How to Create Lambda Function in AWS: A Step-by-Step Guide!

This article offers a professional, step-by-step guide on how to create a Lambda function in AWS, specially written for beginners who want to understand serverless computing in a simple and practical way.

In today’s cloud world, developers no longer want to manage servers, operating systems, or scaling issues. They want to focus only on writing code. AWS Lambda makes this possible by allowing you to run code without provisioning or managing servers.

In this guide, we will clearly explain what AWS Lambda is, how it works, and how you can create your first Lambda function step by step, even if you have never used AWS before.

Let’s explore it together!

What Is AWS Lambda?

AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It allows you to run your code without creating or managing servers.

In simple words, AWS Lambda runs your code only when needed and automatically handles:

• Server provisioning
• Scaling
• Availability
• Maintenance

You just upload your code, and AWS Lambda executes it when an event happens.

Real-Life Example:

Think of AWS Lambda like electricity at home. You don’t run a power plant. You just switch on the button and pay only for the units you use.

What Does “Serverless” Really Mean?

“Serverless” does not mean there are no servers. It means you don’t manage them.

AWS:

• Handles servers
• Scales automatically
• Takes care of failures

You:

• Write code
• Define triggers
• Pay only for usage

How AWS Lambda Works (Internal Flow)

AWS Lambda follows an event-driven architecture.

1. Basic Flow:

1. An event occurs (API request, file upload, cron job, etc.)
2. AWS Lambda is triggered
3. Lambda runs your function code
4. The result is returned
5. Function stops automatically

2. Internal Lifecycle:

• Event Source → API Gateway / S3 / EventBridge
• Lambda Function → Executes code
• IAM Role → Grants permissions
• CloudWatch Logs → Monitoring & debugging

3. Cold Start vs Warm Start:

• Cold Start: First execution, slightly slower
• Warm Start: Reused environment, faster execution

Key Features of AWS Lambda

• Fully serverless execution
• Automatic scaling
• Pay-per-execution pricing
• Multiple programming languages
• Built-in monitoring (CloudWatch)
• Secure by default with IAM
• Integrates with 200+ AWS services

Common Use Cases of AWS Lambda

AWS Lambda is widely used in real-world applications:

• Backend APIs
• File processing (S3 upload)
• Scheduled cron jobs
• Data transformation
• Chatbots
• Automation scripts
• IoT data handling
• Email notifications

Prerequisites to Create AWS Lambda Function

Before creating a Lambda function, you need:

• An AWS account
• Basic programming knowledge
• Understanding of events & triggers
• Basic idea of IAM (permissions)

No advanced server knowledge is required.

Programming Languages Supported by AWS Lambda

AWS Lambda supports multiple runtimes:

• Python (most popular)
• Node.js
• Java
• Go
• C#
• Ruby
• Custom runtimes (Docker-based)

For beginners, Python or Node.js is recommended.

How to Create Lambda Function in AWS?

Now let’s create a Lambda function step by step.

1. Login to AWS Console

• Go to aws.amazon.com
• Login to AWS Management Console

2. Open AWS Lambda Service

• Search for Lambda in AWS services
• Click on AWS Lambda

3. Click “Create Function”

You will see three options:

• Author from scratch
• Use a blueprint
• Container image

Choose Author from scratch.

4. Configure Basic Function Settings

Fill the details:

• Function name: helloLambda
• Runtime: Python 3.x
• Architecture: x86_64

5. Configure Execution Role (IAM)

Select:

• Create a new role with basic Lambda permissions

This allows Lambda to write logs to CloudWatch.

6. Create the Function

Click the Create function. Your Lambda function is now created 🎉

Writing Your First AWS Lambda Code (Python)

AWS Lambda uses a handler function.

1. Default Python Code:

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

2. Explanation:

• event: Input data
• context: Runtime information
• return: Response

How to Deploy a Lambda Function?

Whenever you edit the code:

• Click Deploy
• AWS updates the function instantly

No server restart required.

How to Test AWS Lambda Function

1. Click Test
2. Create a test event
3. Click Invoke
4. Check output & logs

You can see logs in CloudWatch.

Adding Triggers to AWS Lambda

Lambda works with triggers.

Common Triggers:

• API Gateway (HTTP requests)
• S3 (file uploads)
• DynamoDB
• EventBridge (cron jobs)
• SNS / SQS

Example: When a file is uploaded to S3 → Lambda runs automatically.

AWS Lambda with API Gateway (Overview)

API Gateway allows you to:

• Expose Lambda as a REST or HTTP API
• Handle request & response
• Secure endpoints

Flow:

User → API Gateway → Lambda → Response

This is commonly used for serverless backend APIs.

AWS Lambda Pricing Explained (Simple Words)

AWS Lambda follows pay-as-you-go pricing.

1. Free Tier:

• 1 million requests per month
• 400,000 GB-seconds compute time

2. Paid Usage Depends On:

• Number of requests
• Execution duration
• Memory allocated

You only pay when your function runs.

AWS Lambda Limits You Must Know

• Max execution time: 15 minutes
• Memory: 128 MB to 10 GB
• Payload size limit
• Concurrent execution limits

These limits are sufficient for most applications.

AWS Lambda vs EC2 (Quick Comparison)

Feature	AWS Lambda	EC2
Server management	No	Yes
Scaling	Automatic	Manual
Pricing	Per execution	Per hour
Maintenance	AWS handles	You handle
Best for	Event-based tasks	Long-running apps

Best Practices for AWS Lambda

• Keep functions small
• One function = one responsibility
• Use environment variables
• Optimize memory allocation
• Monitor logs
• Handle errors properly

Common Mistakes Beginners Make

• Giving full IAM permissions
• Ignoring timeouts
• Hardcoding secrets
• Creating large functions
• Not monitoring logs

Avoiding these improves performance and security.

