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Title: Building a Serverless URL Shortener with AWS Lambda, API Gateway, and DynamoDB
Have you ever needed to share a long, unwieldy URL and wished there was an easy way to shorten it? URL shorteners are handy tools that generate a short, unique alias for a long URL, making it easier to share links across different platforms. In this blog post, we'll explore how to build a serverless URL shortener
The Serverless Approach Going serverless means you don't have to worry about provisioning or managing any servers. Instead, you build and run your application using cloud services that automatically scale based on demand. For our URL shortener, we'll be using:
AWS Lambda to run our URL shortening and redirection logic
Amazon API Gateway to expose HTTP endpoints for our Lambda functions
Amazon DynamoDB as a NoSQL database to store the URL mappings
Terraform for provisioning all the AWS resources
The Architecture Here's a high-level overview of how our serverless URL shortener will work:
A client sends a POST request to the API Gateway endpoint with the long URL they want to shorten.
API Gateway invokes the "create URL" Lambda function.
The Lambda function generates a unique short ID, stores the mapping (short ID -> long URL) in DynamoDB, and returns the short ID.
To access the original URL, the client sends a GET request to the API Gateway endpoint with the short ID.
API Gateway invokes the "get URL" Lambda function.
The Lambda function looks up the short ID in DynamoDB and returns an HTTP 301 redirect to the original long URL.
Sounds simple enough, right? Let's dive into the implementation details.
The Terraform Setup We'll be using Terraform to provision all the required AWS resources for our URL shortener. The main.tf file defines the core infrastructure:
A DynamoDB table to store the URL mappings
An IAM role and policy to grant Lambda functions access to DynamoDB
Two Lambda functions: one for creating short URLs, another for retrieving the original URLs
An API Gateway HTTP API with routes and integrations mapped to the Lambda functions
The Lambda Functions The URL shortening logic lives in the create_url.py Lambda function:
It parses the request body to get the original long URL.
Generates a unique 8-character short ID by hashing the long URL and current timestamp.
Stores the short ID -> long URL mapping in DynamoDB.
Returns the short ID in the response.
The get_url.py Lambda function handles URL redirection:
Extracts the short ID from the request path parameters.
Queries DynamoDB for the corresponding long URL.
If found, returns an HTTP 301 redirect to the long URL.
If not found, returns a 404 error.
Using the URL Shortener After deploying the Terraform configuration, you'll get an API Gateway endpoint URL. To create a new shortened URL, send a POST request with the long URL in the request body:
This will return a JSON response with the generated short ID, e.g., {"short_id": "a1b2c3d4"}.
To access the original URL, simply send a GET request with the short ID:
curl -L <api_endpoint>/a1b2c3d4
The -L flag in curl follows the HTTP 301 redirect to the long URL.
So that was the high level explainantion, Now let us get to implementation with all necessary detaiils.
Lets leverage LLMS and AI for this purpose to make the job easy. Let us use Amazon Q to help us with the problem statement.
amazon q
q
1. Here you can see Q has given us folder structure as well as code now lets copy that code into our files I am pasting code for each filr a. tf b. tf c. tf d. tf e. Lambda i. Create-url.py ii. Get-url.py
2. Main.tf
main code
Okay so here is the entire code snippet :-
Explanation of redirect_url.py (Lambda Function for URL Redirection) :-
Imports Required Libraries - json : Handles JSON response - os : Fetches environment variables (DynamoDB table name). - boto3 : AWS SDK for Python to interact with DynamoDB. - Key : Helps query DynamoDB items.
Initialize DynamoDB Table - Reads DYNAMODB_TABLE from environment variables. - Connects to the DynamoDB table.
Lambda Function ( lambda_handler ) - Extracts short_id from the URL path parameters. - Queries DynamoDB for the corresponding long_url . - If found, returns an HTTP 301 redirect to long_url . - If not found, returns HTTP 404. - If an error occurs, returns HTTP 500 with the error message.
Example Workflow:- 📌 Request:- GET /a1b2c3d4
📌 Response (Redirect to long URL):- HTTP/1.1 301 Moved Permanently Location: https://example.com/very-long-url
📌 If short_id not found: { "error": "URL not found" }
This function enables URL redirection by mapping short links to long URLs stored in DynamoDB.
function
we paste all code with respect to their files now we can run to process terraform commands
teraform output
teraform2
Now our infra is ready you can see api endpoint below now run following command to shorten url. To create a new shortened URL, use the POST endpoint. For example:
This will return a response like:- { "short_id": "a1b2c3d4" }
url response
To use the shortened URL, simply access:-
url2
note :- (Replace a1b2c3d4 with the short_id you received)
This will redirect you to your original URL (https://example.com in this example). Some important notes:-
The -L flag in curl follows the redirect The API endpoint will look something like: https://abc123def.execute-api.useast-1.amazonaws.com/prod Make sure to keep the API endpoint URL for future use The shortened URLs are stored in DynamoDB and will persist until deleted.
Wrapping Up In this blog post, we explored how to build a serverless URL shortener using AWS services like Lambda, API Gateway, and DynamoDB. By leveraging serverless architectures, we can build and deploy applications without worrying about provisioning or managing servers.
The Terraform configuration makes it easy to provision all the required AWS resources, while the Python code running on Lambda handles the core URL shortening and redirection logic. With just a few API calls, users can shorten long URLs and access the original URLs through short, easy-to-share links.
This is just one example of how serverless architectures can simplify application development and deployment. As cloud services continue to evolve, we can expect to see more innovative use cases for serverless computing.
Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.
