Developing Serverless Applications on AWS Using Terraform and Docker

In today's fast-paced digital landscape, developing serverless applications has become a game-changer for many developers and businesses. The combination of AWS (Amazon Web Services), Terraform, and Docker offers a powerful toolkit for building, deploying, and managing serverless applications efficiently. In this article, we will dive into the essentials of these technologies, explore their use cases, and provide actionable insights with code examples to help you get started.

Understanding Serverless Architecture

What is Serverless?

Serverless architecture allows developers to build and run applications without the need to manage the underlying infrastructure. AWS Lambda, one of the leading serverless computing platforms, enables you to execute code in response to events without provisioning or managing servers. This model provides automatic scaling, built-in fault tolerance, and a pay-per-use pricing model.

Benefits of Serverless Applications

• Cost Efficiency: You only pay for the compute time you consume.
• Scalability: Automatically scales with your application's demand.
• Reduced Operational Overhead: Focus more on coding and less on infrastructure management.

Overview of Terraform and Docker

What is Terraform?

Terraform is an Infrastructure as Code (IaC) tool that allows you to define and provision cloud infrastructure using a high-level configuration language. It simplifies the management of cloud resources and enables version control for your infrastructure.

What is Docker?

Docker is a platform that allows developers to automate the deployment of applications inside lightweight, portable containers. Containers package your application code along with its dependencies, ensuring consistency across different environments.

Use Cases for AWS Serverless Applications

1. Microservices Architecture: Build and deploy microservices that respond to specific events or API calls.
2. Data Processing: Automate tasks such as image processing, data transformation, and ETL (Extract, Transform, Load) jobs.
3. Web Applications: Serve dynamic content without managing web servers.

Setting Up Your Development Environment

Prerequisites

Before we dive into coding, ensure you have the following installed on your machine:

• AWS CLI: For managing AWS services.
• Terraform: For provisioning infrastructure.
• Docker: For containerization.

Install AWS CLI

To install the AWS CLI, follow the instructions for your operating system:

# For macOS
brew install awscli

# For Ubuntu
sudo apt install awscli

Creating a Serverless Application with Terraform and Docker

Step 1: Define Your Infrastructure with Terraform

Create a new directory for your project:

mkdir serverless-app && cd serverless-app

Next, create a main.tf file to define your AWS Lambda function and API Gateway:

provider "aws" {
  region = "us-east-1"
}

resource "aws_lambda_function" "my_lambda" {
  function_name = "myServerlessFunction"
  handler       = "app.handler"
  runtime       = "nodejs14.x"
  role          = aws_iam_role.lambda_exec.arn
  source_code_hash = filebase64sha256("function.zip")

  depends_on = [aws_iam_role_policy_attachment.lambda_policy]
}

resource "aws_iam_role" "lambda_exec" {
  name = "lambda_exec_role"

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

resource "aws_iam_role_policy_attachment" "lambda_policy" {
  role       = aws_iam_role.lambda_exec.name
  policy_arn = "arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole"
}

Step 2: Create Your Docker Image

Create a simple Node.js application. First, create a Dockerfile in the same directory:

FROM node:14

WORKDIR /usr/src/app

COPY package*.json ./
RUN npm install

COPY . .

CMD ["node", "app.js"]

Next, create a simple app.js file:

exports.handler = async (event) => {
    return {
        statusCode: 200,
        body: JSON.stringify('Hello from Lambda!'),
    };
};

Step 3: Build and Push Your Docker Image

First, build the Docker image:

docker build -t my-serverless-app .

Then, tag and push the Docker image to Amazon Elastic Container Registry (ECR):

# Create an ECR repository
aws ecr create-repository --repository-name my-serverless-app

# Tag the image
docker tag my-serverless-app:latest <aws_account_id>.dkr.ecr.us-east-1.amazonaws.com/my-serverless-app:latest

# Authenticate Docker to ECR
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin <aws_account_id>.dkr.ecr.us-east-1.amazonaws.com

# Push the image
docker push <aws_account_id>.dkr.ecr.us-east-1.amazonaws.com/my-serverless-app:latest

Step 4: Deploy Your Application

After pushing your image, you need to update your Terraform configuration to point to the Docker image in ECR:

resource "aws_lambda_function" "my_lambda" {
  function_name = "myServerlessFunction"
  image_uri     = "<aws_account_id>.dkr.ecr.us-east-1.amazonaws.com/my-serverless-app:latest"
}

Finally, deploy your infrastructure using Terraform:

terraform init
terraform apply

Step 5: Testing Your Serverless Application

Once the deployment finishes, you can test your Lambda function using the AWS Lambda console or through API Gateway if you have set it up.

Troubleshooting Common Issues

• Permission Errors: Ensure your IAM role has the necessary permissions.
• Deployment Failures: Check your Terraform logs for detailed error messages.
• Docker Issues: Ensure your Docker image is built correctly and the correct tags are being used.

Conclusion

Developing serverless applications on AWS using Terraform and Docker streamlines the deployment process and enhances scalability. By leveraging these powerful tools, you can focus on writing code rather than managing infrastructure. With the steps outlined in this article, you are well on your way to creating your own serverless applications. Embrace the serverless revolution and watch your development workflow transform!