Why serverless matters in AWS - See It in Action

Why Serverless Matters

📖 Scenario: You are working for a small startup that wants to build a simple web application. The team wants to focus on writing code and not worry about managing servers or infrastructure. You will help them understand how to set up a serverless function on AWS to handle user requests.

🎯 Goal: Build a simple AWS Lambda function configuration using AWS CloudFormation that shows how serverless computing works and why it matters for developers who want to avoid managing servers.

📋 What You'll Learn

Create a CloudFormation template with a Lambda function resource

Add a configuration variable for the Lambda function runtime

Use the runtime variable in the Lambda function resource

Complete the template with a handler and role properties

💡 Why This Matters

🌍 Real World

Serverless computing lets developers focus on code without managing servers. This project shows how to define a serverless function on AWS using CloudFormation.

💼 Career

Understanding serverless infrastructure setup is key for cloud engineers and developers working with AWS Lambda and infrastructure as code.

1

Create the initial CloudFormation template structure

Create a CloudFormation template starting with AWSTemplateFormatVersion set to '2010-09-09' and an empty Resources section.

AWS

# Your code here

Hint

Start with the basic CloudFormation template keys: AWSTemplateFormatVersion and Resources.

2

Add a configuration variable for Lambda runtime

Add a Parameters section with a parameter named LambdaRuntime of type String and default value python3.12.

AWS

AWSTemplateFormatVersion: '2010-09-09'
Resources: {}
# Add Parameters section with LambdaRuntime parameter here

Hint

Use Parameters to define a variable for the Lambda runtime environment.

3

Add the Lambda function resource using the runtime parameter

Add a resource named MyLambdaFunction of type AWS::Lambda::Function inside Resources. Use !Ref LambdaRuntime for the Runtime property. Also add Handler set to index.handler and Role set to arn:aws:iam::123456789012:role/lambda-execution-role.

AWS

AWSTemplateFormatVersion: '2010-09-09'
Parameters:
  LambdaRuntime:
    Type: String
    Default: python3.12
Resources: {}
# Add MyLambdaFunction resource here using !Ref LambdaRuntime

Hint

Use the !Ref intrinsic function to refer to the LambdaRuntime parameter in the Lambda function's Runtime property.

4

Complete the CloudFormation template

Ensure the CloudFormation template is valid YAML with all sections properly indented and closed. The template should define AWSTemplateFormatVersion, Parameters with LambdaRuntime, and Resources with MyLambdaFunction using the runtime parameter, handler, and role.

AWS

AWSTemplateFormatVersion: '2010-09-09'
Parameters:
  LambdaRuntime:
    Type: String
    Default: python3.12
Resources:
  MyLambdaFunction:
    Type: AWS::Lambda::Function
    Properties:
      Runtime: !Ref LambdaRuntime
      Handler: index.handler
      Role: arn:aws:iam::123456789012:role/lambda-execution-role
# Verify the template is complete and valid

Hint

Check indentation and that all required properties are present for the Lambda function resource.

Practice

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

easy

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

B. You get unlimited free storage space.

C. You must manually scale your application.

D. You don't have to manage or maintain servers.

Solution

1. Step 1: Understand serverless computing basics

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

2. Step 2: Identify the main benefit

   This removes the need for server maintenance and management by the user.

3. Final Answer:

   You don't have to manage or maintain servers. -> Option D

4. Quick Check:

   Serverless = No server management [OK]

Hint: Serverless means no server management needed [OK]

Common Mistakes:

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

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

easy

A. AWS Lambda

B. Amazon EC2

C. Amazon S3 Glacier

D. Amazon RDS

Solution

1. Step 1: Identify serverless AWS services

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

2. Step 2: Compare options

   EC2 and RDS require server management; S3 Glacier is storage, not compute.

3. Final Answer:

   AWS Lambda -> Option A

4. Quick Check:

   Lambda = serverless compute [OK]

Hint: Lambda is AWS's serverless compute service [OK]

Common Mistakes:

• Choosing EC2 which needs server setup
• Confusing storage services with serverless compute
• Picking RDS which manages database servers

3. Consider this AWS Lambda usage scenario: You run a function that processes 1000 requests in a minute. How does serverless pricing affect your cost?

medium

A. You pay a flat fee for unlimited requests per month.

B. You pay for the maximum number of concurrent requests allowed.

C. You pay only for the compute time used during those 1000 requests.

D. You pay for the total number of servers running your function.

Solution

1. Step 1: Understand serverless pricing model

   Serverless charges based on actual compute time and number of requests.

2. Step 2: Apply to scenario

   For 1000 requests, you pay only for the compute time those requests consume, not fixed fees or server counts.

3. Final Answer:

   You pay only for the compute time used during those 1000 requests. -> Option C

4. Quick Check:

   Serverless pricing = pay per use [OK]

Hint: Serverless charges only for actual compute time used [OK]

Common Mistakes:

• Assuming flat monthly fees
• Thinking payment depends on server count
• Confusing concurrency limits with billing

4. You wrote a serverless function but it fails to handle sudden traffic spikes, causing errors. What is the likely cause?

medium

A. The function has a fixed number of instances and does not auto-scale.

B. Serverless functions automatically scale, so the error is unrelated to scaling.

C. The function's timeout setting is too high.

D. The function is not connected to a database.

Solution

1. Step 1: Understand serverless scaling

   Serverless functions usually auto-scale, but concurrency limits or misconfigurations can restrict it to a fixed number of instances.

2. Step 2: Identify cause of errors

   If the function does not scale beyond a fixed number, it cannot handle traffic spikes, causing errors.

3. Final Answer:

   The function has a fixed number of instances and does not auto-scale. -> Option A

4. Quick Check:

   Scaling limits cause errors under load [OK]

Hint: Check if auto-scaling limits block traffic handling [OK]

Common Mistakes:

• Assuming serverless always scales without limits
• Blaming timeout when scaling is the issue
• Ignoring connection issues unrelated to scaling

5. You want to build a photo-sharing app that automatically adjusts capacity as users upload photos. Which serverless feature best supports this?

hard

A. Fixed monthly billing for predictable costs.

B. Automatic scaling of compute resources based on demand.

C. Manual server provisioning to control capacity.

D. Dedicated servers for consistent performance.

Solution

1. Step 1: Identify app needs

   The app must handle varying user uploads, so capacity must adjust automatically.

2. Step 2: Match serverless feature

   Automatic scaling lets compute resources grow or shrink with demand, ideal for this app.

3. Final Answer:

   Automatic scaling of compute resources based on demand. -> Option B

4. Quick Check:

   Serverless auto-scales to match user demand [OK]

Hint: Auto-scaling matches resources to user demand [OK]

Common Mistakes:

• Choosing fixed billing which doesn't scale
• Thinking manual provisioning is needed
• Assuming dedicated servers are serverless