Powering reliable AI agent creation with observability
As organizations scale AI adoption, conventional monitoring instruments are struggling to maintain up.
Long-lived connections, elevated error charges, and sophisticated real-time pipelines require observability constructed for the way AI methods really behave.
But many groups wrestle to pinpoint why LLM infrastructure breaks in methods conventional monitoring can not detect, and learn how to separate actual incidents from anticipated AI error conduct.
As a consequence, scaling effectively has grow to be more and more difficult.
In this unique reside session with Datadog, 4 main consultants will discover how unified observability helps groups detect points earlier, resolve them quicker, and switch manufacturing context into clever motion.
This session will deal with what groups can do now to remain forward.
What you’ll be taught:
- How main groups monitor LLM methods in real-world manufacturing environments
- How to determine and resolve points earlier than they influence customers
- How to carry observability immediately into AI workflows and choice loops
- How to cut back MTTR and enhance reliability throughout AI-driven methods
Speakers
Andy Keogh
Sales Engineer, Datadog
Andy Keogh serves as a Customer Success Sales Engineer at Datadog, the place he works with buyer success groups and present clients to showcase Datadog’s worth, assist onboarding, and align observability initiatives with key enterprise outcomes.
John Trapani
Field CTO, Datadog
John Trapani serves as Datadog’s Field CTO for Financial Services, the place he companions with leaders in banking, capital markets, and insurance coverage to align observability methods with their most essential enterprise outcomes.
Nicolas Chinot
GM US, Dust
Nicolas Chinot is the US General Manager at Dust. He was one in every of its first buyers and later based Dust’s US enterprise, which he now leads. Nicolas beforehand spent a number of years as a Product Lead at Square, which he joined by the acquisition of a startup he based throughout school.
Jean-David Fiquet
Software Engineer, Dust
Jean-David Fiquet is a Software Engineer at Dust, the place he helps construct an AI working system for forward-thinking corporations. Jean-David works on the core platform that allows organizations to deploy safe, context-aware AI brokers related to firm information and instruments.
