Auto scaling App Service in Azure - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is Auto Scaling in Azure App Service?

Auto Scaling automatically adjusts the number of running app instances based on demand to keep your app responsive and cost-effective.

beginner

Name two common metrics used to trigger auto scaling in Azure App Service.

CPU usage and HTTP queue length are common metrics used to decide when to add or remove app instances.

beginner

What is a scale-out action in Azure App Service auto scaling?

Scale-out means adding more instances of your app to handle increased traffic or load.

beginner

How does Azure App Service auto scaling help control costs?

It reduces the number of running instances when demand is low, so you only pay for what you need.

beginner

What is a scale-in action in Azure App Service auto scaling?

Scale-in means removing instances of your app when demand decreases to save resources.

Which metric is NOT typically used to trigger auto scaling in Azure App Service?

A Memory usage

B HTTP queue length

C CPU usage

D Disk space used

Disk space used is generally not used for auto scaling decisions in Azure App Service; CPU, memory, and HTTP queue length are common triggers.

What happens during a scale-out event in Azure App Service?

A App instances are added

B App service is restarted

C App service is stopped

D App instances are removed

Scale-out means adding more instances to handle increased load.

Why is auto scaling important for an app running on Azure App Service?

A To automatically adjust resources based on demand

B To increase app security

C To manually control app updates

D To backup app data

Auto scaling automatically adjusts the number of app instances to match demand, improving performance and cost efficiency.

Which of the following is a benefit of scale-in in Azure App Service?

A Increases app traffic

B Improves app security

C Saves costs by reducing instances

D Backs up app data

Scale-in reduces the number of running instances when demand is low, saving costs.

How can you configure auto scaling rules in Azure App Service?

A Only by editing app code

B Using Azure Portal or Azure CLI

C By restarting the app service

D By changing DNS settings

Auto scaling rules can be set up easily through the Azure Portal or Azure CLI.

Explain how auto scaling works in Azure App Service and why it is useful.

Think about how your app can handle more users or less traffic without manual changes.

Describe the difference between scale-out and scale-in actions in Azure App Service auto scaling.

Consider what happens when your app gets busier or quieter.

Practice

1. What is the main purpose of auto scaling in Azure App Service?

easy

A. Automatically adjust app resources based on demand

B. Manually increase server size when needed

C. Backup app data to cloud storage

D. Monitor user login activities

Solution

1. Step 1: Understand auto scaling concept

   Auto scaling means the system changes resources automatically without manual intervention.

2. Step 2: Identify the purpose in Azure App Service

   Azure App Service auto scaling adjusts the number of instances based on app demand to maintain performance and control costs.

3. Final Answer:

   Automatically adjust app resources based on demand -> Option A

4. Quick Check:

   Auto scaling = automatic resource adjustment [OK]

Hint: Auto scaling means automatic resource changes [OK]

Common Mistakes:

• Confusing auto scaling with manual scaling
• Thinking auto scaling backs up data
• Assuming auto scaling monitors user activity

2. Which of the following is the correct way to set a CPU-based auto scale rule in Azure App Service?

easy

A. Set a rule to scale in when CPU usage < 90%

B. Set a rule to scale out when memory usage < 30%

C. Set a rule to scale out when CPU usage > 70%

D. Set a rule to scale out when disk space > 80%

Solution

1. Step 1: Identify correct metric for scaling out

   CPU usage is a common metric to trigger scaling out when it exceeds a threshold.

2. Step 2: Check the threshold and direction

   Scaling out happens when CPU usage is high (e.g., > 70%), not low or unrelated metrics like disk space.

3. Final Answer:

   Set a rule to scale out when CPU usage > 70% -> Option C

4. Quick Check:

   Scale out triggers on high CPU [OK]

Hint: Scale out when CPU usage is high, not low [OK]

Common Mistakes:

• Using memory or disk space incorrectly for CPU scaling
• Scaling in when CPU is still high
• Setting wrong thresholds for scaling

3. Given this auto scale setting: minimum instances = 2, maximum instances = 5, scale out rule triggers at CPU > 60%, scale in rule triggers at CPU < 30%. If CPU usage rises from 50% to 65%, what happens?

medium

A. Instances reset to minimum count immediately

B. The number of instances increases by one, up to 5

C. No change in instances because CPU is below 70%

D. The number of instances decreases by one, down to 2

Solution

1. Step 1: Analyze CPU usage against scale out rule

   CPU rose from 50% to 65%, which is above the 60% threshold for scaling out.

2. Step 2: Apply scaling limits

   Instances will increase by one but will not exceed the maximum of 5 instances.

3. Final Answer:

   The number of instances increases by one, up to 5 -> Option B

4. Quick Check:

   CPU > 60% triggers scale out [OK]

Hint: Scale out triggers when CPU crosses threshold upwards [OK]

Common Mistakes:

• Thinking CPU must be above 70% to scale out
• Confusing scale in and scale out rules
• Assuming immediate reset to minimum instances

4. You configured auto scaling with minimum 1 instance and maximum 3 instances. The scale out rule triggers at CPU > 50%. However, your app never scales out even when CPU is 80%. What is the most likely issue?

medium

A. CPU metric is not supported for scaling

B. The minimum instance count is too high

C. Maximum instance count is set too low

D. The scale out rule is disabled or not linked to the App Service

Solution

1. Step 1: Check if scaling rules are active

   If the scale out rule is disabled or not properly linked, scaling won't trigger despite high CPU.

2. Step 2: Verify instance limits and metric support

   Minimum and maximum instance counts are valid, and CPU is a supported metric, so these are unlikely causes.

3. Final Answer:

   The scale out rule is disabled or not linked to the App Service -> Option D

4. Quick Check:

   Active rules needed for scaling [OK]

Hint: Check if scaling rules are enabled and linked [OK]

Common Mistakes:

• Assuming instance counts block scaling
• Believing CPU metric is unsupported
• Ignoring rule activation status

5. You want to optimize costs by setting auto scaling for your Azure App Service. You set minimum instances to 1 and maximum to 10. You add a scale out rule for CPU > 70% and a scale in rule for CPU < 40%. However, during peak hours, your app scales out to 10 instances quickly but never scales in after peak hours. What is the best way to fix this?

hard

A. Add a cooldown period to delay scaling in after peak hours

B. Increase the minimum instance count to 5

C. Remove the scale out rule to prevent scaling beyond 1 instance

D. Set scale in rule to CPU < 80% to scale in faster

Solution

1. Step 1: Understand why scaling in doesn't happen

   Without a cooldown period, rapid fluctuations can prevent scale in or cause instability.

2. Step 2: Apply cooldown period to stabilize scaling

   Adding a cooldown period delays scale in, allowing CPU to stay below threshold steadily before reducing instances.

3. Final Answer:

   Add a cooldown period to delay scaling in after peak hours -> Option A

4. Quick Check:

   Cooldown stabilizes scale in/out actions [OK]

Hint: Use cooldown to prevent rapid scale in/out flips [OK]

Common Mistakes:

• Raising minimum instances unnecessarily
• Removing scale out rule stops scaling out
• Setting scale in threshold too high causes no scale in