How do you validate network automation scripts?

1 Test your scripts locally

Before you run your network automation scripts on your production network, you should test them locally on a simulated or isolated environment. This way, you can verify the logic, syntax, and functionality of your scripts without affecting your live network. You can use tools like GNS3, EVE-NG, or Vagrant to create virtual network devices and scenarios that mimic your real network. You can also use Python libraries like Netmiko, NAPALM, or PyATS to interact with your network devices and run your scripts. Testing your scripts locally can help you identify and fix any bugs, errors, or inconsistencies in your code.

2 Use a version control system

A version control system (VCS) is a software tool that tracks and manages the changes made to your network automation scripts. A VCS can help you maintain a history of your script versions, compare and merge different versions, and revert to previous versions if needed. A VCS can also facilitate collaboration and communication among your network automation team members, as well as integration with other tools and platforms. You can use a VCS like Git, SVN, or Mercurial to store, manage, and share your network automation scripts.

4 Monitor and troubleshoot your scripts

After you deploy your network automation scripts to your network, you should monitor and troubleshoot them to ensure they are running correctly and efficiently. You can use tools like SNMP, NetFlow, or Grafana to collect and visualize data about your network performance, utilization, and health. You can also use tools like Splunk, ELK, or Graylog to collect and analyze logs and events generated by your network devices and scripts. Monitoring and troubleshooting your scripts can help you detect and resolve any issues or anomalies that may arise in your network.

5 Document and review your scripts

Another important aspect of validating your network automation scripts is documenting and reviewing them. Documenting your scripts can help you explain the purpose, functionality, and requirements of your scripts, as well as provide instructions and guidelines for using and maintaining them. Reviewing your scripts can help you evaluate the quality, efficiency, and security of your code, as well as identify any areas for improvement or optimization. You can use tools like Sphinx, MkDocs, or Doxygen to generate documentation for your scripts. You can also use tools like Pylint, Flake8, or Bandit to perform code analysis and linting on your scripts.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?