Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the evolution of observability in Large Language Models (LLMs) and AWS applications in this comprehensive conference talk. Delve into the fundamentals of observability, its significance in LLM contexts, and the distinction between direct and indirect LLM observability. Examine the observability maturity model for AWS Bedrock integrated applications, covering key pillars such as LLM-specific metrics, prompt engineering properties, and performance metrics for RAG models. Learn about visualization tools, incident management, security compliance, and cost optimization strategies. Discover the importance of a maturity framework and how to implement foundation-level LLM observability. Gain insights on measuring progress through business outcomes, best practices to follow, and common pitfalls to avoid in your journey towards advanced observability and AIOps capabilities.