A SRE's Guide to LLMOps: Deploying and Managing AI/ML Workloads Using Kubernetes

A SRE's Guide to LLMOps: Deploying and Managing AI/ML Workloads Using Kubernetes

Mirantis via YouTube Direct link

15:30 - One2N's successes & challenges with K8s LLMOps

4 of 10

4 of 10

15:30 - One2N's successes & challenges with K8s LLMOps

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

A SRE's Guide to LLMOps: Deploying and Managing AI/ML Workloads Using Kubernetes

Automatically move to the next video in the Classroom when playback concludes

  1. 1 0:00 - Intro
  2. 2 0:24 - Why SREs need to worry about LLMs
  3. 3 1:11 - One2N's journey towards true LLMOps
  4. 4 15:30 - One2N's successes & challenges with K8s LLMOps
  5. 5 18:35 - MLOps vs LLMOps: Infra, Deployment & Architecture
  6. 6 19:31 - VMs to Kubernetes for LLMOps
  7. 7 23:07 - Vector Storage: index vs database
  8. 8 25:12 - Deep dive into One2N's Lab setup real-world use case
  9. 9 28:58 - Key takeaways to get started with LLMOps
  10. 10 31:23 - Outro

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.