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From Siloed Operations to
Unified Agentic Operations

AI Agents to Break Silos: Need Unified Control Plane & Agentic Data Federation

Pulished: February 27th, 2026
Raju Datla
CEO, Fabrix.ai

Enterprise IT and SRE operations today are deeply fragmented. Most organizations operate more than twenty monitoring and observability tools spanning cloud-native applications, traditional enterprise systems, infrastructure, networks, and security. Each platform focuses on a specific domain - APM, NPM, SIEM, cloud, or infrastructure, forcing operations teams to manually swivel between dashboards to correlate signals and determine root cause. This “swivel chair” problem slows incident response, increases operational complexity, and prevents true automation. As enterprises move toward autonomous operations, this siloed approach is no longer sufficient.

Siloed Approach (Siloed Operations to Siloed Agentic Operations):

The Swivel Chair problem: SREs and IT Ops teams jump between dashboards, alerts, and consoles trying to correlate signals manually. Root cause analysis becomes a human stitching exercise across siloed systems. Mean time to resolution increases. Productivity declines. Automation stalls.

In response, many observability vendors have introduced AI agents. However, in most cases these agents are simply layered on top of existing siloed platforms. The underlying architecture remains unchanged. Each vendor’s agent operates within its own ecosystem, without the ability to reason across domains or orchestrate multi-vendor workflows. The result is not unified operations, it is siloed intelligence.

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Desired Approach by Enterprise Leaders

What enterprises actually want is end-to-end, unified agentic operations. They expect AI agents to seamlessly connect cloud, infrastructure, network, and security systems, correlate signals across domains, and drive faster root cause analysis and remediation. The goal is not another layer of dashboards, but autonomous execution across the entire IT estate.

  • One AI touch point, not dealing with too many tools
  • Unified Control Plane
  • Federate across data silos
  • Orchestrate across multiple agents
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Typical Approaches:
Centralization Trap

Some vendors attempt to solve this by asking enterprises to re-ingest all operational data into a single centralized platform. In practice, this approach is expensive and disruptive. It requires architectural redesign, increases data storage and processing costs, and still does not inherently deliver automation or auto-remediation. Centralization adds cost without eliminating silos.

Re-ingest back to one platform.
  • Limited support for data ingestion
  • Architectural redesign
  • Significant increase in data costs
"Send Us All the Data" - Significant Architectural Impact
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Other approaches fall short
  • Manual federation is not scalable: Mapping data schemas across multiple tools and domains requires ongoing customization, brittle integrations, and constant maintenance, slowing time to value.
  • Cloud native only focus is incomplete: Vendors built solely around OpenTelemetry and cloud-native stacks ignore the majority of enterprise workloads(75%+) that still run on traditional infrastructure.

Fabrix Approach

Unified Agentic Operations: Cross-domain & Multi-Vendor

Fabrix takes a fundamentally different approach through Agentic Data Federation powered by ontology and orchestration. Instead of moving data, Fabrix keeps data where it resides and deploys federation agents across existing observability platforms. By building a cross-domain enterprise ontology and orchestrating workflows across vendors, Fabrix enables automated remediation without forcing enterprises to re-architect their environments. This creates true unified agentic operations, not bolt-on intelligence, but coordinated, cross-domain autonomy.

The future of IT operations is not siloed monitoring or centralized data lakes. It is federated, cross-domain, autonomous operations. That is the shift enterprises are demanding and the shift Fabrix is delivering.

The following white papers provide a deep dive into our Agentic Federation approach and outline a modern agentic architecture designed to address 16 critical production breaking points.
Unified Agentic Operations: Unified Control Plane &
Agentic Data Federation
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Three Layers, Working Together
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Example Case Study:

Problem Statement

Large enterprises run their IT environments across dozens of specialized tools and teams: application monitoring, infrastructure, security, network. Each team owns their domain. Nobody owns the seam between them. When something breaks across that seam, which is exactly when it matters most, the diagnosis becomes a coordination problem as much as a technical one.

Situation

At 2:14 AM, a payment processing service breaches its latency SLA. Three teams are paged. Each opens their own dashboards, sees their own slice of the problem, and finds nothing obviously wrong in their domain. Forty minutes later they're on a bridge call, trading screenshots, trying to agree on which signal matters.

The actual cause (a storage controller degradation cascading through shared infrastructure into application thread exhaustion) sits invisible across the boundary between two teams' toolsets. Assembling the picture requires someone who knows that a VM name in one system maps to a hostname in another, which maps to a service dependency in a third. That knowledge doesn't exist anywhere except in the heads of senior engineers. At 3 AM. Under pressure.

This is how enterprises lose hours on incidents that should take minutes.

Solution

Fabrix.ai's RCA Agent resolved the same incident in under six minutes, without a bridge call, without manual correlation, and without touching the existing tool stack.

The reason it could move that fast is the Ontology Layer. Before the agent ever ran, Fabrix.ai built a graph-based map of the enterprise data landscape: every data source, every entity type, and critically, how they relate across systems. The agent knew that the affected microservices ran on specific VMs, that those VMs shared a datastore, and that the storage controller had a corresponding record in infrastructure monitoring. That knowledge was encoded once, not reconstructed at 3 AM by an exhausted engineer.

When the alert fired, the agent traced the full causal chain across five systems in four minutes, surfaced a ranked root cause with evidence, and filed a remediation ticket with the complete diagnostic trail. The Infrastructure team woke up to a resolved incident.

Mean time to resolution: from 47 minutes to under six. No new infrastructure. No centralized data warehouse. Just agents that know the lay of the land before they start working.

Customer Environment
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Fabrix RCA Agent Orchestration
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“The Fabrix RCA Agent identified a critical VPN configuration change impacting applications accross an entire region in minutes. In the past, it would have taken multiple teams hours of cross-tool investigation to uncover the root cause.” - Network Ops Director