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OpsBot – Multi-Agent AIOps for SolarWinds & Enterprise Observability

rajasekar

🚀 OpsBot – Multi-Agent AIOps for SolarWinds & Enterprise Observability

OpsBot is a Multi-Agent, MCP & RAG-powered AIOps platform that brings SolarWinds and multiple enterprise observability/IT platforms into a single intelligent operations interface.

🤖 Multi-Agent AIOps

Specialized AI agents work together based on the request:

SolarWinds – SWQL/SWIS, NPM, NCM, SAM, nodes, interfaces, alerts, health and inventory
AppDynamics – application performance, agents, health rules, databases and policies
ThousandEyes – tests, alerts, network and external-path visibility
Cisco Catalyst Center/DNAC – devices, APs, PnP, health and issues
NetBox – DCIM/IPAM and source-of-truth validation
ServiceNow – incidents, events and CMDB correlation
Splunk – operational data and forwarder workflows
NetTools – DNS, Ping, TCP and Traceroute
Knowledge & Analysis Agents – knowledge retrieval, analysis and correlation
Commander & Orchestrator – dynamically select and coordinate the required agents and tools

🔴 Live Agent Mission Control

Live Agent Flow provides real-time visibility into how each request is being handled:

User → Commander → Orchestrator → Agents → Tools/APIs → AI/LLM → Analysis → Response

Users can see:

Agent-to-agent communication • Active/Idle status • Current tasks • API/tool calls • Execution time • AI/LLM provider & model • Request tracking • Execution history

🔌 MCP + 📚 RAG

MCP (Model Context Protocol) provides an extensible approach for connecting agents with tools and operational capabilities.

RAG (Retrieval-Augmented Generation) provides context-aware knowledge using operational documentation, troubleshooting knowledge, runbooks, SWQL knowledge and other relevant information.

This allows OpsBot to combine:

RAG Knowledge + Live Monitoring Data + Multi-Agent Analysis

rather than depending only on an LLM.

🧠 Intelligent Multi-LLM Routing

OpsBot can choose the most appropriate execution path:

Deterministic Tools/SWQL → RAG/Knowledge → Enterprise LLM → Local LLM

Not every request needs AI. Simple queries can be handled directly through tools/APIs, while AI can be used for more complex analysis and correlation.

🔎 Cross-Platform Investigation & RCA

Multiple agents can investigate the same issue together.

For example:

“Investigate why Application X is slow.”

OpsBot can correlate information from:

SolarWinds + AppDynamics + ThousandEyes + DNAC + NetTools + RAG

to analyze application, infrastructure, network and external-path conditions together and assist with root-cause analysis.

🛠️ SolarWinds Intelligence

Capabilities include:

SWQL/SWIS • Node/Interface/Volume Monitoring • Alerts • Health Analysis • Interface Utilization • Anomaly Detection • NCM Configuration • Config Comparison • Backup Visibility • Topology • CI Comparison • Maintenance Operations • Inventory • Cross-Platform Search • Runtime SWIS Schema Discovery

🔗 Multi-Source Infrastructure Correlation

Infrastructure information can be correlated across:

SolarWinds ↔ Cisco Catalyst Center ↔ NetBox ↔ ServiceNow CMDB

helping identify inventory mismatches, missing CIs, retired devices still being monitored and source-of-truth differences.

⚡ Key Highlights

✅ Multi-Agent architecture
✅ MCP integration/extensibility
✅ RAG-powered knowledge intelligence
✅ Multi-LLM support and intelligent routing
✅ Live Agent Mission Control
✅ Cross-platform investigation & correlation
✅ SolarWinds SWIS/SWQL intelligence
✅ Zero installation
✅ Zero external runtime dependencies
✅ No administrator access required to run
✅ Portable

💡 Looking for Feedback

I’m continuing to enhance OpsBot and would love to hear ideas from the THWACK community.

If anyone is interested in AI OpsBot or would like to know more, please feel free to ping/message me. Suggestions and real-world use cases are very welcome! 🚀

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Comments

vinay.by

Nice post @rajasekar thanks for sharing, but how safe is this? Would major enterprises even allow this - keeping in mind the cyber security angle.

m_roberts

This is not what I believe you would have been shown in the Phoenix World Tour. That would have been the SolarWinds native version of this kind of solution, that would have been the SW1 platform.

i_like_eggs

Really interesting. The SolarWinds side stood out to me because there is already so much capability within Observability Self-Hosted.

These are some of the capabilities I use today, rather than future ideas. With a different operating model, I use Observability Self-Hosted to correlate related observations across alerts, metrics and monitored entities, identify repeating time patterns, and retain those patterns as structured memory.

The platform can also create anomaly-based alerting, build regression models to forecast almost any consistently sampled numeric metric, from NPM and SAM metrics through to hardware sensor values, apply recurrence and freshness rules to reduce noise, and present the resulting context through views, dashboards, reports and ticket payloads.

I can definitely see the value of AI as a conversational and orchestration layer. Ideally, an approach like this would work across both Self-Hosted and SaaS, with local, private or external models depending on the organisation’s security requirements.

Observability Self-Hosted is an incredibly powerful piece of software and genuinely deserves to be recognised as one of the very best observability platforms available.

The real constraint is usually the time, engineering effort and perspective applied to its data. That is often where I see the real gap, but that is just my perspective ✌️

ecklerwr1

I saw the preview of this live in Phoenix and it's pretty legit. I wish I could run it against our locally hosted LLM but it seems you have to have an outside connection to the SW model on the internet for it to work.

Quick Links

PALO-ALG - Logging
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