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Rahul Joshi
Rahul Joshi

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Day 20 - AWS Lambda

#masterclassdevsecops #webdev #devops #lambda

Cloud computing has evolved dramatically over the last decade.

The journey looked something like this:

Physical Servers
        ↓
Virtual Machines
        ↓
Containers
        ↓
Serverless Computing
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One of the biggest innovations in cloud computing is AWS Lambda.

Instead of managing:

  • Servers
  • Operating Systems
  • Patching
  • Scaling
  • Capacity Planning

You simply upload code and AWS runs it.

This is the foundation of Serverless Computing.

What is AWS Lambda?

AWS Lambda is a serverless compute service that allows you to run code without provisioning or managing servers.

You upload a function and AWS executes it whenever an event occurs.

Example:

User Uploads Image
        ↓
S3 Event Triggered
        ↓
Lambda Function Runs
        ↓
Image Processed
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You only pay for execution time.

No execution means:

No Cost
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Why AWS Introduced Lambda

Before Lambda, deploying applications looked like this:

Provision EC2
       ↓
Install Runtime
       ↓
Deploy Application
       ↓
Monitor Servers
       ↓
Scale Infrastructure
       ↓
Patch OS
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Even small applications required infrastructure management.

AWS wanted developers to focus on:

Business Logic
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Instead of:

Infrastructure Management
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Thus Lambda was introduced in 2014.

What is Serverless?

Serverless does NOT mean servers don't exist.

Servers still exist.

AWS manages them for you.

Instead of:

You Manage Servers
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Lambda provides:

AWS Manages Servers
You Manage Code
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Lambda works

Example:

API Gateway
       ↓
Lambda
       ↓
DynamoDB
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Benefits of AWS Lambda

1. No Server Management

No:

  • EC2
  • OS updates
  • Capacity planning

2. Automatic Scaling

AWS automatically scales functions.

1 Request
      ↓
1 Lambda Instance

1000 Requests
      ↓
1000 Lambda Instances
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3. Pay Per Use

You only pay for:

Requests
+
Execution Duration
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4. Event Driven

Lambda reacts to events.

Examples:

  • API requests
  • S3 uploads
  • SNS notifications
  • SQS messages
  • DynamoDB streams

5. High Availability

AWS automatically distributes Lambda execution across Availability Zones.

Supported Programming Languages

AWS Lambda supports multiple runtimes.

Python

Popular for:

  • Automation
  • AI/ML
  • Data processing

Example:

import json

def lambda_handler(event, context):
    # TODO implement
    return {
        'statusCode': 200,
        'body': json.dumps('Hello from Lambda!')
    }
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Node.js

Popular for:

  • APIs
  • Web applications

Java

Popular for:

  • Enterprise workloads

.NET

Popular for:

  • Microsoft environments

Go

Popular for:

  • High performance
  • Fast startup

Custom Runtime

Using Custom Runtime API, you can run:

  • Rust
  • PHP
  • Other languages

Lambda Function Components

Every Lambda contains:

Function Code

Your business logic.

Runtime

Language execution environment.

Example:

Python 3.12
Node.js 20
Java 21
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Handler

Entry point of Lambda.

Example:

lambda_handler(event, context)
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AWS invokes this function.

Event

Input to the Lambda.

Example:

{
  "bucket": "images"
}
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Context

Runtime information.

Contains:

  • Request ID
  • Timeout
  • Memory

Lambda Execution Lifecycle 

Request Arrives
        ↓
Environment Created
        ↓
Function Runs
        ↓
Response Returned
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Understanding Cold Starts

One of the most important Lambda concepts.

Cold Start

When Lambda has no running execution environment:

Request Arrives
       ↓
Create Environment
       ↓
Load Runtime
       ↓
Execute Function
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Extra startup time occurs.

Warm Start

If environment already exists:

Request Arrives
       ↓
Execute Function Immediately
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Faster response.

What is Concurrency?

Concurrency means:

How Many Functions
Can Run Simultaneously
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Example:

100 Requests
       ↓
100 Concurrent Executions
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Reserved Concurrency

Reserve capacity for critical workloads.

Example:

Payment Function
Reserved = 100
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Always guaranteed.

Provisioned Concurrency

Used to eliminate cold starts.

AWS keeps execution environments warm.

