Why serverless matters in Azure - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create an Azure Function App using serverless compute.

Azure

az functionapp create --resource-group myResourceGroup --consumption-plan-location westus --runtime python --name myFunctionApp --storage-account [1]

Drag options to blanks, or click blank then click option'

Amystorageaccount

Bmyfunctionplan

Cmyappserviceplan

Dmyresourcegroup

Attempts:

3 left

💡 Hint

Common Mistakes

Using the app service plan name instead of storage account

Confusing resource group with storage account

The storage account is required to create a Function App in Azure serverless. It stores code and triggers.

2fill in blank

medium

Complete the code to create a serverless Azure Function with the correct trigger type.

Azure

func new --name HttpTrigger --template [1]

Drag options to blanks, or click blank then click option'

Acontainertrigger

Bvmtrigger

CHttpTrigger

Dappservicetrigger

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing triggers related to VMs or containers which are not serverless triggers

The HTTP trigger is a common serverless trigger that runs functions on web requests.

3fill in blank

hard

Fix the error in the Azure CLI command to scale a serverless function app automatically.

Azure

az functionapp plan update --name myFunctionAppPlan --resource-group myResourceGroup --sku [1]

Drag options to blanks, or click blank then click option'

AY1

BS1

CP1v2

DB1

Attempts:

3 left

💡 Hint

Common Mistakes

Using standard or premium SKUs which are not serverless consumption plans

The Y1 SKU is the consumption (serverless) plan that enables automatic scaling.

4fill in blank

hard

Fill both blanks to configure an Azure Function App to use serverless and enable monitoring.

Azure

az functionapp create --resource-group myResourceGroup --plan [1] --name myFunctionApp --storage-account myStorageAccount --runtime dotnet --app-insights [2]

Drag options to blanks, or click blank then click option'

AConsumptionPlan

BStandardPlan

CmyAppInsights

DmyStorageAccount

Attempts:

3 left

💡 Hint

Common Mistakes

Using a standard plan instead of consumption plan

Confusing storage account with App Insights

The ConsumptionPlan enables serverless scaling, and myAppInsights enables monitoring with Application Insights.

5fill in blank

hard

Fill all three blanks to define a serverless Azure Function with an HTTP trigger and environment variable.

Azure

func init MyFunctionProj --worker-runtime [1]
func new --name HttpTrigger --template [2] --authlevel anonymous
az functionapp config appsettings set --name myFunctionApp --resource-group myResourceGroup --settings [3]=Production

Drag options to blanks, or click blank then click option'

Apython

BHTTP trigger

CENVIRONMENT

Dnode

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong runtime language

Confusing trigger template names

Incorrect environment variable key

The worker runtime is python, the trigger template is HTTP trigger, and the environment variable key is ENVIRONMENT.

Practice

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

easy

A. You don't have to manage servers yourself.

B. You get unlimited free storage.

C. You must buy servers upfront.

D. You need to install software on your computer.

Solution

1. Step 1: Understand serverless computing basics

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

2. Step 2: Identify the main benefit

   This removes the need for you to handle server setup, maintenance, or scaling.

3. Final Answer:

   You don't have to manage servers yourself. -> Option A

4. Quick Check:

   Serverless = No server management [OK]

Hint: Serverless means no server management needed [OK]

Common Mistakes:

• Thinking serverless means free unlimited resources
• Believing you must buy or manage servers
• Confusing serverless with local software installation

2. Which of the following is the correct way to describe serverless billing?

easy

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

B. You pay only for the compute time you actually use.

C. You pay upfront for reserved server capacity.

D. You pay based on the number of servers you own.

Solution

1. Step 1: Understand serverless billing model

   Serverless charges are based on actual compute time used, not fixed fees or reserved capacity.

2. Step 2: Match billing description

   Only "You pay only for the compute time you actually use." correctly states pay-per-use billing.

3. Final Answer:

   You pay only for the compute time you actually use. -> Option B

4. Quick Check:

   Serverless billing = pay per compute time [OK]

Hint: Serverless billing is pay-as-you-go for compute time [OK]

Common Mistakes:

• Assuming fixed monthly fees apply
• Confusing reserved capacity with serverless
• Thinking billing depends on number of servers

3. Consider this Azure Function code snippet:

module.exports = async function (context, req) {
  context.log('Function triggered');
  return { status: 200, body: 'Hello, Serverless!' };
};

What will happen when this function is triggered?

medium

A. It logs nothing and returns an empty response.

B. It throws a syntax error and does not run.

C. It returns status 500 with an error message.

D. It logs 'Function triggered' and returns 'Hello, Serverless!' with status 200.

Solution

1. Step 1: Analyze the function behavior

   The function logs a message and returns a response object with status 200 and a body string.

2. Step 2: Predict the output when triggered

   On trigger, it logs 'Function triggered' and returns the expected response.

3. Final Answer:

   It logs 'Function triggered' and returns 'Hello, Serverless!' with status 200. -> Option D

4. Quick Check:

   Function logs and returns response correctly [OK]

Hint: Look for log and return statements to predict output [OK]

Common Mistakes:

• Assuming syntax errors without checking code
• Expecting error responses without cause
• Ignoring the return statement's content

4. You wrote an Azure serverless function but it never triggers. Which of these is the most likely cause?

medium

A. You set the function to run on a schedule but did not configure the timer trigger.

B. You forgot to deploy the function to Azure.

C. You used too much memory in the function code.

D. You wrote the function in the wrong programming language.

Solution

1. Step 1: Understand function triggers

   Serverless functions run when triggered by events like HTTP requests or timers.

2. Step 2: Identify trigger misconfiguration

   If a timer trigger is set but not configured, the function won't run automatically.

3. Final Answer:

   You set the function to run on a schedule but did not configure the timer trigger. -> Option A

4. Quick Check:

   Missing trigger config = function won't run [OK]

Hint: Check trigger setup if function never runs [OK]

Common Mistakes:

• Assuming deployment is always the issue
• Blaming programming language without cause
• Thinking memory usage stops triggers

5. You want to build a web app that scales automatically and costs less when idle. Which Azure service should you choose?

hard

A. Azure Virtual Machines with manual scaling.

B. Azure App Service with fixed pricing plan.

C. Azure Functions with serverless consumption plan.

D. Azure Kubernetes Service with dedicated nodes.

Solution

1. Step 1: Identify scaling and cost needs

   The app must scale automatically and reduce costs when idle.

2. Step 2: Match service features

   Azure Functions with serverless consumption plan scales automatically and charges only for usage, saving cost when idle.

3. Step 3: Compare other options

   Virtual Machines and Kubernetes require manual or fixed resources, costing more when idle. App Service fixed plan is not serverless.

4. Final Answer:

   Azure Functions with serverless consumption plan. -> Option C

5. Quick Check:

   Serverless = auto scale + pay per use [OK]

Hint: Choose serverless for auto scale and cost efficiency [OK]

Common Mistakes:

• Picking fixed pricing plans ignoring idle costs
• Choosing manual scaling services
• Confusing Kubernetes with serverless