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Network Automation Concepts

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This webinar provides an overview of network automation concepts you should master as you progress from easy wins like creating automated reports or device configurations to building automation systems.

Last modified on 2021-08-28 (release notes)

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Network Automation Concepts

1:53:10 Data Models in Network Automation

This section introduces data models and helps you answer these questions:

  • How should I structure the data I need to describe devices in my network?
  • Should I describe devices or should I focus on network topology and services?
  • Can I use device-level data to create device configurations while presenting high-level data models to the operators?
  • How could I transform abstracted (high-level) network- and services data models into device-level data models?
  • How could I integrate data model transformation into my automation workflow?
Data Model Introduction 17:55 2021-04-21
Data Model Introduction QA 8:53 2021-04-21
Device-Level Data Models 15:33 2021-04-21
Optimizing a Device-Level Data Model 17:53 2021-04-21
Infrastructure and Services Data Models 11:40 2021-04-21
Data Model Transformations 17:45 2021-04-21
Data Model Transformation in Automation Workflow 23:31 2021-08-28

Further Reading – Data Models

Network Automation Data Model Optimization
Data Model Transformation Concepts
Data Transformation Example (Jinja2 / Ansible / Makefile)
Complex Data Transformation Example: Lab Topology Building Tool
Source Code for the Lab Topology Building Tool

Further Reading – Data Transformation

Data Model Transformations in Network Automation Solutions
Worth Reading: Data Manipulation in Jinja2

1:20:31 Formatting, Describing, and Storing Data

After you built your data model, you have to create data structures (device, link, network, service, or customer data) in a format readable by humans and machines, describe the data model for documentation and validation purposes, and store the data somewhere.

This section dives deep into presentation formats (XML, JSON, YAML), data description languages (including YANG), and data stores, from text files and Excel to NoSQL databases.

Data Representation 18:56 2021-08-28
Data Model Descriptions 15:32 2021-08-28
YANG and OpenConfig 13:17 2021-08-28
Data Stores 18:56 2021-08-28
Selecting a Data Store 13:50 2021-08-28

Further Reading – Data Representation

Beware XML-to-JSON Information Loss (Junos with Ansible)
XML-to-JSON Information Loss, Cisco Nexus OS Edition
Fixing XML-to-JSON Conversion Challenges

Further Reading – Data Validation

Data Validation with JSON Schema
Simple Data Validation with YANG Using yanglint
Interesting Tool: Schema Enforcer
New Ansible Data Validation Module(s)
Automation Should Prevent Operator Errors
Validating Data in GitOps-Based Automation
Automation Solution: Testing Data Models

Further Reading – Data Stores

Text Files or Relational Database?
Using YAML Instead of Excel in Network Automation Solutions
Growing Beyond Ansible host_vars and group_vars
What’s the Big Deal with Validation?

Other Interesting Blog Posts

What’s the Big Deal with Validation?
What Is Continuous Integration?
Continuous Integration in Network Automation
Firewall Ruleset Automation with CI Pipeline
From Excel to Network Infrastructure as Code with Carl Buchmann

Sample YANG Data Models

YANG Module Classification (RFC 8199)
Service models explained (RFC 8309)
Customer-focused YANG model for L3VPN service delivery
Network-centric L3VPN YANG Model
YANG model for L2VPN service delivery

Single Source of Truth

After mastering the data model-, model transformation-, and data store concepts, you're ready for one of the most important network automation topics: single source of truth.

We plan to run a series of live sessions focusing on single source of truth in network automation in autumn 2021. In the meantime, enjoy a collection of related blog posts.

Building the Network Automation Source of Truth
Building Network Automation Source-of-Truth (Part 2)
Creating Automation Source-of-Truth from Device Configurations
Device Configurations Are Not a Good Source of Truth
Read Network Device Information with REST API and Store It Into a Database
Building Automation Device Inventory with Open Source Tools

1:41:44 Intent-Driven Networking (2018 Edition)

Most of the intent-based systems are nothing more than a fancy orchestration system with an abstraction layer. This section describes the many levels of abstraction you can implement in such a system.

This material is also available as part of Network Automation Use Cases webinar

What Is Intent-Based Networking 8:17 2018-04-04
Device Configuration as Intent 13:47 2018-04-04
Abstracting and Managing Device-Level Intent 19:34 2018-04-04
Network-Wide Intent 23:21 2018-04-04
Automated Remediation 18:52 2018-04-04
Back to Reality 10:31 2018-04-04
Questions and Answers 7:22 2018-04-04

Additional resources

Slide deck 2.9M 2018-01-13
Intent-Based Networking Taxonomy
The Maslow’s Pyramid of Needs of Intent-based Networking by Benoît Claise

Slide Decks

Data Models and Data Stores 3.3M 2021-01-20
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