Why serverless matters in AWS - Why It Works

Introduction

Serverless computing lets you run code without managing servers. It solves the problem of spending time and money on server setup and maintenance.

When you want to run a small app feature without setting up a whole server.

When your app usage changes a lot and you want to pay only for what you use.

When you want to focus on writing code, not managing infrastructure.

When you need to quickly scale your app up or down based on demand.

When you want to build event-driven apps that react to user actions or data changes.

Commands

This command creates a new AWS Lambda function named 'my-serverless-function' using Python 3.9. It uses a role that allows Lambda to run and a zipped file with your code.

Terminal

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

Expected Output

{

    "FunctionName": "my-serverless-function",

    "FunctionArn": "arn:aws:lambda:us-east-1:123456789012:function:my-serverless-function",

    "Runtime": "python3.9",

    "Role": "arn:aws:iam::123456789012:role/lambda-execution-role",

    "Handler": "lambda_function.lambda_handler",

    "CodeSize": 12345,

    "Description": "",

    "Timeout": 3,

    "MemorySize": 128,

    "LastModified": "2024-06-01T12:00:00.000+0000",

    "CodeSha256": "abc123def456ghi789",

    "Version": "$LATEST",

    "TracingConfig": {

        "Mode": "PassThrough"

    },

    "RevisionId": "1a2b3c4d-5678-90ab-cdef-1234567890ab"

}

→

--function-name - Names your Lambda function

→

--runtime - Specifies the programming language environment

→

--role - Grants permissions for Lambda to run

This command runs your Lambda function and saves the output to a file named output.txt.

Terminal

aws lambda invoke --function-name my-serverless-function output.txt

Expected Output

{

    "StatusCode": 200,

    "ExecutedVersion": "$LATEST"

}

→

--function-name - Specifies which Lambda function to run

This command lists all your Lambda functions so you can see what serverless functions you have.

Terminal

aws lambda list-functions

Expected Output

{

    "Functions": [

        {

            "FunctionName": "my-serverless-function",

            "Runtime": "python3.9",

            "Role": "arn:aws:iam::123456789012:role/lambda-execution-role",

            "Handler": "lambda_function.lambda_handler",

            "CodeSize": 12345,

            "Description": "",

            "Timeout": 3,

            "MemorySize": 128,

            "LastModified": "2024-06-01T12:00:00.000+0000",

            "CodeSha256": "abc123def456ghi789",

            "Version": "$LATEST"

        }

    ]

}

Key Concept

If you remember nothing else from this pattern, remember: serverless lets you run code without managing servers, saving time and cost.

Common Mistakes

Not assigning the correct IAM role with permissions to the Lambda function

The function will fail to run because it lacks permission to access resources or execute.

Create and assign an IAM role with the minimum required permissions for your Lambda function.

Uploading code without packaging dependencies properly

The function will error out if it cannot find required libraries at runtime.

Package your code and dependencies into a zip file before uploading.

Not specifying the correct handler name in the create-function command

Lambda won't know which function to run and will fail with an error.

Ensure the handler matches your code's entry point, e.g., 'lambda_function.lambda_handler'.

Summary

Create a Lambda function with the right runtime, role, and handler using the AWS CLI.

Invoke the Lambda function to run your code and check the output.

List your Lambda functions to manage and verify your serverless apps.

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