IAM Setup for Bedrock: Step-by-Step Guide

Ready Tensor · Beginner ·🛠️ AI Tools & Apps ·6mo ago

About this lesson

In this video, we walk through the complete IAM setup required to run batch inference jobs with Amazon Bedrock. You'll see how to configure permissions, create execution roles, and troubleshoot common access errors. You'll learn how to: - Create IAM user groups with Bedrock permissions - Generate and configure AWS CLI access keys - Create execution roles with trust policies - Define S3 access policies for batch input and output - Add PassRole permissions to your user group - Troubleshoot AccessDenied errors step by step - Run single and batch inference successfully Timestamps: 0:00 - Introduction and setup overview 1:12 - Creating IAM user group with permissions 2:09 - Creating IAM user and access keys 3:42 - Configuring AWS CLI credentials 4:23 - Running single inference successfully 6:03 - Creating execution role policy for batch jobs 7:19 - Creating role with trust policy 8:52 - Adding PassRole policy to fix access errors This video demonstrates the IAM configuration patterns you'll use throughout AWS-based LLM workflows, from managed inference to training jobs. This video is part of the LLM Engineering and Deployment Certification Program by Ready Tensor. Enroll Now: https://app.readytensor.ai/certifications/llm-engineering-and-deployment-DAROCXlj About Ready Tensor: Ready Tensor helps AI/ML professionals build production-grade LLM systems through hands-on certifications and real-world projects. Learn more: https://www.readytensor.ai/ Like the video? Subscribe for more AWS and LLM engineering tutorials!

Original Description

In this video, we walk through the complete IAM setup required to run batch inference jobs with Amazon Bedrock. You'll see how to configure permissions, create execution roles, and troubleshoot common access errors. You'll learn how to: - Create IAM user groups with Bedrock permissions - Generate and configure AWS CLI access keys - Create execution roles with trust policies - Define S3 access policies for batch input and output - Add PassRole permissions to your user group - Troubleshoot AccessDenied errors step by step - Run single and batch inference successfully Timestamps: 0:00 - Introduction and setup overview 1:12 - Creating IAM user group with permissions 2:09 - Creating IAM user and access keys 3:42 - Configuring AWS CLI credentials 4:23 - Running single inference successfully 6:03 - Creating execution role policy for batch jobs 7:19 - Creating role with trust policy 8:52 - Adding PassRole policy to fix access errors This video demonstrates the IAM configuration patterns you'll use throughout AWS-based LLM workflows, from managed inference to training jobs. This video is part of the LLM Engineering and Deployment Certification Program by Ready Tensor. Enroll Now: https://app.readytensor.ai/certifications/llm-engineering-and-deployment-DAROCXlj About Ready Tensor: Ready Tensor helps AI/ML professionals build production-grade LLM systems through hands-on certifications and real-world projects. Learn more: https://www.readytensor.ai/ Like the video? Subscribe for more AWS and LLM engineering tutorials!
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Chapters (8)

Introduction and setup overview
1:12 Creating IAM user group with permissions
2:09 Creating IAM user and access keys
3:42 Configuring AWS CLI credentials
4:23 Running single inference successfully
6:03 Creating execution role policy for batch jobs
7:19 Creating role with trust policy
8:52 Adding PassRole policy to fix access errors
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