Getting Started with the Cisco U. AI Assistant with the Deep Network Model: Suggested Use Cases

[ad_1] At Cisco Dwell in San Diego, D.J. Sampath, Senior Vice President of Cisco’s AI Software program and Platform group, wowed the group with a demo of AI Canvas. That’s a multi-data, multi-agent system, built-in with Cisco’s AI Assistant and powered by Cisco’s Deep Community Mannequin. In that demo, we might all see AI Canvas’s capacity to hurry troubleshooting, deliver siloed groups collectively, and allow automation throughout your complete stack.

AI Canvas received’t be out there till October. Nonetheless, we wished to supply our CCIEs, CCDEs, and Cisco Licensed DevNet Consultants the chance to work with the Deep Community Mannequin as quickly as attainable. So we’re making the mannequin out there to CCIEs and different specialists via an AI Studying Assistant out there in Cisco U.

We expect CCIEs (and shortly, different community engineers) will discover a wealth of ways in which the Deep Community Mannequin may help them study extra and turn into extra environment friendly. However we notice that agentic ops is model new, and that you simply is likely to be questioning how one can instantly begin experimenting with the Deep Community Mannequin. So I assumed I’d supply some pattern use instances that will help you get began.

Tailor-made situations and coaching paths As a CCIE, you’ve obtained years—generally many years—of expertise in networking, and also you’re totally on top of things in your group’s IT infrastructure. However what about your workforce members, particularly extra junior community engineers? The Deep Community Mannequin AI Assistant can be utilized to construct tailor-made situations and coaching concepts so that everybody in your workforce can study the talents wanted for the community you at present have, in addition to any new applied sciences your group plans to roll out.

The Deep Community Mannequin understands a variety of networking applied sciences, nevertheless it’s educated explicitly on a depth and breadth of Cisco-specific materials. It’s additionally educated on the supplies and coursework out there in Cisco U. You may strive a immediate corresponding to this one:

I'm the tech lead for a small workforce of community engineers. I have to shortly get them on top of things on the networking know-how we use in the environment, together with BGP, MPLS, and OSPF. May you construct me a customized research plan?

Once I requested this query of the Deep Community Mannequin AI Assistant, I obtained a really good syllabus in define kind, with hyperlinks to programs in Cisco U.

Right here’s a pattern:

Design validation and optimization Cisco Validated Designs (CVDs) are basically blueprints, and IT professionals are accustomed to working via them. However generally you want extra steerage. The Deep Community Mannequin AI Assistant may help make CVDs extra navigable. It may entry different sources to assist flesh out CVDs and supply options for enhancing or optimizing designs.

It may additionally summarize the CVD, supplying you with a high-level overview earlier than studying the entire thing. You'll be able to ask it questions corresponding to:

Contemplating the CVD for FlexPod, present a getting-started doc that I can use to configure my preliminary UCS supervisor. I'm starting to implement the CVD for FlexPod. May you give me a high-level overview of what I’ll be doing and the items I’ll be working with?

The Deep Community Mannequin AI Assistant may help validate an current design with respect to a CVD and supply options for enhancing or optimizing designs.

What sort of storage know-how ought to I think about for booting my blades in a UCS B chassis?

Should you’re having points with a CVD, you possibly can ask the Deep Community Mannequin AI Assistant the place it's best to begin wanting.

Automation assistant The Deep Community Mannequin AI Assistant also can assist with automation. You would ask it questions corresponding to:

I'm an professional in community structure and wish some assist automating our department SD-WAN deployment. What can be a well-supported, easy-to-learn device that may assist me help this? My workforce doesn’t have a substantial amount of coding expertise. May you present examples and hyperlinks to related documentation and coaching?

Troubleshooting The Deep Community Mannequin AI Assistant may help analyze community diagnostics, corresponding to syslog messages and debug output, and look at drawback signs to offer perception that is likely to be missed by human eyes. Though generative AI continues to be a younger know-how that may make errors, expert-level IT professionals are well-equipped to guage the output for accuracy and detect hallucinations.

For instance, the Deep Community Mannequin AI Assistant might assist interpret a syslog message. You would merely enter the message into the assistant and say you want recommendation or a spot to start out. As a result of it’s educated on Cisco’s syslog codecs, it may give steerage and cross-reference different information.

Should you’re working with a number of information sources, the evaluation turns into extra advanced. With the Deep Community Mannequin AI Assistant, you possibly can describe the symptom you see after which ask, “What ought to I search for?” (After all, it's best to at all times watch out about pasting uncooked output into AI.) On this manner, you need to use the assistant to information you to the purpose the place you’re snug taking on.

Numerous debugging is basically taking a look at several types of diagnostic information and trying to find the needle in a haystack that may assist what to do subsequent. The Deep Community Mannequin AI Assistant may help with that course of. For instance, if it's good to troubleshoot routing adjacencies, you’ll possible want to assemble information from a number of gadgets and correlate the info to establish a root trigger.

You're a community troubleshooting assistant. Assist me diagnose why my OSPFv3 session will not be establishing with one neighbor. That is the output from ‘present ospfv3 neighbor’:

OSPFv3 1 address-family ipv6 (router-id 192.0.2.1)

Neighbor ID Pri State Useless Time Interface ID Interface 192.0.2.2 128 EXCHANGE/BDR 00:00:38 13 Vlan300 192.0.2.6 128 FULL/DR 00:00:37 5 Vlan300 And that is the related config from Vlan300: ipv6 tackle FE80::300:241 link-local ipv6 tackle 2001:DB8::241/64 ipv6 allow ipv6 mtu 1500 ipv6 nd dad makes an attempt 0 ipv6 nd ra suppress all no ipv6 redirects ipv6 ospf 1 space 0 bfd interval 1000 min_rx 1000 multiplier 5

Right here’s the response I obtained:

In some unspecified time in the future, many people find yourself troubleshooting on the protocol degree (packet seize or it didn’t occur, proper?), the place issues get advanced in a short time. On this case, you possibly can paste the decoded output of a packet seize (corresponding to that from Wireshark or Tshark) to the Deep Community Mannequin AI Assistant, which may break down the body particulars for you. It may establish hard-to-spot points and dramatically improve the efficacy of deep networking troubleshooting.

The AI assistant may give you extra that means and context than you may get with different instruments. I attempted this with a problematic SNMPv3 packet. The AI assistant seemed on the worth of the fields and defined them to me. Whereas Wireshark confirmed me the sector names, the AI assistant defined that one subject, the msgAuthoritativeEngineTime, represented the variety of seconds a tool had been on-line, which was 61411 (roughly seven weeks). The factor is, I simply booted that gadget. So my SNMP supervisor was confused, and the SNMPv3 lure wasn’t being trusted. Bug discovered!

Whereas most of us are fairly accustomed to a variety of community applied sciences, we might not be specialists in each one of many protocols we run on our community. Subsequently, think about how helpful this may be for a protocol you’re not extremely educated about on the subject degree. The AI assistant is superb at analyzing these fields and explaining their network-relevant context. Whereas the assistant received’t resolve the issue for you, when used correctly, it may give you some good hints. When you perceive extra about these fields, making use of some reasoning and fixing the bug is way simpler.

These are simply a number of the ways in which the Deep Community Mannequin AI Assistant might be useful to skilled community engineers. I hope they’re a helpful springboard in your considering. Should you strive them out, I’d be excited to listen to concerning the outcomes you’re getting.

However I’d be much more excited to listen to about use instances you’ve give you that I'd by no means consider. AI is an extremely highly effective device that may make us extra environment friendly and, frankly, much less pressured. However we should work out one of the best methods to make use of them, and we’re all on that journey collectively.