Useful for:

  • APIs
  • User-facing workloads

What is Lambda Scaling?

Lambda automatically scales horizontally.

1 Request
       ↓
1 Environment

10000 Requests
       ↓
10000 Environments
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No manual scaling required.

What is a Lambda Layer?

One of the most important Lambda concepts.

Lambda Layers allow sharing code across multiple functions.

Without Layers:

Function A
 └─ boto3

Function B
 └─ boto3

Function C
 └─ boto3
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Duplication occurs.

With Layers 

Layer
 └─ boto3

Function A
Function B
Function C
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All functions share the same dependency.

Why Lambda Layers Matter

Benefits:

  • Smaller deployment packages
  • Reusability
  • Easier maintenance
  • Faster deployments

Common Layer Use Cases

Python Libraries 

numpy
pandas
requests
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Monitoring Agents 

Datadog
New Relic
OpenTelemetry
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Lambda Storage Options

Temporary Storage 

/tmp
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Default:

512 MB
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Can be increased.

Amazon S3

Persistent object storage.

Used for:

  • Files
  • Images
  • Backups

Amazon EFS

Network file system for Lambda.

Useful for:

  • Shared storage
  • Large datasets

Event Sources for Lambda

API Gateway 

User Request
      ↓
API Gateway
      ↓
Lambda
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Most common pattern.

Amazon S3 

File Uploaded
      ↓
Lambda Triggered
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Lambda and VPC

By default:

Lambda
     ↓
AWS Managed Network
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For private resources:

Lambda
     ↓
VPC
     ↓
RDS
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Lambda can connect to:

  • RDS
  • ElastiCache
  • Private APIs

Lambda with RDS

Common architecture:

API Gateway
      ↓
Lambda
      ↓
Aurora MySQL
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Challenges:

  • Connection management
  • Database scaling

Solution:

RDS Proxy
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Lambda Monitoring

CloudWatch Logs

Automatically captures:

  • stdout
  • stderr
  • application logs

CloudWatch Metrics

Monitor:

  • Invocations
  • Duration
  • Errors
  • Throttles
  • Concurrent executions

AWS X-Ray

Distributed tracing for Lambda applications.

Useful for:

  • Performance analysis
  • Bottleneck detection

Lambda Security

IAM Roles

Lambda should never use hardcoded credentials.

Use:

IAM Execution Role
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Secrets Manager

Store:

  • Database passwords
  • API keys
  • Tokens

KMS Encryption

Encrypt:

  • Environment variables
  • Data

Lambda Limits

Some important limits:

Feature Limit
Timeout 15 Minutes
Memory 128 MB – 10 GB
Ephemeral Storage Up to 10 GB
Deployment Package 50 MB ZIP
Container Image 10 GB

ec2

Lambda Container

Real-World Lambda Use Cases

Image Processing 

S3 Upload
      ↓
Lambda
      ↓
Resize Image
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Serverless APIs 

API Gateway
      ↓
Lambda
      ↓
DynamoDB
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Log Processing 

CloudWatch Logs
       ↓
Lambda
       ↓
Elasticsearch/OpenSearch
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Scheduled Jobs 

EventBridge
      ↓
Lambda
      ↓
Daily Report
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Production Best Practices

Keep Functions Small

One function = one responsibility.

Use Layers

Avoid dependency duplication.

Enable Monitoring

Use:

  • CloudWatch
  • X-Ray

Use Provisioned Concurrency

For latency-sensitive APIs.

Use RDS Proxy

For database-heavy workloads.

Secure Secrets

Use:

  • Secrets Manager
  • Parameter Store

Never hardcode credentials.

Final Thoughts

AWS Lambda transformed cloud computing by allowing developers to focus entirely on code.

Instead of managing:

Servers
Operating Systems
Scaling
Patching
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you simply write functions and AWS handles the infrastructure.

Lambda is ideal for:

  • APIs
  • Event-driven applications
  • Automation
  • Data processing
  • Serverless architectures

Understanding concepts like:

  • Layers
  • Cold Starts
  • Concurrency
  • Provisioned Concurrency
  • Event Sources
  • RDS Proxy

is essential for designing production-grade serverless applications.

For modern cloud engineers, AWS Lambda is no longer optional—it is one of the most important services in the AWS ecosystem.

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