[P] Optimizing ML Workloads with TPI (Terraform Provider Iterative) - One Provider to Rule AWS, Azure, GCP, K8s

The guide introduces Terraform Provider Iterative (TPI) - an open-source tool extending the functionality of Terraform. The tool enables full lifecycle management of computing resources and is designed specifically for ML pipelines: [Machine Learning Workloads with Terraform Provider Iterative](https://dvc.org/blog/terraform-provider)

It was designed for machine learning (ML/AI) teams and optimizes CPU/GPU expenses. TPI unifies auto-scaling groups for all the major cloud providers: AWS, Azure, GCP and Kubernetes.

* Spot instances auto-recovery (if an instance was evicted/terminated) with data and checkpoint synchronization …

aws azure gcp iterative k8s machinelearning ml provider terraform