Overviews how to secure application endpoints with Identity Aware Proxy (IAP)
This tutorial guides you through deploying a containerized agent built with the [Google Agent Development Kit (ADK)](https://google.github.io/adk-docs/) to [Google Kubernetes Engine (GKE)](https://cloud.google.com/kubernetes-engine/docs/concepts/kubernetes-engine-overview). The agent uses [VertexAI](https://cloud.google.com/vertex-ai/docs) to access LLMs. GKE provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure.
This tutorial shows you who to serve a large language model (LLM) using both Tensor Processing Units (TPUs) and GPUs on Google Kubernetes Engine (GKE) using the same deployment with [vLLM](https://github.com/vllm-project/vllm)
Deploying and managing servers dedicated to performing inference tasks for machine learning models.
Overviews how to convert your inference checkpoint for various model servers
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