Why a network digital twin is the missing piece for AI-era operations

Ask a software developer where they test code, and they’ll describe a staging environment, version control, and an automated regression suite.

The short version

• Ask a network engineer the same question, and the honest answer, more often than not, is “in production.” This was standard practice when I was running networks more than 20 years ago, and it’s still the case.
• For decades, the industry has accepted making a change, watching what happens, and rolling back if something breaks.
• That was tolerable when teams made changes one at a time during a maintenance window.

What happened

As AI agents begin proposing and executing network changes, “test in production” shifts from a bad habit to a serious liability. That’s the core argument of a new e-book from Forward, The Network Digital Twin Guide , which contends that a mathematically accurate model of the network is a prerequisite for autonomous operations.

Why it matters

Forward obviously has a stake in that conclusion, but the problem it describes is real, and I hear about it constantly from network leaders.

Summary by Nerd News Network. Read the full article at Network World via the links above and below.