AI and LLM Observability with Dynatrace скачать в хорошем качестве

AI and LLM Observability with Dynatrace

Explore how #Dynatrace provides OpenTelemetry-based AI and LLM Observability into all layers of your AI Stack: Infrastructure, Model, Semantic, Orchestration, and Application. Organizations adopting Artificial Intelligence (AI) and large language models (LLMs) struggle to optimize performance, understand costs, and ensure accurate responses. In this use case tutorial, you'll: Learn what challenges companies face when adopting AI Understand how to observe AI and LLM and the benefits of doing so Watch a full demo on observing and analyzing typical AI challenges, including slow requests, performance issues, and accurate responses. Useful links: Explore our sample dashboards on the Dynatrace Playground: https://dynatr.ac/4dnkuLX Get hands-on and deploy our GenAI demo app using GitHub Codespace: https://dynatr.ac/4eH77Hf Implement AI observability in your environments with our detailed Dynatrace Documentation: https://dynatr.ac/3XKxKEC 📖 Chapters 📖 00:00 - Introduction 00:26 - AI Market Observations 00:54 - AI Adoption Challenges 01:26 - AI Observability Overview 03:34 - Demo Architecture 05:00 - Demo begins 05:53 - Analyzing Slow AI Requests 09:22 - Analyzing Costs of AI Usage 10:48 - Analyzing the Performance of Models 11:30 - Analyzing AI Accuracy 13:40 - Wrap Up 🔬 Have a question about our platform? Visit our Dynatrace Community to connect with our experts and users → https://dynatr.ac/3FYfPB3 Try our platform with a free trial, or schedule a personalized demo at https://dynatr.ac/3VxvLDH. 👉✅ Stay up-to-date with Dynatrace! Follow us on: Facebook →   / dynatrace   Instagram →   / dynatrace   LinkedIn →   / dynatrace   X →   / dynatrace   Twitch →   / dynatrace