Deploying a Serverless Application Using Terraform

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Serverless architectures have transformed cloud computing by eliminating infrastructure management while ensuring high scalability and cost efficiency. In this guide, we will deploy a serverless application using Terraform, leveraging AWS Lambda, API Gateway, and S3 to build a fully automated and scalable solution.

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Why Serverless?

No infrastructure management
Auto-scaling based on demand
Pay-per-use pricing model
Faster development and deployment

Steps to Deploy the Serverless Application

We will:

Set up infrastructure with Terraform.
Package and deploy a Lambda function.
Integrate it with API Gateway.
Test the entire workflow.

Task 1: Create Infrastructure

1. Create a Directory and Configure Terraform

mkdir serverless &amp;&amp; cd serverless

1	mkdir serverless && cd serverless

2. Define AWS Provider and S3 Bucket

Create main.tf:

provider "aws" {  
  region = var.aws_region  
}  

resource "random_pet" "lambda_bucket_name" {  
  prefix = "learn-terraform-functions"  
  length = 4  
}  

resource "aws_s3_bucket" "lambda_bucket" {  
  bucket = random_pet.lambda_bucket_name.id  
}  

resource "aws_s3_bucket_ownership_controls" "lambda_bucket" {  
  bucket = aws_s3_bucket.lambda_bucket.id  
  rule {  
    object_ownership = "BucketOwnerPreferred"  
  }  
}  

resource "aws_s3_bucket_acl" "lambda_bucket" {  
  depends_on = [aws_s3_bucket_ownership_controls.lambda_bucket]  
  bucket = aws_s3_bucket.lambda_bucket.id  
  acl    = "private"  
}

provider "aws" {

region = var.aws_region

}

resource "random_pet" "lambda_bucket_name" {

prefix = "learn-terraform-functions"

length = 4

}

resource "aws_s3_bucket" "lambda_bucket" {

bucket = random_pet.lambda_bucket_name.id

}

resource "aws_s3_bucket_ownership_controls" "lambda_bucket" {

bucket = aws_s3_bucket.lambda_bucket.id

rule {

object_ownership = "BucketOwnerPreferred"

}

resource "aws_s3_bucket_acl" "lambda_bucket" {

depends_on = [aws_s3_bucket_ownership_controls.lambda_bucket]

bucket = aws_s3_bucket.lambda_bucket.id

acl = "private"

}

3. Define Outputs

Create output.tf:

output "lambda_bucket_name" {  
  description = "Name of the S3 bucket used to store function code."  
  value = aws_s3_bucket.lambda_bucket.id  
}

output "lambda_bucket_name" {

description = "Name of the S3 bucket used to store function code."

value = aws_s3_bucket.lambda_bucket.id

}

4. Define Variables

Create variables.tf:

variable "aws_region" {  
  description = "AWS region for all resources."  
  type    = string  
  default = "us-east-1"  
}

variable "aws_region" {

description = "AWS region for all resources."

type = string

default = "us-east-1"

}

5. Initialize and Apply Terraform

terraform init  
terraform apply --auto-approve

1 2	terraform init terraform apply --auto-approve

Task 2: Create and Upload Lambda Function Archive

1. Create a Node.js Lambda Function

mkdir hello-world &amp;&amp; cd hello-world

1	mkdir hello-world && cd hello-world

Create hello.js:

module.exports.handler = async (event) =&gt; {  
  console.log('Event: ', event);  
  let responseMessage = 'Hello, World!';  
  return {  
    statusCode: 200,  
    headers: {  
      'Content-Type': 'application/json',  
    },  
    body: JSON.stringify({  
      message: responseMessage,  
    }),  
  }  
}

module.exports.handler = async (event) => {

console.log('Event: ', event);

let responseMessage = 'Hello, World!';

return {

statusCode: 200,

headers: {

'Content-Type': 'application/json',

body: JSON.stringify({

message: responseMessage,

}),

}

2. Package and Upload the Function

Create s3_object.tf:

data "archive_file" "lambda_hello_world" {  
  type = "zip"  
  source_dir  = "${path.module}/hello-world"  
  output_path = "${path.module}/hello-world.zip"  
}  

resource "aws_s3_object" "lambda_hello_world" {  
  bucket = aws_s3_bucket.lambda_bucket.id  
  key    = "hello-world.zip"  
  source = data.archive_file.lambda_hello_world.output_path  
  etag = filemd5(data.archive_file.lambda_hello_world.output_path)  
}

data "archive_file" "lambda_hello_world" {

type = "zip"

source_dir = "${path.module}/hello-world"

output_path = "${path.module}/hello-world.zip"

}

resource "aws_s3_object" "lambda_hello_world" {

bucket = aws_s3_bucket.lambda_bucket.id

key = "hello-world.zip"

source = data.archive_file.lambda_hello_world.output_path

etag = filemd5(data.archive_file.lambda_hello_world.output_path)

