Self-Hosted LLMs on Kubernetes: A Practical Guide - Hema Veeradhi & Aakanksha Duggal, Red Hat

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Self-Hosted LLMs on Kubernetes: A Practical Guide - Hema Veeradhi & Aakanksha Duggal, Red Hat
Have you ever considered deploying your own large language model (LLM), but the seemingly complex process held you back from exploring this possibility? The complexities of deploying and managing LLMs in production environments often pose significant challenges. This talk will serve as a comprehensive introductory guide, empowering beginners to commence their LLM journey by effectively hosting their own models on Kubernetes. We will discuss the process of selecting appropriate open source LLM models, containerization of the models, and creating Kubernetes deployment manifests and resource provisioning to support the LLM's computational needs. Self-hosted LLMs offer enhanced data privacy, flexibility in model training, and reduced operational costs, making them an attractive option for organizations seeking greater control over their AI infrastructure. By the end of this talk, attendees will possess the necessary skills and knowledge to navigate the exciting path of self-hosting LLMs.

[@east4ming]

This is a step-by-step, informative, hands-on guide. Very well presented, thank you!

[@LanTran-jo9od]

the title is hosting in k8s. However, the recorded video is for running in local. Did I miss anything?