Self-driving infrastructure with Pulumi and Jev

Pulumi and TypeSafe AI developed GeoDeploy, an open-source prototype that combines Pulumi’s infrastructure automation with TypeSafe’s Jev SystemOne decision model to select, provision, and manage Kubernetes deployments across AWS, Azure, and Google Cloud. Users provide target user geographies, data-residency requirements, a container image and architecture, workload specifications, provider limits, and a budget; the tool then gathers live cloud pricing, calculates capacity and monthly costs deterministically, and asks Jev to choose only among vetted regional candidates. Responsibilities are deliberately separated: TypeScript performs pricing and technical calculations, Jev makes constrained qualitative choices such as regional suitability and deployment-module posture, and Pulumi provisions cloud resources. Jev returns typed selections, scores, probabilities, and confidence levels rather than free-form text, while confidence gates, candidate validation, audit records, and deterministic fallbacks prevent uncertain AI outputs from driving high-risk decisions. GeoDeploy can also monitor CPU utilization and recommend or apply scaling changes according to confidence thresholds, although the authors note that real production autoscaling should incorporate additional metrics such as latency and error rates.

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