Streamline custom model creation and deployment for Amazon Bedrock with Provisioned Throughput using Terraform

The article explains how to streamline the creation and deployment of custom models for Amazon Bedrock using Terraform. It provides a solution to automate the process of retrieving and formatting data for model customization, initiating the model customization job, and configuring Provisioned Throughput for the custom models.

Specifically, the article covers:

• Prerequisites for the solution, including AWS account, IAM permissions, and software installations
• Setting up a Terraform project and initializing it
• Creating data sources and an S3 bucket for storing training data
• Creating an IAM service role for Amazon Bedrock
• Configuring a Python virtual environment and downloading a public dataset
• Converting the dataset to JSONL format and uploading it to S3
• Creating an Amazon Bedrock custom model using fine-tuning
• Configuring Provisioned Throughput for the custom models
• Best practices and considerations, such as data and model versioning, data privacy, and billing
• Cleaning up the created resources