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Google

AI Infrastructure: Orchestration and Automation

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Overview

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This course covers the automation and operational management of GKE clusters optimized for distributed AI and machine learning workloads. You will learn to provision accelerator resources, configure advanced workload queueing, mitigate capacity constraints, and orchestrate large-scale distributed jobs.

Syllabus

  • Introduction
    • Introduction
  • AI Workloads on Google Kubernetes Engine
    • Why run your AI workloads on GKE
    • How Kubernetes manages AI workloads
    • Automate GKE cluster creation with Terraform
    • Options to accelerate cluster creation
  • Optimize Scheduling and Resource Allocation
    • Schedule batch workloads with Kueue
    • Kueue: Setup, quotas, and scheduling
    • Acquire and optimize resources with DWS and TAS
    • Optimize your resources with CCC
    • Design fallback strategies in CCC
    • Create fallback strategy profiles in CCC
  • Orchestrate Distributed Training
    • Introduction to Ray and KubeRay
    • Orchestrate distributed Ray workloads on GKE
  • Summary
    • Quiz
    • Resources
    • Conclusion
  • Your Next Steps
    • Completion

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