Cloud Control — Interactive Solution Brief
CISCO Next Generation Observability Interactive Solution Brief
Cloud Control · Observability Cloud · Galileo

Next-Level Observability.
Built for the AI Era.

Three core concepts that explain why Cloud Control, Observability Cloud, and Galileo are the foundation customers need to operate at AI scale — with cross-domain insight, predictable data economics, and trusted oversight of every LLM and agent in production.

Concept 01 · The Foundation

Single-Domain Views Create Dangerous Blind Spots.

Modern incidents span security, network, infrastructure, application, and user behavior simultaneously. Looking at one domain at a time produces a confident-but-wrong answer. Correlated views surface the actual root cause.

Live Incident Simulation · PseudoCo Branch 47
Click each domain to see what it sees in isolation

Symptom: Users report slow checkout. 4 monitoring tools are firing. None of them agree on what’s wrong.

🛡️
Security
SCC, AI Defense, Secure Access
🌐
Network
ThousandEyes, Meraki, SD-WAN
📱
Application
AppDynamics, Splunk O11y
🖥️
Infrastructure
Intersight, Nexus Dashboard
⬆ Click a domain above to see its conclusion in isolation.
75%
MTTR reduction with unified cross-domain observability (Apica)
>95%
reduction in mean time to root cause with AI correlation
84%
of organizations pursuing observability tool consolidation (LogicMonitor 2026)
10+
monitoring tools the average enterprise has to reconcile manually
12 hrs
per week wasted chasing data across siloed systems (Forrester)
30%
of breaches go fully undetected by single-domain security tools

Cloud Control · AgenticOps in Action

Sam Ali starts her day with one login. One inventory and topology. One view for alerts. One AI Assistant. And AI Canvas embedded inside Cloud Control — the multiplayer workspace where human operators and AI agents investigate and remediate cross-domain incidents together, grounded in platform data and policy.

Launch Cloud Control Demo
Concept 02 · Modernization Lands on the AI Factory

App Modernization Becomes Code Sprawl — And It Lands on Your AI PODs.

AI agents ship apps, configs, and pipelines at machine speed. The sprawl doesn’t stay in the codebase — it lands on GPUs, CPU, memory, and tokens inside the AI Factory. Observability Cloud is native to Cisco AI PODs: see the impact of AI workloads at the hardware layer, before silent failures cascade through the stack.

AI-PoD Telemetry · Infrastructure Impact Simulation
Scale AI activity, then flip observability mode to see the hardware
Modernization Mandate
1 strategic intent
AI Agents · Code Sprawl Engine
12 agents shipping apps, configs, pipelines
Landing on Cisco AI PODs
288 workloads · GPU / CPU / memory / tokens
PilotTeam-scaleEnterprise-wide
Observability: App tier only · Hardware is dark
Legacy 3-tier observability stops at the app. No view into AI-PoD GPU, CPU, memory, or token spend. Silent failures cascade.
87%
GPU Utilization
82%
Memory Utilization
$245
Token Cost / Day
1.8 hrs
Agentic MTTD
No
AI-PoD Visibility

Observability Cloud · Native to Cisco AI PODs

Splunk AI Infrastructure Monitoring built into the AI Factory. The Splunk Distribution of OpenTelemetry Collector pulls metrics and metadata from NVIDIA GPUs, NVIDIA NIM, Cisco UCS, Cisco Nexus, and certified storage — surfaced through purpose-built dashboards. App, agent, and silicon in one pane — with the Cisco Data Fabric and Time Series Foundation Model exposing AI-ready intelligence at any scale.

Launch Observability Cloud Demo
Concept 03 · The Economics

If You Hand AI Raw Data, You Pay for It on Every Query.

Today's default AI architecture — point the model at every API and MCP server — forces the model to rediscover, gather, and correlate data on every single call. Costs scale with environment size. A tiered data strategy in the Cisco Data Fabric shifts that work upstream, once.

Token Cost Simulator
Drag the slider to scale the environment
Small business (50)Mid-marketLarge enterprise (250K)

Direct API / MCP Access Status quo

AI queries raw endpoints, rebuilds context on every call
28,400 tokens / query
$2.07 per query Latency: 8.2s

Cisco Data Fabric (Tiered) Proposed

Pre-cataloged, correlated, pre-mapped relationships exposed as one clean layer
1,420 tokens / query
$0.26 per query Latency: 0.4s
20x
token efficiency at 5,000 entities — flat cost per query, regardless of scale
Industry-validated: Graph-based and pre-correlated approaches deliver 80–97% token reduction vs. raw retrieval. Cisco Data Fabric pushes that into production at enterprise scale.
3–20x
token efficiency gains from pre-tiered, correlated data (small to large environments)
80–97%
token reduction in graph-based RAG approaches (TERAG, GraphRAG)
78x
average accuracy improvement from pre-processed, deduplicated structures (Blockify on Dell)
67%
YoY token cost drop for enterprises using tiered intelligence stacks (top performers: 80–87%)

Onstak · Our Ecosystem Partner for Intelligent Correlation

Onstak has built a production-ready Intelligent Correlation solution on top of the Cisco Data Fabric and the architecture in this brief — pulling sources, correlation, and audit trail out of the AI “black box.” If you want help applying these concepts in your environment, their team can scope, deploy, and operate it alongside you.

