Monitoring Agentic AI Applications with Splunk Observability Cloud

Splunk Observability for AI monitors the performance, quality, security, and cost of AI application stack. It includes the following:

• AI Agent Monitoring, which monitors the performance, quality, security, and cost of LLM and agentic applications.
• AI Infrastructure Monitoring, which monitors the health, availability, and consumption (or usage) of AI infrastructure.

This workshop provides hands-on experience deploying and working with these capabilities in Splunk Observability Cloud. This includes:

• Understanding how to connect an Azure account to Splunk Observability Cloud to capture AI infrastructure-related metrics.
• Exploring out-of-the box dashboards and navigators related to AI infrastructure.
• Reviewing the architecture of an Agentic AI application built with LangChain and LangGraph.
• Practice deploying an Agentic AI application and instrumenting it with OpenTelemetry.
• Exploring how metrics, traces, and logs can be used in Splunk Observability Cloud to understand agent performance.
• Practice modifying an Agentic AI application to use tool calls and agents.
• Practice adding quality issues to an application and detecting them with Splunk Observability Cloud using semantic quality evals.
• Practice adding AI Defense instrumentation to the application and security risks, and detecting them with Splunk Observability Cloud.