Amazon Web Services
Compute
- AWS EC2
- EC2 Instance Types
- EC2 Pricing Models
- EC2 Auto Scaling
- Elastic Load Balancing-ELB
- AWS Lambda – Serverless Computing
- Amazon Lightsail
- AWS Elastic Beanstalk
- AWS Fargate
- Amazon ECS (Elastic Container Service)
- Amazon EKS (Elastic Kubernetes Service)
DynamoDB
- DynamoDB Global Table vs Regular DynamoDB Table
- DynamoDB Streams
- Athena query data to DynamoDB
- Athena Query Results with DynamoDB
- PySpark DataFrame to DynamoDB
Redshift
Lambda
Glue
Lambda
Storage
- S3 vs. EBS vs. EFS
- Amazon S3 (Simple Storage Service)
- Amazon S3 Storage Classes
- Amazon EBS (Elastic Block Store)
- Amazon EFS (Elastic File System)
- AWS Storage Gateway
- AWS Snowball
- Amazon FSx
- AWS Backup
Security
🚀 AWS Lambda – Serverless Computing for Running Code Without Managing Servers
Imagine building an application where you don’t worry about servers, scaling, or infrastructure—you just write your code, upload it, and AWS takes care of everything.
That’s exactly what AWS Lambda offers:
- A serverless computing service that lets you run code without provisioning or managing servers.
- You only pay for the compute time used.
- It automatically scales based on demand.
Think of AWS Lambda as your personal cloud assistant—always ready to run your code when needed, and disappearing when idle.
🔑 What is AWS Lambda?
AWS Lambda is a Function-as-a-Service (FaaS) offering. It allows you to:
- Run code in response to events (API call, file upload, database change, etc.).
- Write functions in multiple languages (Python, Node.js, Java, Go, C#, etc.).
- Forget about infrastructure management—Lambda handles scaling, patching, and availability.
- Pay only for the execution duration (ms) and number of requests.
👉 Example Use Cases:
- Processing uploaded images in S3.
- Running background jobs.
- Handling API requests.
- Streaming data in real-time.
⚙️ Key Concepts of AWS Lambda
- Function – Your actual code.
- Trigger/Event Source – What invokes the function (S3, API Gateway, DynamoDB, CloudWatch, etc.).
- Execution Role – IAM role that defines Lambda’s permissions.
- Timeout & Memory – Execution limits.
- Concurrency – How many function instances can run simultaneously.
📌 Example 1: AWS Lambda with S3 (File Processing)
When a file is uploaded to an S3 bucket, Lambda can process it automatically.
Code Example (Python)
import boto3
def lambda_handler(event, context): s3 = boto3.client('s3') bucket = event['Records'][0]['s3']['bucket']['name'] key = event['Records'][0]['s3']['object']['key'] print(f"File uploaded: {key} in bucket: {bucket}") return {"status": "success"}
👉 This function logs file uploads in real time.
CLI Example: Deploy Lambda for S3
aws lambda create-function \ --function-name s3FileLogger \ --runtime python3.9 \ --role arn:aws:iam::123456789012:role/execution_role \ --handler lambda_function.lambda_handler \ --zip-file fileb://function.zip
Node.js Example for S3 File Metadata
exports.handler = async (event) => { const bucket = event.Records[0].s3.bucket.name; const file = event.Records[0].s3.object.key; console.log(`New file: ${file} in bucket: ${bucket}`); return { status: "processed" };};
📌 Example 2: AWS Lambda with API Gateway (Serverless REST API)
Lambda + API Gateway = Fully Serverless API.
Python Example – Hello World API
def lambda_handler(event, context): return { "statusCode": 200, "body": "Hello, AWS Lambda!" }
CLI Example – Create REST API with Lambda
aws apigateway create-rest-api --name "HelloAPI"
Node.js Example – JSON Response
exports.handler = async (event) => { return { statusCode: 200, body: JSON.stringify({ message: "Hello from Serverless API!" }) };};
📌 Example 3: AWS Lambda with DynamoDB (Event-Driven DB Processing)
Lambda can process real-time changes in a DynamoDB table.
Python Example – Log New Items
def lambda_handler(event, context): for record in event['Records']: print("New record:", record['dynamodb']['NewImage'])
CLI Example – Create DynamoDB Stream
aws dynamodb create-table \ --table-name Users \ --attribute-definitions AttributeName=UserId,AttributeType=S \ --key-schema AttributeName=UserId,KeyType=HASH \ --billing-mode PAY_PER_REQUEST \ --stream-specification StreamEnabled=true,StreamViewType=NEW_IMAGE
Node.js Example – Insert Notification
exports.handler = async (event) => { for (const record of event.Records) { console.log("Inserted:", record.dynamodb.NewImage); }};
📌 Example 4: AWS Lambda with CloudWatch (Scheduled Tasks)
Lambda can act as a cron job.
Python Example – Scheduled Task
def lambda_handler(event, context): print("Running scheduled job via CloudWatch event")
CLI Example – Create CloudWatch Rule
aws events put-rule --name "DailyJob" --schedule-expression "rate(1 day)"
Node.js Example – Send Reminder
exports.handler = async (event) => { console.log("Reminder: Daily Task Triggered!");};
📌 Example 5: AWS Lambda with Kinesis (Stream Processing)
Lambda can consume real-time streaming data.
Python Example – Process Kinesis Records
def lambda_handler(event, context): for record in event['Records']: payload = record['kinesis']['data'] print("Data received:", payload)
CLI Example – Create Kinesis Stream
aws kinesis create-stream --stream-name myStream --shard-count 1
Node.js Example – Log Streamed Data
exports.handler = async (event) => { event.Records.forEach(record => { console.log("Stream data:", record.kinesis.data); });};
🧠 How to Remember AWS Lambda Concepts (Interview & Exams)
👉 Trick: S-A-D-C-K
- S = S3 triggers
- A = API Gateway integration
- D = DynamoDB streams
- C = CloudWatch scheduled jobs
- K = Kinesis real-time streaming
💡 Memory Hook: Think “Serverless Apps Don’t Care for Kubernetes” → S-A-D-C-K.
🎯 Why AWS Lambda is Important
- Cost-Efficient – Pay only for execution.
- Auto-Scaling – Zero to millions of requests.
- No Infrastructure Management – Focus only on code.
- Highly Integrated – Works with 200+ AWS services.
- Popular in Exams – Lambda-based scenarios appear in AWS Solutions Architect, Developer, and SysOps exams.
🌍 Real-World Use Cases
- E-commerce – Auto-resize product images when uploaded.
- IoT – Process device data in real time.
- Banking – Fraud detection with DynamoDB + Lambda.
- Startups – Build serverless APIs quickly without DevOps overhead.
📌 Conclusion
AWS Lambda is the heart of serverless computing. It enables developers to:
- Write small, event-driven functions.
- Forget about server provisioning.
- Scale automatically with demand.
👉 Remember the core triggers (S3, API Gateway, DynamoDB, CloudWatch, Kinesis). 👉 Practice with small projects like serverless APIs or scheduled jobs.
By mastering AWS Lambda, you gain skills that are in huge demand in cloud-native development and AWS certifications.