}

3. Apply Configuration

terraform init -upgrade  
terraform apply --auto-approve

1 2	terraform init -upgrade terraform apply --auto-approve

Task 3: Create the Lambda Function

1. Define Lambda Function and IAM Role

Create lambda.tf:

resource "aws_lambda_function" "hello_world" {  
  function_name = "MeharHelloWorld"  
  s3_bucket = aws_s3_bucket.lambda_bucket.id  
  s3_key    = aws_s3_object.lambda_hello_world.key  
  runtime = "nodejs20.x"  
  handler = "hello.handler"  
  source_code_hash = data.archive_file.lambda_hello_world.output_base64sha256  
  role = aws_iam_role.lambda_exec.arn  
}  

resource "aws_cloudwatch_log_group" "hello_world" {  
  name = "/aws/lambda/${aws_lambda_function.hello_world.function_name}"  
  retention_in_days = 30  
}  

resource "aws_iam_role" "lambda_exec" {  
  name = "mehar-serverless_lambda"  
  assume_role_policy = jsonencode({  
    Version = "2012-10-17"  
    Statement = [{  
      Action = "sts:AssumeRole"  
      Effect = "Allow"  
      Sid    = ""  
      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"  
}

resource "aws_lambda_function" "hello_world" {

function_name = "MeharHelloWorld"

s3_bucket = aws_s3_bucket.lambda_bucket.id

s3_key = aws_s3_object.lambda_hello_world.key

runtime = "nodejs20.x"

handler = "hello.handler"

source_code_hash = data.archive_file.lambda_hello_world.output_base64sha256

role = aws_iam_role.lambda_exec.arn

}

resource "aws_cloudwatch_log_group" "hello_world" {

name = "/aws/lambda/${aws_lambda_function.hello_world.function_name}"

retention_in_days = 30

}

resource "aws_iam_role" "lambda_exec" {

name = "mehar-serverless_lambda"

assume_role_policy = jsonencode({

Version = "2012-10-17"

Statement = [{

Action = "sts:AssumeRole"

Effect = "Allow"

Sid = ""

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"

}

2. Add Lambda Output

Create outputs_lambda.tf:

output "function_name" {  
  description = "Name of the Lambda function."  
  value = aws_lambda_function.hello_world.function_name  
}

output "function_name" {

description = "Name of the Lambda function."

value = aws_lambda_function.hello_world.function_name

}

3. Apply and Test Lambda

terraform apply --auto-approve  
aws lambda invoke --region=us-east-1 --function-name=$(terraform output -raw function_name) response.json  
cat response.json

terraform apply --auto-approve

aws lambda invoke --region=us-east-1 --function-name=$(terraform output -raw function_name) response.json

cat response.json

Task 4: Create an HTTP API with API Gateway

1. Define API Gateway Resources

Create api.tf:

resource "aws_apigatewayv2_api" "lambda" {  
  name          = "mehar-serverless_lambda_gw"  
  protocol_type = "HTTP"  
}  

resource "aws_apigatewayv2_stage" "lambda" {  
  api_id = aws_apigatewayv2_api.lambda.id  
  name        = "mehar-serverless_lambda_stage"  
  auto_deploy = true  
  access_log_settings {  
    destination_arn = aws_cloudwatch_log_group.api_gw.arn  
    format = jsonencode({  
      requestId               = "$context.requestId"  
      sourceIp                = "$context.identity.sourceIp"  
      requestTime             = "$context.requestTime"  
      protocol                = "$context.protocol"  
      httpMethod              = "$context.httpMethod"  
      resourcePath            = "$context.resourcePath"  
      routeKey                = "$context.routeKey"  
      status                  = "$context.status"  
      responseLength          = "$context.responseLength"  
      integrationErrorMessage = "$context.integrationErrorMessage"  
    })  
  }  
}  

resource "aws_apigatewayv2_integration" "hello_world" {  
  api_id = aws_apigatewayv2_api.lambda.id  
  integration_uri    = aws_lambda_function.hello_world.invoke_arn  
  integration_type   = "AWS_PROXY"  
  integration_method = "POST"  
}  

resource "aws_apigatewayv2_route" "hello_world" {  
  api_id = aws_apigatewayv2_api.lambda.id  
  route_key = "GET /hello"  
  target    = "integrations/${aws_apigatewayv2_integration.hello_world.id}"  
}  

resource "aws_cloudwatch_log_group" "api_gw" {  
  name = "/aws/api_gw/${aws_apigatewayv2_api.lambda.name}"  
  retention_in_days = 30  
}  

resource "aws_lambda_permission" "api_gw" {  
  statement_id  = "AllowExecutionFromAPIGateway"  
  action        = "lambda:InvokeFunction"  
  function_name = aws_lambda_function.hello_world.function_name  
  principal     = "apigateway.amazonaws.com"  
  source_arn = "${aws_apigatewayv2_api.lambda.execution_arn}/*/*"  
}

resource "aws_apigatewayv2_api" "lambda" {

name = "mehar-serverless_lambda_gw"

protocol_type = "HTTP"

