Learn to implement metrics, logs, and centralized monitoring to maintain your AI brokers sturdy and production-ready
Constructing AI brokers is an thrilling problem, however merely deploying them isn’t all the time sufficient to make sure a clean, sturdy expertise for customers. As soon as deployed, AI functions want efficient monitoring and logging to maintain them working optimally. With out correct observability instruments, points can go undetected, and even minor bugs can snowball into main manufacturing issues.
On this information, we’ll stroll you thru how you can arrange monitoring and logging in your AI agent, so you possibly can preserve full visibility over its habits and efficiency. We’ll discover how you can gather important metrics, collect logs, and centralize this knowledge in a single platform. By the top of this tutorial, you’ll have a foundational setup that means that you can detect, diagnose, and deal with points early, making certain a extra secure and responsive AI software.
Full code is obtainable right here: https://github.com/CVxTz/opentelemetry-langgraph-langchain-example