TPI, or Terraform Provider Iterative, is the first product on HashiCorp’s Terraform technology stack. Dmitry Petrov, Co-Founder and CEO of Iterative.ai, joined us on TFiR Newsroom to talk about TPI and how the product helps machine learning (ML) teams manage their computing resources more efficiently. It offers full lifecycle management of computing resources (including GPUs and respawning spot instances) from several cloud vendors (AWS, Azure, GCP, K8s) without needing to be a cloud expert.
Key highlights from this video interview are:
- Petrov discusses how TPI is different from traditional IT tools that data scientists and machine learning engineers use.
- He discusses how Iterative is helping with resource orchestration by putting it in a traditional software development stack.
- Petrov explains why they chose Terraform and how it helps teams collaborate better and help with cost saving on GPU or CPU instances.
- TPI simplifies machine learning training, which can take a lot of time. It helps with cost-cutting. Petrov elaborates on the potential costs of training a single model just on computational resources and the challenges with infrastructure optimization.
- Petrov explains how spot instances work and how TPI does spot instances automatically. He explains how with TPI the cloud takes care of the recovery of your instances automatically and how this saves resources.
- TPI is open source meaning you can download the software into your machine and can work directly with your resources without third-party services and additional infrastructure. Petrov explains how people can get started with TPI and make use of it.
- Petrov discusses some of the use cases of TPI and how it is helping to close the gap between training and productization.
- Petrov shares their future plans to build more features for machine learning engineers and how they are working towards helping people iterate 1,000 times in a single model and the steps they need to take to achieve this.
About Dmitry Petrov: Creator of DVC. Ex-Data Scientist at Microsoft. PhD in Computer Science.
About Iterative.ai: Iterative.ai, the company behind Iterative Studio and popular open-source tools DVC and CML, enables data science teams to build models faster and collaborate better with data-centric machine learning tools. Iterative’s developer-first approach to MLOps delivers model reproducibility, governance, and automation across the ML lifecycle, all integrated tightly with software development workflows. Iterative is a remote-first company, backed by True Ventures, Afore Capital, and 468 Capital.
The summary of the show is written by Emily Nicholls.