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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 pulumiINTEGRATION 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