How to Deploy a Zero-Touch Ollama GPU Inference Server on AWS, Azure, and Google Cloud with Pulumi
A detailed technical guide on deploying a fully automated, zero-touch Ollama GPU inference server across AWS, Azure, and Google Cloud using Pulumi infrastructure as code. The article walks through setting up GPU instances, model servers, and firewall rules declaratively, with OIDC credentials from Pulumi ESC to eliminate static keys. It covers multi-cloud deployment patterns, infrastructure automation for AI workloads, and practical implementation steps for running open-source LLMs in the cloud.
Key quotes
Infrastructure as code earned its place by making that kind of setup predictable and repeatable, and AI infrastructure is no exception.
A GPU box serving a model is still a VM, a disk, and a firewall rule, and it should be declared like one.
Putting Ollama on a cloud GPU is something I keep coming back to.
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