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Artificial Intelligence (AI) and Machine Learning (ML) are the next big hype in networking following Software-Defined Everything and Intent-Based Everything. Like with the previous hype bubbles it’s worth figuring out

• How much of the hype is real (TL&DR: not much)?
• Whether the technology is ready to be used in production networks (TL&DR: some of it)
• How you could use the technology to make your life easier

How Real Is It?

Like with the previous hype tsunamis I’ll do my best to help you figure out the answers to the above questions with a hefty dose of skepticism and snark¹, starting with:

The netlab tool will help you be more proficient once you decide to drop GUI-based network simulators and build your labs using CLI and infrastructure-as-code principles.

You can also use netlab (potentially together with GitHub Codespaces) to build online, easy-to-consume, hands-on training solutions. I used that approach to build the BGP labs, IS-IS labs, and VXLAN/EVPN labs.

Segment Routing with MPLS Labels (SR-MPLS) is a major improvement over the traditional MPLS control plane (LDP or RSVP-TE). Instead of running two protocols (a routing protocol and a signaling protocol), SR-MPLS adds segment information to the IS-IS or OSPF topology database, avoiding the pesky IGP/LDP synchronization issues we’ve been fighting for decades.

The MPLS labels (Segment Identifiers) assigned to nodes, adjacencies, or prefixes can be used to transport data across the network (similar to traditional MPLS core), to establish traffic engineering tunnels, or to implement topology-independent loop-free alternate paths for fast failover.

ChatGPT trying (and failing) to explain EVPN