Streamlining AWS Serverless Architecture in the AWS Cloud using Terraform Modules

In today’s cloud-centric world, managing serverless architectures efficiently is paramount for developers. Terraform, an open-source Infrastructure as Code (IaC) tool, provides a powerful way to deploy and manage AWS resources with ease and precision. This blog post delves into setting up a serverless architecture on AWS, utilizing Terraform modules for AWS Lambda, IAM, and SNS to create a robust and scalable application infrastructure.

Organizing Infrastructure with Terraform Modules

For clarity and maintainability, our Terraform configuration is organized into modules. Each module corresponds to a specific AWS resource category—iam, sns, and lambda. These modules reside in a dedicated modules folder, each containing four essential files:

main.tf: Contains the resource definitions.
variables.tf: Defines input variables for the module.
outputs.tf: Specifies output values that can be used by other configurations.
locals.tf: (Optional) Defines local variables within the module.

The root directory of our Terraform project also includes these files, orchestrating the invocation of modules and the overall configuration.

IAM Module: Securing Lambda Execution

The IAM module is pivotal for defining the execution role for AWS Lambda. This role includes permissions essential for Lambda's operation, such as writing logs to Amazon CloudWatch. Furthermore, we've enhanced it to include permissions for publishing messages to SNS topics, a critical requirement for our serverless notification mechanism.

The SNS module creates a topic that serves as a communication hub. This topic is used for Lambda's asynchronous invocation errors. Additionally, an email subscription is created, enabling immediate alerts for specific events or errors, thereby increasing observability.

Lambda Module: Running Serverless Functions

Our Lambda module outlines the function itself, including its runtime, handler, and association with the IAM role for execution permissions. It's configured for asynchronous execution, with a direct integration to the SNS topic for handling invocation errors.

Root Configuration: Bringing It All Together

The root directory’s main.tf references each module, passing necessary variables and binding the components together. It leverages outputs from the iam and sns modules to configure the Lambda function, ensuring a cohesive and secure serverless setup.

Terraform Variables and Outputs: Ensuring Flexibility

Our use of variables.tf and outputs.tf ensures that the configuration is flexible and reusable. Variables allow for customization of resources such as the Lambda function name or the SNS email subscription address, while outputs facilitate the interconnection between modules.

Conclusion

By modularizing the Terraform configuration for AWS Lambda, IAM, and SNS, developers can achieve a high degree of reusability and clarity in their infrastructure code. This approach not only simplifies the management of serverless applications but also enhances security and communication flow within the application architecture. With Terraform, the infrastructure becomes as dynamic and scalable as the serverless functions it supports, embodying the true essence of cloud computing.