Automate Access Control in Amazon EKS Using Amazon Bedrock Agents

Automate Access Control in Amazon EKS Using Amazon Bedrock Agents
Automate Access Control in Amazon EKS Using Amazon Bedrock Agents

CLOUD LABS



Automate Access Control in Amazon EKS Using Amazon Bedrock Agents

In this Cloud Lab, you’ll build an autonomous EKS access management system using Amazon Bedrock Agents to interpret natural language requests and securely update Kubernetes RBAC via a Lambda tool.

9 Tasks

intermediate

2hr

Certificate of Completion

Desktop OnlyDevice is not compatible.
No Setup Required
Amazon Web Services

Learning Objectives

Hands-on experience configuring an Amazon Bedrock Agent with necessary IAM roles and defining a tool using a custom OpenAPI schema
Practical experience connecting a Lambda function to act as the Bedrock Agent's execution engine for secure EKS cluster management
Ability to streamline operational tasks using an agent capable of interpreting natural-language commands for EKS access control

Technologies
Bedrock
EKS
Lambda logoLambda
Cloud Lab Overview

Amazon EKS provides a robust platform for running containerized applications and includes internal permission and access management via Kubernetes role-based access control (RBAC), service accounts, and AWS IAM roles.

As teams grow and multiple users, services, and automated systems interact with the cluster, managing these permissions consistently can become complex. Mistakes or delays in updating roles and access policies can lead to security gaps, operational bottlenecks, or slowed development workflows.

Generative AI-driven automation using Amazon Bedrock Agents can simplify this process by interpreting natural-language requests and autonomously updating access controls, reducing manual effort and improving reliability.

In this Cloud Lab, you will learn how to build an intelligent, automated access control workflow. You will begin by creating the foundational IAM roles needed throughout the lab. Next, you’ll provision an EKS cluster that the agent will manage.

After that, you’ll set up the tooling layer the agent relies on, which includes an S3 bucket containing an OpenAPI schema and a Lambda function that modifies access rules within the cluster.

Once the tooling layer is ready, you will create and configure an Amazon Bedrock Agent that uses this Lambda function as its execution engine. With the agent configured, you will validate the end-to-end setup by issuing natural-language requests such as granting or revoking user access and observing how the agent autonomously interprets the request, invokes the Lambda function, and updates access controls within the EKS cluster.

After completing this Cloud Lab, you will understand how to automate EKS access management using Amazon Bedrock Agents.

You will gain hands-on experience configuring a Bedrock Agent with tools, defining operational schemas, wiring Lambda functions for cluster management, and validating end-to-end agent behavior. By the end, you will see how generative AI can streamline operational tasks, reduce manual overhead, and make Kubernetes access control more intuitive, reliable, and efficient.

The following is the high-level architecture diagram of the infrastructure you’ll create in this Cloud Lab:

Automated EKS access control
Automated EKS access control
Cloud Lab Tasks
1.Introduction
Getting Started
2.Core Infrastructure Setup
Create IAM Roles
Create an EKS Cluster
3.Agent Tooling and API Layer
Create an S3 Bucket
Create a Lambda Function
4.Intelligent Access Automation and Validation
Create a Bedrock Agent
Test the Setup
5.Conclusion
Clean Up
Wrap Up
Labs Rules Apply
Stay within resource usage requirements.
Do not engage in cryptocurrency mining.
Do not engage in or encourage activity that is illegal.

Before you start...

Try these optional labs before starting this lab.

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