Nautobot Version Control
Project description
Nautobot Version Control
The Nautobot Version Control app brings version control to the Nautobot open source Network Source of Truth and Network Automation Platform.
Nautobot provides a number of features to validate its data model and safeguard network configuration from errors. Adding database versioning provides another layer of assurance by enabling human review of proposed changes to production data, use of automated testing pipelines, and database rollback in the case of errors.
The database versioning is made possible by the use of a Dolt database. Dolt is a MySQL-compatible SQL database that you can fork, clone, branch, merge, push and pull just like a Git repository.
Dolt’s branch and merge versioning model allows operators to safely modify the data model on feature branches, merging to production only after validation is complete.
Documentation
In addition to this README
file, there are docs covering the following topics:
- Version control operations
- Covers common version control operations in the Version Control app
- Common workflows
- Covers common workflows enabled by the Version Control app
- Design
- Describes the technical design and implementation details of the Version Control app
Installation
Installation Considerations
There are some special considerations for running the Version Control app:
- Nautobot 1.2.0 or later is required
- The Nautobot installation must be running a Dolt database
- There are some additional configurations required in
nautobot_config.py
The version control app can be installed with pip3:
pip3 install nautobot-version-control
To ensure the version control app is automatically reinstalled during future upgrades, create a new file named local_requirements.txt
(if not already existing) in the Nautobot root directory (e.g. /opt/nautobot
) to include the nautobot-version-control
package:
echo nautobot-version-control >> local_requirements.txt
Configuring Nautobot to use Version Control
Add this to your nautobot_config.py
to prepare your Nautobot settings for Dolt:
# Dolt requires a second database using the same credentials as the default database so that it may
# generate diffs.
DATABASES["global"] = DATABASES["default"]
# Dolt requires a custom database router to generate the before & after queries for generating diffs.
DATABASE_ROUTERS = ["dolt.routers.GlobalStateRouter"]
# Because Dolt creates branches of the database, the default database sessions cannot be used. We
# must tell Nautobot to use Redis for sessions instead. This adds a distinct cache configuration for
# using Redis cache for sessions.
# See: https://github.com/jazzband/django-redis#configure-as-session-backend
CACHES["sessions"] = {
"BACKEND": "django_redis.cache.RedisCache",
"LOCATION": parse_redis_connection(redis_database=2),
"TIMEOUT": 300,
"OPTIONS": {
"CLIENT_CLASS": "django_redis.client.DefaultClient",
},
}
# Use the sessions alias defined in CACHES for sessions caching
SESSION_CACHE_ALIAS = "sessions"
# Use the Redis cache as the session engine
SESSION_ENGINE = "django.contrib.sessions.backends.cache"
# Enable the Version Control app
PLUGINS = [ "nautobot_version_control" ]
Then run database migrations:
$ nautobot-server migrate
Production Deployment
TBD as we progress towards stable release.
Development Environment
In addition to the instructions below, we also have a demonstration video that walks the user through the dev and test setup process described below.
Getting Started
Getting started with development for the Version Control plugin is straightforward. It is modeled directly after the development environment of Nautobot itself, and should feel very familiar to anyone with Django development experience.
The Version Control app uses a Docker Compose environment to make it simple to manage dependencies like Dolt and Redis.
Install Invoke
Because it is used to execute all common Docker workflow tasks, Invoke must be installed for your user environment. On most systems, if you're installing without root/superuser permissions, the default will install into your local user environment.
$ pip3 install invoke
If you run into issues, you may also deliberately tell pip3 to install into your user environment by adding the --user flag:
$ pip3 install --user invoke
List Invoke Tasks
Now that you have an invoke command, list the tasks defined in tasks.py with invoke --list
:
$ invoke --list
Available tasks:
bandit Run bandit to validate basic static code security analysis.
black Check Python code style with Black.
build Build Nautobot docker image.
check-migrations Check for missing migrations.
cli Launch a bash shell inside the running Nautobot container.
createsuperuser Create a new Nautobot superuser account (default: "admin"), will prompt for password.
debug Start Nautobot and its dependencies in debug mode.
destroy Destroy all containers and volumes.
flake8 Check for PEP8 compliance and other style issues.
generate-packages Generate all Python packages inside docker and copy the file locally under dist/.
hadolint Check Dockerfile for hadolint compliance and other style issues.
load-data Load data.
makemigrations Perform makemigrations operation in Django.
migrate Perform migrate operation in Django.
nbshell Launch an interactive nbshell session.
post-upgrade Performs Nautobot common post-upgrade operations using a single entrypoint.
pydocstyle Run pydocstyle to validate docstring formatting adheres to NTC defined standards.
pylint Run pylint code analysis.
restart Gracefully restart all containers.
sphinx Rebuild Sphinx documentation on changes, with live-reload in the
browser.
start Start Nautobot and its dependencies in detached mode.
stop Stop Nautobot and its dependencies.
tests Run all tests for this plugin.
unittest Run Nautobot unit tests.
unittest-coverage Report on code test coverage as measured by 'invoke unittest'.
vscode Launch Visual Studio Code with the appropriate Environment variables to run in a container.
yamllint Run yamllint to validate formating adheres to NTC defined YAML standards.
Using Docker with Invoke
A development environment can be easily started up from the root of the project using commands detailed below.
Initialize the Local environment
Run the following commmands to initialize the local environment:
cp development/creds.example.env development/creds.env
invoke build
From here, you can either start the local environment with a sample database or start the local environment with an empty database.
Start the Local environment with a sample database
This is a good option for those who want to quickly spin up a working instance of Nautobot running the Version Control app. The steps below will create a Nautobot instance running Version Control and install sample data to experiment with.
invoke migrate
invoke load-data
invoke start
invoke load-data
can take up to 30 min to run and it will generate many warning messages which may be safely ignored.
After a few minutes, Nautobot will be available at http://0.0.0.0:8080
You can connect with either of these 2 accounts:
- Login
admin
/ Passwordadmin
- Login
demo
/ Passwordnautobot
Run the following commands to reset the local environment and load the sample dataset again:
invoke stop
invoke destroy
invoke migrate
invoke load-data
invoke start
Start the Local environment with an empty database
This option will simply start the local dev environment. Nautobot will have an empty database:
invoke migrate
invoke start
After a few minutes, Nautobot will be available at http://0.0.0.0:8080
You can connect with:
- Login
admin
/ Passwordadmin
Run the following commands to reset the local environment:
invoke stop
invoke destroy
invoke migrate
invoke start
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