL and click
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**Sign in with GitLab**. Authentication is automatically enabled for any user of the GitLab instance via OAuth2. This
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will redirect to GitLab in order to authorize JupyterHub to use your GitLab account. Click **Authorize**.
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Once the application has been authorized you will taken back to the JupyterHub application. Click **Start My Server**.
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The server will take a couple of seconds to start.
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### 4. Configure access
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In order for the runbook to access your GitLab project, you will need to enter a
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[GitLab Access Token](https://docs.gitlab.com/ee/user/profile/personal_access_tokens.html)
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as well as your Project ID in the **Setup** section of the demo runbook.
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Double-click the **DevOps-Runbook-Demo** folder located on the left panel.
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Double-click the "Nurtch-DevOps-Demo.ipynb" runbook.
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The contents on the runbook will be displayed on the right side of the screen. Under the "Setup" section, you will find
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entries for both your `PRIVATE_TOKEN` and your `PROJECT_ID`. Enter both these values, conserving the single quotes as follows:
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```sql
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PRIVATE_TOKEN = 'n671WNGecHugsdEDPsyo'
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PROJECT_ID = '1234567'
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```
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Update the `VARIABLE_NAME` on the last line of this section to match the name of the variable you are using for your
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access token. In this example our variable name is `PRIVATE_TOKEN`.
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```sql
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VARIABLE_VALUE = project.variables.get('PRIVATE_TOKEN').value
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```
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### 5. Configure an operation
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For this example we'll use the "**Run SQL queries in Notebook**" section in the sample runbook to query
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a postgres database. The first 4 lines of the section define the variables that are required for this query to function.
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```sql
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%env DB_USER={project.variables.get('DB_USER').value}
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%env DB_PASSWORD={project.variables.get('DB_PASSWORD').value}
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%env DB_ENDPOINT={project.variables.get('DB_ENDPOINT').value}
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%env DB_NAME={project.variables.get('DB_NAME').value}
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```
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Create the matching variables in your project's **Settings >> CI/CD >> Variables**
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Back in Jupyter, click the "Run SQL queries in Notebook" heading and the click *Run*. The results will be
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displayed in-line as follows:
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You can try other operations such as running shell scripts or interacting with a Kubernetes cluster. Visit the
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[Nurtch Documentation](http://docs.nurtch.com/) for more information. |