Скачать или смотреть 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.

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