At Cisco Reside 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 skill 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 Consultants the chance to work with the Deep Community Mannequin as quickly as potential. So we’re making the mannequin out there to CCIEs and different consultants by way 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 can assist them study extra and develop into extra environment friendly. However we notice that agentic ops is model new, and that you simply may be questioning how one can instantly begin experimenting with the Deep Community Mannequin. So I believed I’d provide some pattern use circumstances that can assist you get began.
Tailor-made eventualities and coaching paths
As a CCIE, you’ve acquired years—generally a long time—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 eventualities and coaching concepts so that everybody in your workforce can study the abilities 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 would possibly attempt a immediate comparable to this one:
- I’m the tech lead for a small workforce of community engineers. I have to rapidly 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 acquired 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 way of them. However generally you want extra steering. The Deep Community Mannequin AI Assistant can assist make CVDs extra navigable. It could possibly entry different sources to assist flesh out CVDs and provide options for bettering or optimizing designs.
It could possibly 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 comparable 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 can assist validate an current design with respect to a CVD and provide options for bettering or optimizing designs.
- What sort of storage know-how 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 may 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 would ask it questions comparable to:
- I’m an skilled in community structure and wish some assist automating our department SD-WAN deployment. What could be a well-supported, easy-to-learn device that will assist me help this? My workforce doesn’t have an excessive amount of coding expertise. May you present examples and hyperlinks to related documentation and coaching?
Troubleshooting
The Deep Community Mannequin AI Assistant can assist analyze community diagnostics, comparable to syslog messages and debug output, and look at downside signs to offer perception that may 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 judge 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 can provide steering 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 may describe the symptom you see after which ask, “What ought to I search for?” (After all, you need to at all times watch out about pasting uncooked output into AI.) On this approach, you should use the assistant to information you to the purpose the place you’re snug taking on.
Lots of debugging is actually several types of diagnostic information and looking for the needle in a haystack that may assist what to do subsequent. The Deep Community Mannequin AI Assistant can assist with that course of. For instance, if it’s essential to troubleshoot routing adjacencies, you’ll doubtless want to collect information from a number of gadgets and correlate the information to establish a root trigger.
You are a community troubleshooting assistant. Assist me diagnose why my OSPFv3 session just isn’t 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 Lifeless 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 deal with FE80::300:241 link-local ipv6 deal with 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 acquired:
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 may paste the decoded output of a packet seize (comparable to that from Wireshark or Tshark) to the Deep Community Mannequin AI Assistant, which might break down the body particulars for you. It could possibly establish hard-to-spot points and dramatically enhance the efficacy of deep networking troubleshooting.
The AI assistant can provide 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 seemed on the worth of the fields and defined them to me. Whereas Wireshark confirmed me the sphere 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 system. So my SNMP supervisor was confused, and the SNMPv3 entice wasn’t being trusted. Bug discovered!
Whereas most of us are fairly accustomed to a variety of community applied sciences, we is probably not 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 subject degree. The AI assistant is superb at analyzing these fields and explaining their network-relevant context. Whereas the assistant received’t remedy the issue for you, when used correctly, it can provide 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 may very well be useful to skilled community engineers. I hope they’re a helpful springboard to your pondering. In the event you attempt them out, I’d be excited to listen to in regards to the outcomes you’re getting.
However I’d be much more excited to listen to about use circumstances you’ve provide you with that I would by no means consider. AI is an extremely highly effective device that may make us extra environment friendly and, frankly, much less careworn. However we should determine the very best methods to make use of them, and we’re all on that journey collectively.
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