}

resource "aws_apigatewayv2_stage" "lambda" {

api_id = aws_apigatewayv2_api.lambda.id

name = "mehar-serverless_lambda_stage"

auto_deploy = true

access_log_settings {

destination_arn = aws_cloudwatch_log_group.api_gw.arn

format = jsonencode({

requestId = "$context.requestId"

sourceIp = "$context.identity.sourceIp"

requestTime = "$context.requestTime"

protocol = "$context.protocol"

httpMethod = "$context.httpMethod"

resourcePath = "$context.resourcePath"

routeKey = "$context.routeKey"

status = "$context.status"

responseLength = "$context.responseLength"

integrationErrorMessage = "$context.integrationErrorMessage"

})

}

resource "aws_apigatewayv2_integration" "hello_world" {

api_id = aws_apigatewayv2_api.lambda.id

integration_uri = aws_lambda_function.hello_world.invoke_arn

integration_type = "AWS_PROXY"

integration_method = "POST"

}

resource "aws_apigatewayv2_route" "hello_world" {

api_id = aws_apigatewayv2_api.lambda.id

route_key = "GET /hello"

target = "integrations/${aws_apigatewayv2_integration.hello_world.id}"

}

resource "aws_cloudwatch_log_group" "api_gw" {

name = "/aws/api_gw/${aws_apigatewayv2_api.lambda.name}"

retention_in_days = 30

}

resource "aws_lambda_permission" "api_gw" {

statement_id = "AllowExecutionFromAPIGateway"

action = "lambda:InvokeFunction"

function_name = aws_lambda_function.hello_world.function_name

principal = "apigateway.amazonaws.com"

source_arn = "${aws_apigatewayv2_api.lambda.execution_arn}/*/*"

}

2. Add API Output

Create outputs_api.tf:

output “base_url” {
description = “Base URL for API Gateway stage.”
value = aws_apigatewayv2_stage.lambda.invoke_url
}

3. Apply and Test API Gateway

terraform apply --auto-approve  
curl "$(terraform output -raw base_url)/hello"

1 2	terraform apply --auto-approve curl "$(terraform output -raw base_url)/hello"

Task 5: Clean Up Resources

terraform destroy --auto-approve  
cd ~ &amp;&amp; rm -rf serverless

1 2	terraform destroy --auto-approve cd ~ && rm -rf serverless

Conclusion

By following this guide, you have successfully deployed a serverless application using Terraform, integrating AWS Lambda, API Gateway, and S3. This setup ensures scalability, cost efficiency, and ease of management while eliminating the need for manual infrastructure handling.

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About CloudThat

CloudThat is a leading provider of Cloud Training and Consulting services with a global presence in India, the USA, Asia, Europe, and Africa. Specializing in AWS, Microsoft Azure, GCP, VMware, Databricks, and more, the company serves mid-market and enterprise clients, offering comprehensive expertise in Cloud Migration, Data Platforms, DevOps, IoT, AI/ML, and more.

CloudThat is the first Indian Company to win the prestigious Microsoft Partner 2024 Award and is recognized as a top-tier partner with AWS and Microsoft, including the prestigious ‘Think Big’ partner award from AWS and the Microsoft Superstars FY 2023 award in Asia & India. Having trained 650k+ professionals in 500+ cloud certifications and completed 300+ consulting projects globally, CloudThat is an official AWS Advanced Consulting Partner, Microsoft Gold Partner, AWS Training Partner, AWS Migration Partner, AWS Data and Analytics Partner, AWS DevOps Competency Partner, AWS GenAI Competency Partner, Amazon QuickSight Service Delivery Partner, Amazon EKS Service Delivery Partner, AWS Microsoft Workload Partners, Amazon EC2 Service Delivery Partner, Amazon ECS Service Delivery Partner, AWS Glue Service Delivery Partner, Amazon Redshift Service Delivery Partner, AWS Control Tower Service Delivery Partner, AWS WAF Service Delivery Partner, Amazon CloudFront, Amazon OpenSearch, AWS DMS, AWS Systems Manager, Amazon RDS, and many more.

WRITTEN BY Mehar Nafis

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Deploying a Serverless Application Using Terraform

Transform Your Career with AWS Certifications

Why Serverless?

Steps to Deploy the Serverless Application

Task 1: Create Infrastructure

1. Create a Directory and Configure Terraform

2. Define AWS Provider and S3 Bucket

3. Define Outputs

4. Define Variables

5. Initialize and Apply Terraform

Task 2: Create and Upload Lambda Function Archive

1. Create a Node.js Lambda Function

2. Package and Upload the Function

3. Apply Configuration

Task 3: Create the Lambda Function

1. Define Lambda Function and IAM Role

2. Add Lambda Output

3. Apply and Test Lambda

Task 4: Create an HTTP API with API Gateway

1. Define API Gateway Resources

2. Add API Output

3. Apply and Test API Gateway

Task 5: Clean Up Resources

Conclusion

Earn Multiple AWS Certifications for the Price of Two

About CloudThat

WRITTEN BY Mehar Nafis

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