How to Deploy Code in AWS Lambda: Step-by-Step Tutorial

Quick Summary

In this tutorial, you will learn how to deploy code in AWS Lambda, from setting up your function to optimizing its performance. It’s your go-to guide for using serverless computing to run your cloud functions more efficiently.

Introduction

AWS Lambda is a serverless computing service that runs your code without the need to set up or manage servers. All you need to do is write your code and upload it; Lambda takes care of the rest. It automatically runs your code in response to events like file uploads, button clicks, or API calls.

For example, when a user uploads a file or clicks a button, Lambda can automatically run your code in response. It scales automatically based on demand and charges you only for the actual compute time, making it a cost-effective and straightforward way to build and run applications.

Whether you’re new to serverless or looking to simplify how you deploy apps, this guide walks you through each step. We’ll cover creating an AWS account, setting up your Lambda function, configuring triggers, and monitoring performance. By the end, you’ll know how to deploy code in AWS Lambda effortlessly.
Let’s get started!

How to Deploy Code in AWS Lambda in 10 Simple Steps

Here’s how you can easily deploy code in AWS Lambda with this step-by-step guide.

If you don’t have an AWS account yet:
1. Visit the AWS homepage.
2. Click create an AWS account.
3. Follow the registration process, and provide your email, password, and billing information.
4. Once your account is activated, log in to the AWS Management Console.
Tip: AWS offers a Free Tier, which includes 1 million free Lambda requests per month. Explore it to keep costs low.

Step 2: Create Your Lambda Function

Follow the steps given below to build your Lambda function:

1. Open the Lambda Console

In the AWS Management Console, search for Lambda in the search bar.
Click on AWS Lambda to open the Lambda dashboard.

2. Start a New Function

Click the Create function button.

CChoose Author from scratch.
Name your function (e.g., MyLambdaFunction).
Select the runtime and choose the programming language (e.g., Python, Node.js) for your code.

3. Permissions:

Select Create a new role with basic Lambda permissions. This creates an IAM role with the AWSLambdaBasicExecutionRole policy, allowing your function to write logs to CloudWatch.

Change Default Execution Role and Create Function

4. Create the Function

After filling in the details, click the Create function. AWS will set up your Lambda function and take you to the configuration page.

IAM Role Details

The default role is sufficient for simple functions, but you’ll need additional permissions if your function interacts with other AWS services (e.g., S3 or DynamoDB). For example, to allow S3 access, attach a policy like this:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "logs:CreateLogGroup",
        "logs:CreateLogStream",
        "logs:PutLogEvents"
      ],
      "Resource": "*"
    },
    {
      "Effect": "Allow",
      "Action": "s3:GetObject",
      "Resource": "arn:aws:s3:::example-bucket/*"
    }
  ]
}

Step 3: Add Your Code to Lambda

You can write code directly in the Lambda console or upload a zip file. Here’s how to do both:

Option 1: Inline Code Editor

For simple functions:

In the Function code section, select Edit code inline.
Write your code directly in the provided text editor. For example, a basic Python function:

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

Click Save.

Option 2: Upload Your Code

For complex applications or those with dependencies:
1. Prepare your code locally:

Python: Create a folder with your code (e.g., lambda_function.py) and a requirements.txt for dependencies. Install dependencies into the folder:

pip install -r requirements.txt -t .

Node.js: Create a folder with your code (e.g., index.js) and run:

npm install

2. Zip your code (including any external libraries or dependencies, not the folder itself).
3. In the Function code section, select Upload a .zip file.
4. Click Upload, select your zipped code, and click Save.

Example Node.js Function:

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

Step 4: Configure Lambda Function

Lambda allows you to adjust the memory, timeout, and other settings.

Adjust Memory and Timeout

1. In the Configuration tab, click General configuration > Edit.
2. Adjust:

Memory: Default is 128 MB. Increase for CPU-intensive tasks (note: CPU scales with memory).
Timeout: Default is 3 seconds. Increase for longer-running tasks (max 15 minutes).

3. Click Save.

Environment Variables

For configuration settings like API keys:
1. In the Configuration tab, select Environment variables > Edit.
2. Add key-value pairs, e.g., API_KEY = your-api-key.
3. For sensitive data, enable encryption:

Click Enable helpers for encryption in transit.
Use an AWS KMS key to encrypt the variable.

Security Tip: Follow the principle of least privilege. Only grant the IAM role permissions needed for your function’s tasks.

Step 5: Set Up a Trigger for Your Lambda Function

Triggers invoke your Lambda function. Popular triggers include API Gateway (for HTTP APIs) and S3 (for file uploads).

Example: API Gateway Trigger

1. In the Designer section, click + Add trigger.
2. Select API Gateway.
3. Configure:

API type: REST API.
Security: Open (for testing) or IAM (for production).

4. Click Add.
5. AWS creates an API endpoint. Test it by sending an HTTP request (e.g., via curl or Postman).

Example: S3 Trigger

1. Click + Add trigger and select S3.
2. Choose a bucket and event type (e.g., All objects create events).
3. Click Add.
Tip: Test trigger configurations in a non-production environment to avoid unexpected costs.

