Operations | Monitoring | ITSM | DevOps | Cloud

Close the AIOps loop with Splunk Observability Cloud and Red Hat Ansible Automation Platform. Explore how OpenTelemetry and Event-Driven Ansible turn alerts into automated fixes, reducing manual firefighting and speeding up incident resolution.

Most teams keep an agent from regressing by hardcoding checks into its logic, an if-statement here, a regex there. Every new rule then becomes a code change, a review, and a deploy, and the person who spots the problem in production is rarely the person who can ship the fix. Agent Control moves those rules out of the code and into one hub. Steer, block, and validate agent behavior in real time, with rules any team member can update without touching the codebase.

Your agent breaks in production. You fix it and move on. But the input that actually broke it is gone and two months later the same failure quietly comes back, because there was never anything to test against. That's not a debugging problem. It's a missing dataset. This demo turns low-scoring production traces into a regression suite you can run against every prompt and model change, without writing a single test case by hand.

Every engineering team has unit tests. They tell you the code still works. They tell you nothing about what the model started saying. This demo wires a single eval gate script into a git pre-push hook, so Splunk Agent Observability scores every agent's output before the push is allowed through. Luna, an on-premise small language model, runs as a synchronous judge against fixed thresholds. Fail one, and the push is blocked.

Agentic AI is transforming the enterprise, but its success hinges on one critical factor: trust. Without robust governance, auditability, and a unified data foundation, scaling AI safely remains out of reach.

What exactly are your agents up to? See how Cisco and Splunk help you trace every decision and control your costs.

Episode 1, "Beyond the Thread: Deconstructing the Cisco Data Fabric Powered by the Splunk Platform," explores the intersection of data strategy and operational efficiency. Hosted by Splunk's Courtney Wright, the session features insights from experts Keith McClellan and Michael Sondag on the complexities organizations face in data management and operational models.

Episode two of Beyond the Thread explores how organizations can leverage a solid data foundation for AI-driven actions. Hosted by Courtney Wright and featuring experts Greg Ainsley-Malik and Sonal Pardeshi, the discussion delves into the Cisco Data Fabric, powered by the Splunk platform, and its role in transforming machine data into actionable insights. The episode highlights the journey towards agentic operations, addressing the challenges faced in moving from AI-ready data to effective implementations, and examines different adoption strategies that organizations may pursue.

Your competitive edge isn't the model; it's the data that only you have. Sonal Pardeshi, Head of AI Product at Splunk, explains why teams building on general-purpose models keep arriving at the same generic outcomes, and what changes when agents are grounded in your own machine data and your own governance. AI Toolkit and Agent Launchpad let teams build and run agents against your grounded data.

See how Splunk delivers end-to-end visibility across payment rails — monitoring transaction flows in real time to catch failures, latency, and anomalies before they hit customers. Learn how financial institutions use that insight to protect uptime, reduce fraud risk, and keep every payment moving.