At Cisco Stay in San Diego, D.J. Sampath, Senior Vice President of Cisco’s AI Software program and Platform group, wowed the gang 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 may all see AI Canvas’s potential to hurry troubleshooting, carry siloed groups collectively, and allow automation throughout all the stack.
AI Canvas received’t be out there till October. Nevertheless, we needed to supply our CCIEs, CCDEs, and Cisco Licensed DevNet Specialists 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 consultants by means of an AI Studying Assistant out there in Cisco U.
We predict CCIEs (and shortly, different community engineers) will discover a wealth of ways in which the Deep Community Mannequin might help them study extra and turn out to be extra environment friendly. However we understand that agentic ops is model new, and that you simply could be questioning how one can instantly begin experimenting with the Deep Community Mannequin. So I believed I’d supply some pattern use instances that will help you get began.
Tailor-made eventualities and coaching paths
As a CCIE, you’ve received years—generally many years—of expertise in networking, and also you’re totally in control in your group’s IT infrastructure. However what about your crew members, particularly extra junior community engineers? The Deep Community Mannequin AI Assistant can be utilized to construct tailor-made eventualities and coaching concepts so that everybody in your crew can study the talents wanted for the community you at the moment 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, but it surely’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 would possibly strive a immediate resembling this one:
- I’m the tech lead for a small crew of community engineers. I have to shortly get them in control on the networking expertise we use in our surroundings, together with BGP, MPLS, and OSPF. Might you construct me a customized research plan?
After I requested this query of the Deep Community Mannequin AI Assistant, I received 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 by means of them. However generally you want extra steerage. The Deep Community Mannequin AI Assistant might help make CVDs extra navigable. It could actually entry different sources to assist flesh out CVDs and supply options for enhancing or optimizing designs.
It could actually additionally summarize the CVD, providing you with a high-level overview earlier than studying the entire thing. You may ask it questions resembling:
- 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. Might 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 might help validate an current design with respect to a CVD and supply options for enhancing or optimizing designs.
- What sort of storage expertise ought to I take into account for booting my blades in a UCS B chassis?
In the event you’re having points with a CVD, you’ll be able to ask the Deep Community Mannequin AI Assistant the place you need to begin wanting.
Automation assistant
The Deep Community Mannequin AI Assistant may also assist with automation. You could possibly ask it questions resembling:
- 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 software that will assist me help this? My crew doesn’t have quite a lot of coding expertise. Might you present examples and hyperlinks to related documentation and coaching?
Troubleshooting
The Deep Community Mannequin AI Assistant might help analyze community diagnostics, resembling syslog messages and debug output, and study downside signs to supply perception that could be missed by human eyes. Though generative AI remains to be a younger expertise 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 may assist interpret a syslog message. You could possibly merely enter the message into the assistant and say you want recommendation or a spot to begin. As a result of it’s educated on Cisco’s syslog codecs, it may give steerage and cross-reference different information.
In the event you’re working with a number of information sources, the evaluation turns into extra advanced. With the Deep Community Mannequin AI Assistant, you’ll be able to describe the symptom you see after which ask, “What ought to I search for?” (In fact, you need to all the time watch out about pasting uncooked output into AI.) On this manner, you should utilize the assistant to information you to the purpose the place you’re comfy taking on.
Numerous debugging is basically various kinds of diagnostic information and looking for the needle in a haystack that can assist what to do subsequent. The Deep Community Mannequin AI Assistant might help with that course of. For instance, if you should troubleshoot routing adjacencies, you’ll doubtless want to collect information from a number of gadgets and correlate the info to determine a root trigger.
You are 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 received:
Sooner or later, 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’ll be able to paste the decoded output of a packet seize (resembling that from Wireshark or Tshark) to the Deep Community Mannequin AI Assistant, which might break down the body particulars for you. It could actually determine hard-to-spot points and dramatically improve the efficacy of deep networking troubleshooting.
The AI assistant may give you extra which means and context than you would possibly get with different instruments. I attempted this with a problematic SNMPv3 packet. The AI assistant regarded on the worth of the fields and defined them to me. Whereas Wireshark confirmed me the sector names, the AI assistant defined that one area, 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 will not be consultants in each one of many protocols we run on our community. Due to this fact, take into account how helpful this may be for a protocol you’re not extremely educated about on the area degree. The AI assistant is superb at analyzing these fields and explaining their network-relevant context. Whereas the assistant received’t clear up 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 far simpler.
These are simply among the ways in which the Deep Community Mannequin AI Assistant may very well be useful to skilled community engineers. I hope they’re a helpful springboard on your pondering. In the event 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 would by no means consider. AI is an extremely highly effective software that may make us extra environment friendly and, frankly, much less confused. However we should determine the perfect methods to make use of them, and we’re all on that journey collectively.
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