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PULUMI

Infrastructure as code in real programming languages

Apache-2.0

ABOUT

Provisioning ML infrastructure — GPU instances, vector databases, model serving endpoints, and data pipelines — typically requires either clicking through cloud consoles or learning HCL (Terraform's domain-specific language). Pulumi lets ML teams define infrastructure using standard programming languages they already know, enabling loops, conditionals, functions, and shared libraries. A Python-trained team can define their training cluster, model registry, and serving infrastructure in Python with full IDE support, unit testing, and package management — without learning a new configuration language.

INSTALL
brew install pulumi

INTEGRATION GUIDE

1. Provision GPU training clusters with spot instances, auto-scaling, and persistent storage 2. Deploy vector database instances (Pinecone, Qdrant, Weaviate) as infrastructure-as-code 3. Define and deploy model serving stacks with load balancers, TLS, and monitoring 4. Manage multi-cloud ML infrastructure (AWS+Azure+GCP) from a single codebase

TAGS

infrastructure-as-codeclouddevopsautomationterraform-alternativepython