Best Network Automation Software

BackBox provides network device automation across device lifecycle management, configuration management, compliance policy management, vulnerability intelligence and network automation, positioned around keeping devices in a known and trusted state.

Vulnerability intelligence tied to configuration state is the combination that distinguishes it. Most vulnerability scanners tell you a device is running a version with a known flaw. Knowing which of your several thousand devices are affected, what configuration they are actually running and whether the mitigating configuration is in place is a different and much harder question, and it is the one that determines what you have to do this week.

The scale problem is what makes this a software category rather than a task. A mid-sized enterprise runs thousands of switches, routers, firewalls and load balancers from several vendors, each with its own command syntax, upgrade procedure and configuration model. Checking them by hand is not slow, it is impossible, so in practice it does not happen and drift accumulates until something breaks or an audit finds it.

Compliance policy management addresses the audit side of the same estate. Regulated organisations must demonstrate that devices match an approved configuration standard, and demonstrating it for a thousand devices requires the check to be automated and the evidence to be produced as a record rather than as a screenshot.

Multi-vendor support is stated explicitly, which is the point. Every vendor supplies management tooling for its own devices, and no real network runs one vendor, so the value sits in the layer that spans them.

Zero Trust for NetOps and securing modern networks are published as solution areas, with roles addressed for MSPs, security, IT and compliance teams. A value calculator, data sheets and case studies are published.

Pricing is not published.

Nautobot is an open source network source of truth and automation platform from Network to Code, published in three commercial forms alongside the open project: Nautobot Cloud as a zero infrastructure SaaS platform, Nautobot Enterprise for self-managed deployment with control over operating system upgrades and audit-ready records, and Nautobot Professional as a supported self-managed starting point with onboarding tools.

Source of truth is the concept that makes the rest coherent, and it is worth being precise about. It means a single authoritative record of what the network is supposed to be: which devices exist, how they are addressed, what they connect to and what configuration they should hold. The network itself is not that record, because the network shows what is, including every undocumented change somebody made at two in the morning during an incident.

The distinction matters because automation without a source of truth amplifies whatever state already exists. If configuration is generated from the devices themselves, errors and drift are propagated rather than corrected. Generating configuration from an intended-state record means the network converges toward what was designed, and any difference between the two becomes a detectable finding rather than an invisible fact.

Being open source is a genuine architectural advantage here rather than a licensing preference. A source of truth must model an organisation's own network, and every network has structures its vendors did not anticipate. An extensible open platform can be adapted; a closed data model has to be worked around, which is how organisations end up back in spreadsheets.

Nautobot Apps provide pre-built extensions and workflows, and NautobotGPT offers job creation assistance and troubleshooting with an MCP server and VS Code integration.

Official certifications are published, which is a meaningful signal for a platform an organisation intends to build on. Enterprise support comes directly from the engineers who build it.

Pricing is not published for the commercial editions, and the open source project itself is freely available.

Itential is an agentic operations platform for infrastructure teams, organised around five published capabilities: build, integrate, execute, secure and govern, and operate.

The governance capability is the one that determines whether this class of software can actually be deployed. Built-in role-based access control, audit and approval gates sit on every action, and that is not a compliance afterthought but the precondition for automating anything on a production network.

The reason is straightforward. Network changes are the single largest cause of network outages, and the organisations with the most to automate are precisely the ones under the most change control. An automation platform without approval gates asks a bank or a carrier to give a workflow engine the ability to reconfigure production, which no change advisory board will approve. Approval gates let automation handle the work while a human retains the decision, which is what makes adoption possible at all.

The agentic positioning raises that stake rather than lowering it. An agent that decides what to do, rather than executing a fixed workflow, needs governance more urgently, not less, and building it in from the start is the right order.

Integrate as a first-class capability reflects the actual state of network operations, where the estate spans multiple vendors, controllers, ticketing systems and cloud providers, and the automation platform's value comes largely from spanning them rather than from any single action.

Build supports visual workflow construction, AI-assisted authoring or bringing your own code, which matters because network teams range from those who write Python daily to those who do not.

Published customer accounts include Lumen's move from manual workflows to AI-assisted autonomy and Southern California Edison automating grid operations. Documentation, release notes, an MCP server and a community marketplace are published.

Pricing is not published, though a pricing page invites enquiry about flexible plans.

Forward Networks builds what it describes as a mathematically accurate digital twin of the network, published as Forward Enterprise with Forward AI and Forward Predict alongside, serving networking, security, cloud and compliance teams from a single verified model of how the network actually behaves.

The mathematical claim is the substance of the product and it is worth understanding precisely. A digital twin here is not a diagram or a monitoring view. It is a formal model built from the actual configuration and state of every device, against which questions can be answered by computation rather than by testing: whether traffic can reach a given destination, which paths it would take, and which rule permits or blocks it.

That is a categorically different capability from monitoring. Monitoring tells you what is happening now. A verified model tells you what is possible, including paths nobody has used yet and paths nobody intended to exist. Most serious security exposures in large networks are of the second kind, a route that works but should not, and no amount of traffic observation finds a path that has not been taken.

Forward Predict extends this to the change itself, testing what a proposed configuration change would do before it is applied. Since change is the largest cause of network outages, verifying a change against a model rather than discovering its effect in production is the strongest argument the category has.

Serving security and compliance teams from the same model is coherent, because a compliance question such as demonstrating that a payment environment is properly segmented is exactly a reachability question, and answering it from a verified model produces evidence rather than an assertion.

The vendor publishes Gartner recognition, a free trial, a user community and an ROI page.

Pricing is not published, though a pricing page and ROI material are offered.