Introduction
1. Introduction
To fully leverage the power of AI, robust and scalable infrastructure is paramount. This is where Google Kubernetes Engine becomes a critical component. GKE provides a managed environment for deploying, managing, and scaling containerized applications, making it ideal for the demanding workloads of AI. This module will explore how GKE facilitates the deployment and optimization of AI models, covering topics such as resource management, scaling strategies, and integration with Google Cloud's AI/ML services. In this section, titled CI/CD at Scale in GKE, you learn to explain how GKE serves as a suitable platform for large language models and the increasing demand for hardware accelerators, describe the high-level architecture of a GKE-based training platform for AI models, outline the architecture for a GKE-based model serving platform, and outline different cost management strategies available when using GKE for AI/ML workloads.2. Let's practice!
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