Why serverless architecture matters in AWS - See It in Action

Why Serverless Architecture Matters

📖 Scenario: You are building a simple cloud setup to understand why serverless architecture is useful. Imagine you want to run a small app that responds to user requests without managing servers yourself.

🎯 Goal: Create a basic AWS Lambda function setup with a trigger and configuration to see how serverless works and why it matters.

📋 What You'll Learn

Create a dictionary called lambda_function with keys FunctionName, Runtime, and Handler with exact values

Add a configuration variable called memory_size set to 128

Create a dictionary called trigger with key EventSource set to API Gateway

Add the Trigger key to lambda_function with the trigger dictionary as its value

💡 Why This Matters

🌍 Real World

Serverless architecture lets developers run code without managing servers. This project shows how to define a simple Lambda function and its trigger, which is common in cloud apps.

💼 Career

Understanding serverless basics is essential for cloud roles like cloud engineer, developer, and architect. It helps in building scalable, cost-effective applications.

1

Create the Lambda function dictionary

Create a dictionary called lambda_function with these exact entries: 'FunctionName': 'MyServerlessApp', 'Runtime': 'python3.12', and 'Handler': 'app.handler'.

AWS

# Create the lambda_function dictionary with FunctionName, Runtime, and Handler
# Your code here

Hint

Use curly braces to create a dictionary with the exact keys and values.

2

Add memory size configuration

Add a variable called memory_size and set it to 128 to represent the Lambda function's memory allocation in MB.

AWS

lambda_function = {
    'FunctionName': 'MyServerlessApp',
    'Runtime': 'python3.12',
    'Handler': 'app.handler'
}
# Add memory_size variable set to 128
# Your code here

Hint

Just create a variable named memory_size and assign it the number 128.

3

Create the trigger dictionary

Create a dictionary called trigger with the key 'EventSource' set to the string 'API Gateway'.

AWS

lambda_function = {
    'FunctionName': 'MyServerlessApp',
    'Runtime': 'python3.12',
    'Handler': 'app.handler'
}
memory_size = 128
# Create trigger dictionary with EventSource set to 'API Gateway'
# Your code here

Hint

Use curly braces to create a dictionary with the key and value exactly as shown.

4

Add the trigger to the Lambda function

Add the key 'Trigger' to the lambda_function dictionary and set its value to the trigger dictionary.

AWS

lambda_function = {
    'FunctionName': 'MyServerlessApp',
    'Runtime': 'python3.12',
    'Handler': 'app.handler'
}
memory_size = 128
trigger = {
    'EventSource': 'API Gateway'
}
# Add 'Trigger' key to lambda_function with trigger dictionary as value
# Your code here

Hint

Use the dictionary key assignment syntax to add the 'Trigger' key with the trigger dictionary as its value.

Practice

1. What is the main benefit of using serverless architecture in cloud computing?

easy

A. You don't need to manage or provision servers.

B. You get unlimited free storage.

C. You must manually scale your application.

D. You pay a fixed monthly fee regardless of usage.

Solution

1. Step 1: Understand serverless basics

   Serverless means the cloud provider manages servers, so you don't have to.

2. Step 2: Identify the key benefit

   This removes the need for manual server management and provisioning.

3. Final Answer:

   You don't need to manage or provision servers. -> Option A

4. Quick Check:

   Serverless = No server management [OK]

Hint: Serverless means no server setup or maintenance needed [OK]

Common Mistakes:

• Thinking serverless means free unlimited resources
• Assuming you must scale servers manually
• Believing serverless has fixed monthly costs

2. Which AWS service is an example of serverless compute?

easy

A. Amazon EC2

B. AWS Lambda

C. Amazon RDS

D. Amazon S3

Solution

1. Step 1: Identify serverless compute services

   AWS Lambda runs code without managing servers, fitting serverless compute.

2. Step 2: Compare options

   EC2 requires server management, RDS is managed database, S3 is storage.

3. Final Answer:

   AWS Lambda -> Option B

4. Quick Check:

   Serverless compute = AWS Lambda [OK]

Hint: Lambda runs code without servers, EC2 does not [OK]

Common Mistakes:

• Choosing EC2 which requires server management
• Confusing storage (S3) with compute
• Selecting RDS which is managed database, not compute

3. Consider this AWS Lambda function code snippet:

exports.handler = async (event) => {
  return { statusCode: 200, body: 'Hello Serverless!' };
};

What will be the output when this Lambda function is invoked?

medium

A. Runtime error because of missing callback

B. SyntaxError due to arrow function

C. { statusCode: 200, body: 'Hello Serverless!' }

D. Empty response with statusCode 500

Solution

1. Step 1: Analyze the Lambda handler syntax

   The handler is an async arrow function returning a valid response object.

2. Step 2: Understand Lambda response behavior

   Returning an object with statusCode and body is correct for API Gateway integration.

3. Final Answer:

   { statusCode: 200, body: 'Hello Serverless!' } -> Option C

4. Quick Check:

   Async handler returns response object [OK]

Hint: Async arrow functions can return response objects directly [OK]

Common Mistakes:

• Thinking arrow functions cause syntax errors
• Assuming callback is required in async handlers
• Expecting empty or error responses without cause

4. You wrote this AWS Lambda function but it always times out:

exports.handler = (event, context) => {
  while(true) {}
};

What is the main reason for the timeout?

medium

A. Lambda functions cannot use arrow functions.

B. Missing async keyword causes timeout.

C. The event parameter is not used.

D. The infinite loop blocks the function from returning.

Solution

1. Step 1: Identify the code behavior

   The while(true) creates an infinite loop that never ends or returns.

2. Step 2: Understand Lambda timeout cause

   Without returning or ending, Lambda runs until timeout is reached.

3. Final Answer:

   The infinite loop blocks the function from returning. -> Option D

4. Quick Check:

   Infinite loop causes timeout [OK]

Hint: Infinite loops cause Lambda to never finish [OK]

Common Mistakes:

• Blaming missing async keyword for timeout
• Thinking arrow functions are unsupported
• Assuming unused parameters cause timeout

5. You want to build a web app that scales automatically and only charges you when users interact. Which serverless feature best supports this?

hard

A. Automatic scaling with pay-per-use billing

B. Reserved instances with fixed monthly cost

C. Manual server provisioning for control

D. Pre-allocated capacity to avoid cold starts

Solution

1. Step 1: Identify serverless scaling and billing

   Serverless automatically scales with demand and charges only for actual usage.

2. Step 2: Compare options for cost and scaling

   Reserved instances and manual provisioning do not scale automatically or charge per use.

3. Final Answer:

   Automatic scaling with pay-per-use billing -> Option A

4. Quick Check:

   Serverless = scale automatically + pay per use [OK]

Hint: Serverless scales automatically and bills only when used [OK]

Common Mistakes:

• Choosing reserved instances which have fixed costs
• Thinking manual provisioning is needed for scaling
• Believing pre-allocated capacity is required in serverless