GPUs in Kubernetes for AI Workloads

Today we dive into running AI models on Kubernetes with GPU support. Learn how to manage GPUs in Kubernetes clusters, create GPU nodes, and optimize resource usage without breaking the bank. We'll walk you through setting up a Google Cloud Kubernetes cluster (the same logic should apply to other Cloud providers), deploying AI models like Ollama's Llama2, and handling GPU partitioning. Watch now to master GPU-based AI workloads in Kubernetes! #Kubernetes #GPU #AI ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Sponsor: CAST AI 🔗 https://cast.ai/devopstoolkit ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Consider joining the channel:    / devopstoolkit   ▬▬▬▬▬▬ 🔗 Additional Info 🔗 ▬▬▬▬▬▬ ➡ Transcript and commands: https://devopstoolkit.live/ai/unlock-... ▬▬▬▬▬▬ 💰 Sponsorships 💰 ▬▬▬▬▬▬ If you are interested in sponsoring this channel, please visit https://devopstoolkit.live/sponsor for more information. Alternatively, feel free to contact me over Twitter or LinkedIn (see below). ▬▬▬▬▬▬ 👋 Contact me 👋 ▬▬▬▬▬▬ ➡ Twitter:   / vfarcic   ➡ LinkedIn:   / viktorfarcic   ▬▬▬▬▬▬ 🚀 Other Channels 🚀 ▬▬▬▬▬▬ 🎤 Podcast: https://www.devopsparadox.com/ 💬 Live streams:    / devopsparadox   ▬▬▬▬▬▬ ⏱ Timecodes ⏱ ▬▬▬▬▬▬ 00:00 AI Inference with GPUs 01:30 CAST AI (sponsor) 02:29 Using GPUs for AI Inference in Kubernetes