AI + Observability: AI Agents, LLMs, Apps, & Infrastructure
The rapid evolution of artificial intelligence is fundamentally changing how engineering teams build and operate modern digital services. As organizations increasingly adopt large language models (LLMs) and agentic AI, the demand for observability is reaching a critical inflection point. Teams are now tasked with a dual challenge: they must gain deep visibility into the complex behavior, cost, and reliability of AI applications, while simultaneously harnessing AI to simplify incident response and eliminate the manual toil of managing distributed, heterogeneous environments.
Our new four-part event series, AI + Observability: AI Agents, LLMs, Apps, & Infrastructure, explores these two sides of the transformation, providing the technical framework and hands-on guidance necessary to succeed in the agentic era.
What We’ll Cover
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Deep Visibility into AI Performance and Economics: Gain a comprehensive understanding of your AI ecosystem by learning to monitor the entire stack, from cloud infrastructure and retrieval pipelines to model prompts and tool calls. We will explore "Born Observable" strategies, showing you how to bake telemetry into AI applications from development to production, enabling precise control over token consumption, model latency, and overall AI spend.
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Intelligent Automation for SRE Workflows: Discover how to integrate conversational AI directly into your incident management lifecycle. By leveraging the AI Assistant within Splunk Observability Cloud, practitioners can query logs, charts, and traces using natural language, significantly accelerating root cause analysis across complex microservices and distributed infrastructure without needing to be deep-domain specialists.
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Practical Implementation and Hands-On Experience: Move beyond theory with a guided technical laboratory session designed to refine your troubleshooting skills. You will work within a live Kubernetes cluster to practice instrumenting and monitoring microservice applications, leaving the session with a permanent Free Edition instance to continue exploring advanced features like database monitoring and secure application protocols.
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Collaborative Technical Strategy Sessions: Engage in a focused forum for addressing your specific technical challenges and implementation strategies. Whether you are currently optimizing an existing LLM workflow or evaluating where to begin, this series facilitates direct interaction with technical specialists, allowing you to troubleshoot real-world implementation hurdles and align your monitoring strategy with your organization’s broader business goals.
Event Schedule and Highlights
1. Webinar: Agent Observability with AWS and Splunk: Optimize AI Performance and Cost
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Date: September 22, 2026 | 10:00am – 11:00am PT
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Focus: Learn to manage the distributed complexity of AI applications. We will demonstrate how to simplify OpenTelemetry instrumentation using the Splunk Observability Studio and how to utilize runtime guardrails to prevent inaccurate or harmful AI outputs.
2. Tech Talk: AI Assistant in Observability Cloud: The Conversational Core of Your AI SRE
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Date: September 30, 2026 | 12:00pm – 1:00pm PT
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Focus: Explore the AI Assistant, the conversational core of your AI SRE strategy. See live demonstrations of how to generate charts, investigate health dependencies, and streamline incident response using plain-language queries.
3. Interactive Lab: Solve Problems Faster with Splunk Observability Free Edition
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Date: October 1, 2026 | 10:00am – 11:30am PT
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Focus: A high-intensity workshop for troubleshooting complex microservice applications. You will perform hands-on configuration of APM and synthetic monitoring, setting the foundation for your own production-grade observability implementation.
4. Strategy Session: AI + Observability Office Hours: Ask the Experts
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Date: October 6, 2026 | 11:00am – 12:00pm PT
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Focus: A dedicated session to discuss the practical realities of monitoring AI workloads. Bring your questions regarding architectural implementation, token usage patterns, and the integration of AI-guided remediation in hybrid environments.
Register now to join these sessions and start building systems you can trust at scale.
