AI Infrastructure and LLMOps Guide

This comprehensive guide demystifies AI infrastructure and LLMOps, providing essential knowledge for deploying and managing AI systems effectively in production. Explore critical topics such as model routing, inference pipelines, caching strategies, GPU utilization, and robust monitoring. Discover real-world architectures and best practices to optimize performance, cost, and scalability for your AI applications.

Chapters

1. 01 Essential AI Infrastructure for LLM Serving 16m
2. 02 Smart Caching Strategies for Cost-Efficient LLM Inference 19m
3. 03 Build & Optimize LLM Inference Pipelines for Production 18m
4. 04 Dynamic Model Routing and A/B Testing for LLMs 14m
5. 05 Build an End-to-End Production RAG System with LLMOps 28m
6. 06 Optimize GPUs for Faster, More Efficient LLM Inference 22m
7. 07 LLM Inference: Core Mechanics, Optimization, and Caching 20m
8. 08 Understanding the Unique Challenges of LLMOps for LLMs 12m
9. 09 Mastering Cost Optimization for LLM Inference 22m
10. 10 Monitoring and Observability for Production LLM Systems 19m
11. 11 Scale LLM Deployments from Single Instances to Clusters 26m
12. 12 Implement Security and Governance for LLM Deployments 16m