Nautobot: Opensource Network Source of Truth (NSoT) and Network Automation Platform

Network to Code is an industry leader in Network Automation and NetDevOps solutions. They help enterprises transition away from traditional, manual network management toward software-driven, scalable, and data-driven infrastructure operations. One of Network to Code’s most prominent contributions to the tech and networking community is Nautobot, an open-source Network Source of Truth (NSoT) and Network Automation Platform. 

Nautobot was initially developed by Network to Code as a fork of NetBox, it provides a centralized platform to model intended network states, manage configurations, and orchestrate automated workflows across modern enterprise networks.

Core Pillars of Nautobot:

1. Network Source of Truth (NSoT): Acts as a flexible, vendor-agnostic repository for all network inventory, IP addresses (IPAM), VLANs, and circuits. This decoupled data allows you to separate network design from vendor-specific command-line syntax.
2. Network Automation Platform: Functions like a smartphone with an app ecosystem. It leverages APIs, webhooks, and Git integration to execute network state changes, making it the central engine for your automation scripts.

Nautobot is designed to solve a fundamental engineering problem in modern infrastructure: how do you build reliable network automation when your network data is fragmented across spreadsheets, disparate monitoring tools, vendor controllers, and legacy CMDBs? Built by Network to Code as a web application on top of the Django Python framework, Nautobot acts as a Network Source of Truth (NSoT) and Network Automation Platform.

The Engine for Synchronization:
Nautobot SSoT & DiffSync One of Nautobot’s most powerful enterprise capabilities is its Single Source of Truth (SSoT) framework, driven by an internal library called DiffSync.

1. Bridging the Gaps: Instead of replacing every tool in your stack overnight, SSoT allows Nautobot to act as a reconciliation engine. It pulls data from external systems (such as IPAM tools, cloud controllers like AWS/Azure, monitoring platforms, or third-party inventory), compares it against its own canonical model, and highlights discrepancies.
2. Dry-Runs and Diffs: Before anything changes, synchronization jobs provide detailed, structured logs and previewable "diffs." This ensures human operators maintain governance while enabling continuous automated reconciliation.

Native Automation & API-First Design Automation cannot function on stale, batch-exported CSV files. Nautobot is built with an API-first approach:

1. Robust REST and GraphQL APIs: External automation pipelines, CI/CD systems, and orchestration tools (like Ansible or Nornir via official inventory plugins) can query the exact state of the network programmatically. GraphQL allows consumers to fetch precisely the nested data structures they need in a single query.
2. The Jobs Framework: Engineers can write native Python scripts (Jobs) directly inside Nautobot. These jobs can be triggered manually via the UI, scheduled as cron-like tasks, or fired off dynamically.
3. Event-Driven Webhooks: Whenever an object changes (e.g., a new port is provisioned or an IP address is allocated), Nautobot can fire a webhook to trigger downstream actions—such as updating a firewall rule, kicking off a provisioning pipeline, or alerting an incident management system.

ref:

NetworkToCode: https://networktocode.com/

Nautobot github: 

1. https://github.com/nautobot
2. https://github.com/nautobot/nautobot

Nautobot documentation:

1. https://archive.docs.nautobot.com/
2. https://archive.docs.nautobot.com/projects/core/en/v1.1.0

Nautobot git repositories: https://docs.nautobot.com/projects/core/en/stable/user-guide/platform-functionality/gitrepository/

Nautobot Dev Example App: https://github.com/nautobot/nautobot-app-dev-example