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Many AI inference workloads don't need a full GPU. So why allocate one per pod? GPU sharing is becoming table stakes for Kubernetes AI infra, but doing it safely means solving for scheduling, fairness, isolation, and noisy neighbors. On August 6 we break down the GPU sharing landscape: time-slicing, MPS, MIG, KAI Scheduler, and HAMi and what it actually takes to run shared GPUs in production. You'll walk away with: - A clear map of GPU sharing approaches and when to use each - Real patterns (and pitfalls) from production - How automation keeps things fair and reliable as demand shifts 🎤 Presenter: Julien Semaan, Head of Kubernetes Engineering 📅 August 6 @11 AM ET 🔗 Register here https://lnkd.in/gvTvH8jt #Kubernetes #GPU #AI #AIInfrastructure #PlatformEngineering #webinar

Autonomous K8s Optimization involves compute AND storage resources. Are you doing both? In this joint session, Lucidity and Kubex will walk through what end-to-end K8s optimization looks like when you address both layers together. Expect real examples, not slides full of theory. You’ll leave with a clear picture of where waste is hiding in your environment and a prioritized approach to addressing it. 📅 May 14 @11:00 AM EST 🔗 Register here https://lnkd.in/effJURwg

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