Serverless Computing with AWS Lambda

Run Code Without Servers — Automatically Scalable and Event-Driven

AWS Lambda is at the heart of serverless architecture—it allows developers to run backend code without provisioning or managing servers. You just write the function, deploy it, and AWS handles the rest: scalability, availability, and infrastructure.

This chapter provides deep insights, real use cases, architecture diagrams, and live code examples in Python and Node.js.

⚡ What is AWS Lambda?

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying infrastructure.

• No servers to manage
• You pay only for the compute time you consume
• Automatically scales from zero to thousands of requests per second
• Supports multiple runtimes: Python, Node.js, Java, Go, .NET

🧱 Key Concepts in Lambda

How AWS Lambda Works – Architecture Diagram (ASCII)

    [Event Source]
        (S3 / API Gateway / DynamoDB / Schedule)
               ↓
         +-------------+
         |  AWS Lambda |
         +-------------+
               ↓
      [Your Code Executes]
               ↓
    [Other AWS Services or Response]

    [Event Source]
        (S3 / API Gateway / DynamoDB / Schedule)
               ↓
         +-------------+
         |  AWS Lambda |
         +-------------+
               ↓
      [Your Code Executes]
               ↓
    [Other AWS Services or Response]

Common Event Sources (Triggers)

✅ AWS supports dozens of event sources, both native and third-party.

Creating a Lambda Function (Console & CLI)

✅ Using Console (Quick Steps):

1. Go to AWS Lambda → Create function
2. Choose Author from Scratch
3. Name: image-processor
4. Runtime: Python 3.9
5. Permissions: Create a new role with S3 access
6. Click Create Function
7. Add code + test event
8. Save and Deploy

✅ Using AWS CLI

zip function.zip index.py

aws lambda create-function \
  --function-name my-function \
  --runtime python3.9 \
  --role arn:aws:iam::123456789012:role/my-lambda-role \
  --handler index.lambda_handler \
  --zip-file fileb://function.zip

zip function.zip index.py

aws lambda create-function \
  --function-name my-function \
  --runtime python3.9 \
  --role arn:aws:iam::123456789012:role/my-lambda-role \
  --handler index.lambda_handler \
  --zip-file fileb://function.zip

Example Lambda Code

🔸 Python (Resizing an Image in S3)

import boto3
from PIL import Image
import io

def lambda_handler(event, context):
    s3 = boto3.client('s3')
    bucket = event['Records'][0]['s3']['bucket']['name']
    key = event['Records'][0]['s3']['object']['key']

    response = s3.get_object(Bucket=bucket, Key=key)
    image = Image.open(response['Body'])

    image.thumbnail((128, 128))
    buffer = io.BytesIO()
    image.save(buffer, 'JPEG')
    buffer.seek(0)

    s3.put_object(Bucket=bucket, Key=f"thumbs/{key}", Body=buffer)
    return {"status": "Thumbnail created"}

import boto3
from PIL import Image
import io

def lambda_handler(event, context):
    s3 = boto3.client('s3')
    bucket = event['Records'][0]['s3']['bucket']['name']
    key = event['Records'][0]['s3']['object']['key']

    response = s3.get_object(Bucket=bucket, Key=key)
    image = Image.open(response['Body'])

    image.thumbnail((128, 128))
    buffer = io.BytesIO()
    image.save(buffer, 'JPEG')
    buffer.seek(0)

    s3.put_object(Bucket=bucket, Key=f"thumbs/{key}", Body=buffer)
    return {"status": "Thumbnail created"}

🔹 Node.js (Return JSON API Response)

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

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

Lambda Layers – Reusable Code and Libraries

Layers are ZIP archives of libraries or dependencies that can be shared across Lambda functions.

• Use for: Python packages (e.g., Pandas), image libraries, Node.js modules
• Speeds up deployment & promotes reuse

aws lambda publish-layer-version \
  --layer-name my-layer \
  --zip-file fileb://layer.zip \
  --compatible-runtimes python3.9

aws lambda publish-layer-version \
  --layer-name my-layer \
  --zip-file fileb://layer.zip \
  --compatible-runtimes python3.9

Lambda Limits (as of 2025)

🧠 Use Provisioned Concurrency to reduce cold start latency.

Monitoring Lambda Functions

✅ Always enable logs and metrics for production functions.

🔐 Security & Permissions

• Lambda assumes an IAM Role to access resources (e.g., S3, DynamoDB)
• Follow least privilege when creating the role
• Use environment variables + KMS for secrets
• Set VPC access only if required (adds latency)

✅ Real-World Use Cases

Best Practices

Summary