Effortlessly Deploy Code with AWS Lambda!
Hire AWS developers to optimize your Lambda functions and scale your cloud infrastructure seamlessly.

Step 6: Test Your Lambda Function

Testing helps ensure that your function works as expected before going live.
1. In the Test tab, click Configure test events.
2. Choose a template (e.g., Hello World or Amazon S3 Put).
3. Modify the event JSON if needed, e.g.:

{
  "key1": "value1"
}

4. Click Save and then Test.
5. Review the Execution results for output, logs, and errors.

Step 7: Monitor and Debug Your Lambda Function

View Logs

AWS Lambda integrates with Amazon CloudWatch, which captures logs for your function. You can view logs to check if your function worked correctly.

Go to the Monitoring tab in the Lambda console.
Click on View logs in CloudWatch.

Monitor Metrics
Lambda provides useful metrics like:

Invocation Count: The total number of times the function was triggered.
Duration: The time taken by the function to complete execution.
Errors: Any failures or issues encountered during the function’s execution.

Tip: Set up CloudWatch alarms to notify you of errors or high costs.

Step 8: Optimize and Manage Your Lambda Function

Optimize Performance

Memory: Increase memory to reduce execution time (but monitor costs).
Code: Optimize code to minimize runtime (e.g., avoid unnecessary loops).
Cold Starts: Use Provisioned Concurrency for latency-sensitive applications.

Cost Optimization

Lambda charges are based on invocations and compute time (GB-seconds). For example, 1 million invocations with 128 MB memory for 200 ms costs ~$0.20. To save costs:

Reduce memory allocation if possible.
Use AWS Budgets to monitor spending.

Versioning and Aliases

1. To save a version, click Actions > Publish new version.
2. Create aliases (e.g., prod, dev) to point to specific versions for easier management.

Step 9: Troubleshooting Common Issues

Timeout Error: Increase the timeout in General configuration or optimize code.
Permission Denied: Verify the IAM role has necessary permissions (e.g., S3 or DynamoDB access).
Module Not Found: Ensure all dependencies are included in the zip file.
Cold Start Delays: Enable Provisioned Concurrency or optimize code.

Step 10: Advanced Features and Next Steps

Lambda Layers

Use Layers to share code or dependencies across functions:
1. Create a zip file with your dependencies (e.g., Python libraries).
2. Upload it as a Layer in the Lambda console.
3. Attach the Layer to your function.

CI/CD Integration

Automate deployments with:

AWS SAM: Define infrastructure as code using template.yaml.
GitHub Actions: Set up a pipeline to deploy Lambda functions on code push.

EventBridge Triggers

Use Amazon EventBridge for event-driven architectures, e.g., triggering Lambda on a schedule or in response to AWS events.

Next Steps:

Build a serverless API with Lambda and API Gateway.
Process S3 uploads with Lambda for data pipelines.
Explore AWS Step Functions for orchestrating multiple Lambda functions.

Conclusion

Deploying code in AWS Lambda is quick and easy, thanks to the intuitive setup process and the power of serverless computing. Whether you’re running a simple script or a complex application, AWS Lambda allows you to focus on your code and leave the infrastructure to AWS.
Now that you’ve learned how to deploy code in AWS Lambda, you can confidently manage triggers, monitor performance, and optimize your function, all while saving time and resources. However, to ensure long-term efficiency and scalability, opt for AWS consulting services that offer expert-driven guidance to optimize your serverless architecture and maximize cloud performance.

Frequently Asked Questions (FAQs)

Which programming languages are supported by AWS Lambda?

AWS Lambda supports several programming languages, including Python, Node.js, Java, Go, .NET, and Ruby.

How does AWS Lambda handle scaling and concurrency?

Lambda automatically scales your application by running code in response to each trigger. Your code can be triggered thousands of times per second, and Lambda handles the scaling for you.

What are the different ways to deploy code to AWS Lambda?

You can deploy code to AWS Lambda by writing code directly in the AWS Management Console’s inline editor or by uploading a .zip file containing your code and dependencies.

How do I manage dependencies when deploying to AWS Lambda?

For Python, you can use pip install -r requirements.txt -t to install dependencies into your project directory before zipping and uploading. For Node.js, you can use npm install to install dependencies.

What is the purpose of the IAM role when creating a Lambda function?

The IAM role grants your Lambda function permissions to access AWS services and resources. For example, if your function needs to read from an S3 bucket, the IAM role must have the appropriate permissions.

How do I set up triggers for my Lambda function?

You can add triggers in the AWS Lambda console by selecting the desired service (e.g., API Gateway, S3) and configuring the event source.

How can I securely manage environment variables in AWS Lambda?

You can store sensitive information in environment variables and encrypt it using AWS Key Management Service (KMS).

Supercharge Your Code Deployment with AWS Lambda!

Leverage expert support to scale effortlessly and optimize performance in a serverless environment.

Build Your Agile Team

Hire Skilled Developer From Us

How to Deploy Code in AWS Lambda: A Complete Step-by-Step Guide

Table of Contents