https://github.com/iterative/blog-tpi-bees
Terraform Provider Iterative + ML data & code -> AWS/Azure/GCP/K8s
https://github.com/iterative/blog-tpi-bees
aws azure blog cloud demo example gcp gpu k8s keras tensorflow terraform terraform-provider
Last synced: 5 months ago
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Terraform Provider Iterative + ML data & code -> AWS/Azure/GCP/K8s
- Host: GitHub
- URL: https://github.com/iterative/blog-tpi-bees
- Owner: iterative
- Created: 2021-11-26T13:46:58.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-06-22T20:05:14.000Z (over 3 years ago)
- Last Synced: 2025-08-29T06:44:04.082Z (5 months ago)
- Topics: aws, azure, blog, cloud, demo, example, gcp, gpu, k8s, keras, tensorflow, terraform, terraform-provider
- Language: Python
- Homepage: https://dvc.org/blog/local-experiments-to-cloud-with-tpi
- Size: 47.8 MB
- Stars: 1
- Watchers: 14
- Forks: 2
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
An example of setting up remote cloud environment for training a machine learning model using [Terraform Provider Iterative](https://github.com/iterative/terraform-provider-iterative).
See the blog post at for a full explanation.
The `main.tf` file contains two different tasks:
1. basic scenario for running a script remotely, and
2. training a model on a GPU device
To run this tutorial, make sure to have a cloud account (AWS, Azure, GCP, or K8s) with [authentication credentials stored as environment variables](https://registry.terraform.io/providers/iterative/iterative/latest/docs/guides/authentication).
1. [Install Terraform](https://www.terraform.io/downloads)
2. `terraform init`: setup dependencies
3. `terraform apply`: provision cloud infrastructure & upload task
4. `terraform refresh && terraform show`: check status
5. `terraform destroy`: download results and terminate cloud infrastructure