Connect with Onstak
Concept 04 · The Trust Layer

When Agents Build the Enterprise, Observability Becomes Non-Negotiable.

LLMs and autonomous agents introduce failure modes traditional monitoring cannot see — hallucinations, drift, runaway token spend, wrong-but-confident actions that return a 200 OK. Cisco acquired Galileo in April 2026 specifically to close this gap.

Agent Fleet Simulation
Toggle observability and scale the fleet
AI Observability: OFF
Agents run unmonitored. Failures look like successes. Issues only surface after customers complain.
Pilot (10)Team (500)F500 fleet (150,000)
Legend Active agent (operating normally) Silent failure (observability OFF — undetected) Caught failure (observability ON — contained)
200
Active agents
24
Silent failures
$8,400
Wasted tokens / day
9.2 hrs
Time to detect
150K+
agents the average Fortune 500 enterprise is projected to manage by 2028
60%
of software teams will use AI eval and observability platforms by 2028 (Gartner, up from 18% in 2025)
40%+
of agentic AI projects risk failure without proper governance and visibility
6x
higher production success rate for AI agents with strong eval frameworks
97%
lower cost vs. LLM-as-judge with Galileo's Luna-2 small evaluator models
32%
of orgs cite quality as the top barrier to agent deployment (observability is the answer)

Galileo · Agentic Ops Platform

End-to-end agent tracing, graph views of decision flows and tool calls, specialized metrics (Action Completion, Tool Selection Quality, Reasoning Coherence, Agent Flow), and runtime Protect guardrails that catch harmful or off-policy outputs before they reach users.

Launch Galileo Demo
The Big Picture

Four Concepts. One Cisco Architecture.

Cross-domain visibility, observability modernization, organized data economics, and agentic trust aren’t four separate products — they’re four layers of the same architecture. Here’s how the demos you’re about to see fit together.

1. Domains 2. Management 3. Data Fabric 4. Correlation 5. AI & Agents 6. Insights
Click Reveal Next Layer to walk the architecture from the bottom up — Domains, then Management, then Data Fabric, then Correlation, then AI & Agents, then Insights.
Insights: Cloud Control — The Unified Operations Front Door
CLOUD CONTROL
One Login
Unified Inventory & Topology
Actions (Correlated Alerts)
AI Assistant
AI Canvas embedded
AI & Agents
Any AI · Cisco LLMs
Any Agents · Cisco Agents · Galileo · AI Defense
Correlation
Intelligent Correlation Engine · MCP · Automation Run Books
Data Fabric
Cisco Data Fabric · Meta Data Catalog · Unified Telemetry · Time Series Data
Management
MicroservicesO11y
3-Tier AppsAppD
EventsITSI
WANThousandEyes
SwitchingCatalyst Center
DatacenterNexus DB
Team MessagingWebEx
Collab. DevicesControl Hub
Contact CenterCCE
OTELSplunk
Security PolicyXDR
Security DevicesSCC
Domains
Apps
Network
Collaboration
Security
Experience It Live

Four Demos. One Conversation.

Cross-launch into any of the four demo environments to see the concepts in action.

Concept 01 · Cross-Domain Insights

Cloud Control

AgenticOps in action: one login, one topology, one alert view, and AI Canvas (embedded in Cloud Control) where operators and agents resolve cross-domain incidents together.

Launch Cloud Control Demo

Concept 02 · Modernization on AI PODs

Observability Cloud

Native to Cisco AI PODs. Splunk AI Infrastructure Monitoring exposes GPU, CPU, memory, and tokenization cost as agents ship code at machine speed — from app, to agent, to silicon.

Launch Observability Cloud Demo

Concept 03 · Tokenomics

Onstak · Intelligent Correlation

Our ecosystem partner Onstak has built an Intelligent Correlation solution on top of this Cisco architecture — AI query volume drops, quality rises, and every answer comes with an audit trail. Connect with their team to scope your deployment.

Connect with Onstak

Concept 04 · Agentic Ops

Galileo

Agent traces, evaluation metrics, and runtime Protect guardrails that stop hallucinations, off-policy actions, and silent failures before they reach customers.

Launch Galileo Demo
Estimate Savings · Build Your Number

What This Architecture Is Worth to You.

Three architectural levers. One annual token line item. Toggle the ones you’re evaluating, drop in your planned spend, and see exactly where the dollars and the operating wins land.

Annual Tokenization Cost Reduction
Plan your AI investment against the three Cisco architecture cost levers
New Annual Budget
$176,055
After the levers you’ve selected apply
Total Annual Savings
$323,945
64.8% reduction vs. current spend
92%
Deployment Success Rate
From a 70% baseline — fewer rollbacks, less rework
18hrs/wk
Ops Time Saved per Engineer
Cross-domain correlation kills the swivel-chair
55%
MTTR Reduction
Agent guardrails + tiered data shorten incidents
Savings ranges modeled from internal Cisco lab testing and published industry benchmarks (graph-RAG token reduction studies, agentic-failure cost analyses). Actual results vary by workload mix.
Cloud Control · Observability Cloud · Galileo  ·  Interactive Solution Brief  ·  For customer use during Cisco events