Aditya Patil
I am a Frontend Engineer currently working as an Associate Software Engineer at Red Hat. I have a strong interest in building modern web applications and enjoy exploring different areas of software engineering, including full-stack development, DevOps, and AI/ML. I am passionate about learning new technologies and sharing knowledge through the developer community.
Red Hat
Associate Software Engineer
Session
The rapid rise of open, modular AI architectures is reshaping how developers build intelligent systems. At the forefront of this movement is the Llama Stack — a flexible, production-ready ecosystem designed to help teams build, deploy, and scale LLM-powered applications with confidence.
This talk delivers a practical, in-depth exploration of the Llama Stack, breaking down its components, capabilities, and real-world performance. Attendees will get a clear understanding of how the stack simplifies model orchestration, enhances security, improves observability, and accelerates production deployment.
Attendees will walk away with actionable insights on:
• What the Llama Stack is, and how its modular architecture empowers teams to build scalable AI systems.
• How the Llama runtime compares to conventional inference pipelines in terms of performance, extensibility, and developer experience.
• Security and governance features that make the Llama Stack enterprise-ready by default.
• Real-world case studies: When the Llama Stack outperforms custom or closed-source solutions—and when it doesn’t
Whether you're an AI engineer, backend developer, architect, or engineering leader, this talk will help you evaluate when and why the Llama Stack should be your foundation for building modern AI applications.