AWS Lambda Security Best Practices

• Follow least-privilege IAM
• Use AWS Secrets Manager
• Enable CloudWatch logs
• Secure API Gateway endpoints
• Avoid public access unless required

5+ Tools Commonly Used with AWS Lambda

To build a complete serverless application, AWS Lambda is commonly used with several other AWS tools that support data storage, APIs, automation, and monitoring.

1. AWS API Gateway

AWS API Gateway is the most commonly used service with AWS Lambda. AWS API Gateway allows you to expose your Lambda function as an HTTP or REST API so users can access it through a URL.

How it works with Lambda:

1. User sends a request (GET, POST, PUT, DELETE)
2. API Gateway receives the request
3. API Gateway triggers the Lambda function
4. Lambda processes the request
5. Response is returned to the user

Real-world example:

• Login API
• Signup API
• Contact form submission
• Mobile app backend
• Serverless website backend

Why it’s important:

• No server management
• Built-in security (API keys, auth)
• Scales automatically
• Perfect for serverless APIs

Note: Most AWS Lambda projects use API Gateway

2. AWS CloudWatch

AWS CloudWatch is the monitoring and logging service for AWS Lambda. it does CloudWatch automatically:

• Stores logs
• Tracks errors
• Measures performance
• Shows execution metrics

CloudWatch helps you see what your Lambda function is doing behind the scenes.

What CloudWatch logs:

• Console output (print/logs)
• Errors and exceptions
• Execution time
• Memory usage
• Invocation count

Real-world example:

• Debugging failed Lambda executions
• Monitoring slow functions
• Tracking usage spikes

Why it’s important:

• Without CloudWatch, debugging Lambda is almost impossible
• Helps optimize cost and performance
• Essential for production apps

Note: Every Lambda function automatically integrates with CloudWatch

3. Amazon DynamoDB

DynamoDB is a fully managed NoSQL database commonly used with AWS Lambda. It stores and retrieves data at very high speed without managing servers.

How it works with Lambda:

• Lambda writes data to DynamoDB
• Lambda reads data from DynamoDB
• DynamoDB can also trigger Lambda on data changes

Real-world examples:

• User profiles
• Session storage
• Order data
• Application logs
• IoT sensor data

Why Lambda + DynamoDB is powerful:

• Both are serverless
• Both scales automatically
• Very low operational cost
• Ideal for modern web & mobile apps

Note: Lambda + DynamoDB = true serverless backend

4. Amazon S3 (Simple Storage Service)

Amazon S3 is used to store files, images, videos, backups, and logs. it does S3 stores objects (files) securely and reliably.

How it works with Lambda:

• File uploaded to S3 → Lambda triggered
• Lambda processes the file
• Lambda stores results back to S3

Real-world examples:

• Image resizing
• Video processing
• File validation
• Backup automation
• CSV or JSON file processing

Example scenario:

1. User uploads image to S3
2. Lambda resizes the image
3. Processed image is saved back to S3

Why it’s important:

• Event-driven architecture
• No manual intervention
• Cost-effective storage

Note: S3 + Lambda is widely used for automation

5. Amazon EventBridge

EventBridge is used for event-based automation and scheduling.

What it does:

• Triggers Lambda based on events
• Runs Lambda on a schedule (cron jobs)
• Connects multiple AWS services

Common use cases:

• Daily reports
• Cleanup tasks
• Scheduled backups
• Syncing data
• Monitoring system health

Example:

• Run Lambda every day at 12 AM
• Trigger Lambda when EC2 state changes
• Trigger Lambda when payment is completed

Why it’s important:

• Replaces traditional cron servers
• Fully serverless scheduling
• Reliable and scalable

Note: EventBridge is the backbone of serverless automation

6. AWS IAM (Identity and Access Management)

IAM is the security foundation of AWS Lambda. It controls who can access what in AWS.

IAM roles in Lambda:

Each Lambda function runs with an IAM role that defines:

• Which services can it access
• What actions can it perform

Example permissions:

• Read from S3
• Write to DynamoDB
• Publish to SNS
• Write logs to CloudWatch

Why IAM is critical:

• Prevents unauthorized access
• Protects sensitive data
• Follows the least-privilege principle

Note: Always give the minimum required permissions only

When You Should NOT Use AWS Lambda

AWS Lambda is not suitable for:

• Long-running processes
• Heavy CPU workloads
• Persistent connections
• Real-time streaming servers

In such cases, EC2 or containers are better.

Future of AWS Lambda & Serverless

Serverless is growing rapidly:

• Lower infrastructure cost
• Faster development
• Better scalability
• Strong integration with AI & automation

AWS Lambda will continue to be a core cloud service.

FAQs:)

Conclusion:)

AWS Lambda is one of the most powerful services offered by Amazon Web Services. It allows developers to build scalable, cost-effective, and serverless applications without worrying about infrastructure management. By learning how to create a Lambda function in AWS, you unlock the foundation of modern cloud and serverless architecture.

“One-to-one marketing is the bridge between customer attention and brand retention.” — Mr Rahman, CEO Oflox®

Read also:)

• What Is Serverless Computing: A-to-Z Guide for Beginners!
• 5+ Best VPN for India Server Free (2026 Guide for Indian Users)
• What Is a Virtual Server: A-to-Z Guide for Beginners!

Have you tried creating an AWS Lambda function for your project? Share your experience or ask your questions in the comments below — we’d love to hear from you!