In the fast-paced world of cloud computing, Amazon Web Services (AWS) is a popular choice for businesses looking to build secure, scalable, and strong applications.
As businesses expand in the AWS world, the need for effective cross-account communication becomes increasingly important.
This allows for central management, resource sharing, and smooth collaboration across multiple AWS accounts.
Understanding cross-account communication in AWS can be tricky, especially for those new to the platform.
But worry not! This guide is here to break it down for you. No matter your experience level, think of this guide as your helpful friend, assisting you in tackling the challenges of cross-account communication and getting the most out of your AWS setup. We’ll start by covering the fundamental theoretical aspects before delving into solving a real-world scenario.
Cross-account communication is crucial in various situations within the AWS ecosystem. Let’s see why it matters:
In essence, cross-account communication acts as a versatile tool, addressing organizational needs ranging from effective workload management and security enforcement to seamless collaboration and data sharing across the AWS ecosystem.
AWS provides various ways to enable communication between different accounts. The key methods involve using resource-based policies and IAM roles.
Some AWS services, like S3, allow you to directly attach resource-based policies to the resource you want to share. These policies specify who (which principal) can access the resource. Unlike identity-based policies for roles, resource-based policies focus on the resource itself.
Not all services support resource-based policies. In such cases, you can opt for cross-account IAM roles for centralized permission management. These roles include a trust policy that permits IAM principals in another AWS account to assume the role.
For more information on resource-based and identity-based policies, check out this AWS user guide.
Let’s transition from theory to hands-on problem-solving.
Imagine a situation where important assets, like video files, are securely stored in an S3 bucket within account A. Now, let’s say there’s a Lambda function in account B that needs to create pre-signed URLs for safe and authorized downloads of these assets. The difficulty here is in establishing a secure communication link between these two AWS accounts. The task is to ensure a reliable and protected means for the Lambda function in account B to access and generate pre-signed URLs for the assets stored in the S3 bucket of account A.
Let’s create the Lambda function with the necessary roles and permissions in our AWS account (account B) using Terraform.
Lambda IAM role
IAM roles are crucial components in how users, services, and resources interact within Amazon Web Services. Unlike IAM users, roles don’t have long-term credentials but rely on temporary credentials generated during role assumption.
Here’s the Terraform code to create the IAM role for our Lambda function:
Lambda function
Now, let’s create the Lambda function using Terraform:
Lambda Role Custom Policy
In our account, we need to attach the following custom policy to the Lambda role. This policy explicitly grants permission for the Lambda role to assume the S3 Access role in account A.
Let’s create the policy and attach it to our presigned URL generator Lambda function.
Replace ACCOUNT_A_ID with the actual AWS account ID where the S3 bucket is, and S3ACCESS_ROLE with the name of the actual S3 access role.
The trust policy defines which principals (entities) can assume a particular role and under what conditions. It is a specific type of resource-based policy for IAM roles focusing on the relationship between the role and the entities that trust it.
In account A, let’s create an S3 access role that has a trust policy allowing the Lambda role in account B to assume it, maintaining security boundaries.
Cross-Account IAM role for S3 Access
Imagine we have a bucket named classic-movies. Let’s create an IAM role for accessing the bucket, and attach a policy that allows permissions required for pre-signed URL generation of the movie objects. Also, we’ll ensure a trust policy is in place, permitting the Lambda role in account B to assume this newly created IAM role.
Replace ACCOUNT_B_ID with the actual AWS account ID where the Lambda function resides, and LAMBDA_ROLE_NAME with the name of the role associated with the Lambda function.
Once trust relationships are established, the Lambda function in our production account – account B can programmatically assume the S3 access role in account A using the AssumeRole API of STS. It’s important to note that, when we assume a role, we give up the original permissions and adopt the permissions assigned to the newly assumed role.
Here’s how you can achieve this in Python:
Generating Presigned URLs
With the assumed role’s credentials, the Lambda function in account B can now generate presigned URLs for securely downloading movies from account A’s S3 bucket. Presigned URLs are short-lived and provide temporary access to the specified object.
Here’s how to generate a presigned URL using the assumed credentials:
When working with pre-signed URLs, it’s crucial to be aware of the relationship between the pre-signed URL’s validity and the duration of the Lambda assumed role. Here are some important points to consider:
Here’s the step-by-step guide to implementing the Lambda function using Python:
Assume the specified IAM role based on the given role ARN.
Generate a presigned URL for downloading an S3 object.
Lambda function to generate a presigned URL.
When deploying a Lambda function, AWS Lambda expects the function code to be packaged in a ZIP archive. Here’s how you can create a zip archive for the Lambda function using Terraform:
Once deployed, our lambda function can securely generate pre-signed URLs for us to download our favorite classic movies stored in the S3 bucket of account A.
By carefully following the outlined steps and taking into account the duration of roles, we have effectively set up a secure communication link between two AWS accounts. This ensures that the Lambda function in account B can securely interact with the S3 access role in account A, enhancing the overall security and efficiency of cross-account communication. It’s similar to establishing a guarded pathway, allowing seamless and protected collaboration between different components of our AWS infrastructure.