Deploying Serverless Applications on AWS Lambda with Terraform

In the ever-evolving landscape of cloud computing, serverless applications have emerged as a game-changer. AWS Lambda, Amazon’s serverless computing service, allows developers to run code without provisioning or managing servers. Combined with Terraform, an Infrastructure as Code (IaC) tool, deploying serverless applications becomes streamlined and efficient. In this article, we’ll explore how to deploy AWS Lambda functions using Terraform, along with practical coding examples and actionable insights.

What is AWS Lambda?

AWS Lambda is a serverless computing service that automatically manages the infrastructure required to run your code. It allows you to execute code in response to events such as changes in data, shifts in system state, or user actions. Here are some key features of AWS Lambda:

• Event-driven: Automatically runs your code in response to events from various AWS services and external sources.
• Automatic scaling: Seamlessly scales your application based on incoming requests.
• Pay-as-you-go: You only pay for the compute time you consume.

What is Terraform?

Terraform is an open-source tool created by HashiCorp that allows you to define infrastructure using a high-level configuration language. It enables developers to manage their infrastructure in a safe, repeatable way. Some benefits of using Terraform include:

• Infrastructure as Code (IaC): Write, plan, and create infrastructure in a declarative manner.
• Version control: Use version control systems like Git to track changes to your infrastructure.
• Multi-cloud support: Manage resources across multiple cloud providers.

Use Cases for Serverless Applications

Before diving into the deployment process, let's explore some common use cases for serverless applications:

• Data processing: Use Lambda functions to process data in real-time, such as transforming logs or analyzing streaming data.
• Web applications: Build RESTful APIs that automatically scale based on usage, serving content without worrying about server maintenance.
• Automation: Automate tasks such as sending notifications, processing images, or managing cloud resources.

Prerequisites

To follow along with this tutorial, ensure you have the following installed:

• An AWS account
• Terraform installed on your local machine
• AWS CLI configured with appropriate permissions

Step-by-Step Guide to Deploying AWS Lambda with Terraform

Step 1: Set Up Your Project

Create a new directory for your project:

mkdir my-serverless-app
cd my-serverless-app

Next, create a file named main.tf, which will contain your Terraform configuration.

Step 2: Define the Provider

In main.tf, start by defining the AWS provider:

provider "aws" {
  region = "us-east-1"  # Change to your preferred region
}

Step 3: Create the Lambda Function

Define a simple Lambda function in your Terraform configuration. We will use Python for this example. Create a lambda_function.py file:

def lambda_handler(event, context):
    return {
        'statusCode': 200,
        'body': 'Hello from AWS Lambda!'
    }

Now, back in main.tf, add the resource block for the Lambda function:

resource "aws_lambda_function" "my_lambda" {
  function_name = "my_lambda_function"
  runtime       = "python3.8"  # Specify your runtime
  handler       = "lambda_function.lambda_handler"

  s3_bucket = aws_s3_bucket.lambda_bucket.bucket
  s3_key    = "lambda_function.zip"

  role = aws_iam_role.lambda_role.arn

  source_code_hash = filebase64sha256("lambda_function.zip")
}

Step 4: Create an S3 Bucket

Lambda functions require code to be uploaded to an S3 bucket. Define a new S3 bucket in main.tf:

resource "aws_s3_bucket" "lambda_bucket" {
  bucket = "my-lambda-bucket-${random_string.unique_suffix.result}"
  acl    = "private"
}

resource "random_string" "unique_suffix" {
  length  = 8
  special = false
}

Step 5: Set Up IAM Role

Your Lambda function needs permissions to execute. Create an IAM role:

resource "aws_iam_role" "lambda_role" {
  name = "my_lambda_role"

  assume_role_policy = jsonencode({
    Version = "2012-10-17"
    Statement = [{
      Action = "sts:AssumeRole"
      Principal = {
        Service = "lambda.amazonaws.com"
      }
      Effect = "Allow"
      Sid    = ""
    }]
  })
}

resource "aws_iam_policy_attachment" "lambda_policy_attachment" {
  name       = "attach_lambda_policy"
  roles      = [aws_iam_role.lambda_role.name]
  policy_arn = "arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole"
}

Step 6: Package the Lambda Function

To deploy your Lambda function, you need to package it into a ZIP file. Use the following command:

zip lambda_function.zip lambda_function.py

Step 7: Initialize and Apply Terraform Configuration

Initialize Terraform and apply your configuration:

terraform init
terraform apply

Review the changes Terraform will make, and confirm by typing yes.

Step 8: Test Your Lambda Function

After deployment, you can test your Lambda function through the AWS Management Console or using the AWS CLI:

aws lambda invoke --function-name my_lambda_function output.txt

Check the content of output.txt to see the response from your Lambda function!

Troubleshooting Common Issues

While deploying serverless applications with AWS Lambda and Terraform can be straightforward, you may encounter some issues:

• Permissions errors: Ensure your IAM role has the necessary permissions.
• Missing dependencies: If your Lambda function relies on external libraries, package them along with your function code.
• Configuration errors: Double-check your Terraform configuration for typos or misconfigurations.

Conclusion

Deploying serverless applications on AWS Lambda using Terraform not only simplifies the infrastructure management process but also empowers developers to focus on writing code. By following the steps outlined in this article, you can quickly set up and deploy a serverless application that is scalable and cost-effective. Embrace the power of serverless architecture and optimize your development workflow today!