Three Domains. One Nervous System. AI-powered observability, Zero Trust, and AI-ready networking — designed together AI OBSERVABILITY Splunk · ThousandEyes · AppD ZERO TRUST XDR · FTD · Duo · ISE · Umbrella AI-READY NETWORK Catalyst Center · SD-WAN · WiFi 7 AI CORRELATION LAYER one signal from every domain · predictive, not reactive
AI Operations · Jul 2026

Designing AI-Powered Observability: From Alert Noise to One Signal

Rajmohan M
Principal Consultant, UC & Contact Center
4 min read · July 2026
AI-Assisted Documentation

Enterprises rarely lack monitoring — they lack agreement between their monitors. The network tool, the app tool, and the security tool each see a fragment of the same incident and raise three unrelated alerts. This design makes them tell one story.

The platform is designed as three integrated domains on the Cisco stack — AI-enabled observability, Zero Trust security, and an AI-ready network — built as an illustrative enterprise scenario. What makes it one platform rather than three deployments is the correlation layer they all feed. Here is the design, domain by domain.

01. Three domains, designed together

Each domain is a complete design on its own. The value comes from planning them as one system, so every platform lands with its telemetry integration already decided.

AI OBSERVABILITY Splunk ES + MLTK · SIEM & UEBA ThousandEyes · network intelligence AppDynamics Cognition · APM OpenTelemetry pipelines ZERO TRUST Cisco XDR · event correlation ASA → FTD migration · Duo ISE TrustSec segmentation Umbrella DNS · UEBA AI-READY NETWORK Catalyst Center AI/ML analytics SD-WAN predictive path selection WiFi 7 architecture AIOps & telemetry optimisation

02. The correlation hub: many alerts in, one incident out

Every telemetry source lands in the same place, where ML-based correlation turns overlapping fragments into a single incident with a probable cause — instead of three teams chasing three tickets for one outage.

Network telemetry · TE Application traces · AppD Security events · XDR Identity & access · ISE Correlation hub Splunk ES + MLTK · Cisco AI Ops ML clustering · UEBA · dedup One incident probable cause attached routed to the right team once The design goal: correlation absorbs the alert flood so people only see incidents worth their attention.

03. From reactive to predictive

The deeper shift is in the timeline. Traditional operations start the clock when a user complains; this design starts it when the anomaly models see a trend bending — before impact, while the fix is still cheap.

REACTIVE user impact detect → triage → fix — clock starts too late PREDICTIVE anomaly detected ML trend analysis → act before users feel anything impact avoided Design targets of the documented platform: 90% lower mean time to detect, 85% fewer false positives through AI correlation.

04. Security feeds the same brain

Zero Trust here is not a parallel project. XDR correlates security events, TrustSec and Duo decide who reaches what, Umbrella filters at DNS — and every one of those decisions lands in the same correlation hub as the network and application telemetry, following NIST 800-207 principles.

FTD firewalls Duo · identity MFA ISE TrustSec · SGTs Umbrella DNS Cisco XDR security correlation → shared hub Automated response response flows back to the enforcement points — quarantine, block, re-authenticate

05. A network that gets ready for AI on its own

The third domain closes the loop: Catalyst Center's AI/ML analytics baseline the network's own behaviour, SD-WAN selects paths predictively rather than after brownouts, and the WiFi 7 design carries the density AI endpoints bring. The network stops being what the tools watch — it becomes one of the intelligent participants.

Where AI fits in

Three domains means three full design guides — platform architectures, integration matrices, and implementation checklists. Claude helped me draft that volume consistently, while the domain boundaries, the correlation-first design decision, and the platform selections are mine. Every page passed the same strict build gate as the rest of this portfolio.

Explore the full design

Each domain above unfolds into complete documentation — the Splunk and ThousandEyes architectures, the AppDynamics Cognition design, OpenTelemetry pipelines, the full Zero Trust framework with the ASA-to-FTD migration strategy, and the AI-ready network chapters. Built as an illustrative enterprise scenario so the structure and decision logic are fully visible.

Full Documentation Site

Cisco AI Observability & Security Platform Design

All three domains, published as a browsable site.

Open the Platform Design →
AI-assisted disclosure: This article and the documentation site it references were produced with AI assistance (Claude, Anthropic) under the author's technical direction, as part of the AbhavTech knowledge-sharing portfolio. Content is illustrative and intended for learning; performance figures are design targets of the documented scenario — validate all designs against official Cisco documentation and your own environment before production use.