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AI Knowledge Base · AI Cloud Platforms · Hyperscalers

Google Cloud

Vertex AI, Gemini and TPUs alongside NVIDIA GPUs.

Ideal para: Teams building on Gemini, data-heavy AI on BigQuery, and large training runs on TPUs.

Workflow: a service on GKE or Cloud Run authenticates as a service account through Workload Identity Federation, Model Armor screens the prompt, and Vertex AI answers inside VPC Service Controls with customer-managed keys.
The request path on Google Cloud: no key files, because the service uses Workload Identity Federation; Model Armor screens prompts and responses; Vertex AI sits inside a VPC Service Controls perimeter with customer-managed encryption keys.

AI services

  • Vertex AI: Gemini and partner models from Model Garden, tuning, evaluation, pipelines and endpoints.
  • Vertex AI Agent Builder and Agent Engine, with the open-source Agent Development Kit (ADK) and the Agent2Agent (A2A) protocol.
  • BigQuery ML and Vertex AI Search for retrieval over enterprise data.

GPUs and accelerators

  • Cloud TPUs, including the latest generations for training and inference.
  • A3 (H100), A3 Ultra (H200), A4 (B200) and A4X (GB200) VMs.
  • GKE with GPU and TPU node pools; Cloud Run with GPUs for serverless inference.

Agents and identity

  • Workload Identity Federation so services and pipelines authenticate without key files.
  • IAM conditions and service accounts per agent.

Security and data

  • VPC Service Controls around Vertex AI, customer-managed encryption keys and data residency controls.
  • Model Armor to screen prompts and responses for injection and data leakage.

Scaling and optimisation

  • Provisioned throughput for Gemini; dynamic workload scheduler for GPU and TPU capacity.
  • Context caching and batch prediction to reduce cost.

UK and EU regions

London (europe-west2) and EU regions.

Watch out for

TPU code paths (JAX, PyTorch/XLA) differ from CUDA; plan the port before committing.

How Workstation helps: We build Vertex AI and Gemini solutions, run GKE GPU and TPU clusters, and connect them to on-premises data.

Scaling AI at large scale with Amazon Bedrock →CI/CD for LLMs, agents and data in the cloud →Securing LLM and agent APIs →The AI agent harness →Identity and authentication for AI →

Talk to a cloud engineer →Ask the AI Sales Engineer ↗← All AI cloud platforms

Other providers we work with

AWSAzureOracle CloudCoreWeaveLambdaNebiusDigitalOceanVast.aiRunPod

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