Build Reliable, Cost-Effective Agents with Splunk Agent Observability

AI needs oversight. Agents can behave and fail in unpredictable ways that erode customer trust and create large bills before engineering teams know anything is wrong. The non-deterministic behavior of agents drives increased risk of security, privacy, and compliance incidents.

Teams want to deploy agents into critical business workflows but are faced with a wall of unpredictability: runaway token costs, more complex infrastructure, opaque governance rules, and a complete lack of visibility into "black box" agent behavior.

In this webinar we’ll show you how Splunk Agent Observability (powered by the acquisition of Galileo) delivers end-to-end visibility to monitor the performance, security, and cost of the entire AI stack, from agents and large language models (LLMs) to the underlying infrastructure.

In this session, you will learn about how Agent Observability helps teams:

[li indent=0 align=left]Observe performance across the entire AI stack to diagnose failures or errors by tracing dependencies, analyzing workflows, and tracking SLOs like latency and error rates [li indent=0 align=left]Evaluate agent behavior from development through production with live evals that transition to cost-effective guardrails at scale [li indent=0 align=left]Track tokenomics to understand how resources like GPUs and tokens are being used, optimize affecting costs, and correlate with quality and business value to ensure ROI [li indent=0 align=left]Block sophisticated prompt-injection attacks, and inaccurate or harmful responses with custom SLM-powered guardrails