Why auto scaling matters in AWS - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to specify the minimum number of instances in an Auto Scaling group.

AWS

MinSize = [1]

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

A0

Bmax

C5

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Setting MinSize to a negative number causes errors.

Using 'max' as a value is invalid.

The minimum size must be zero or more. Setting it to 0 allows no instances when demand is low.

2fill in blank

medium

Complete the code to set the desired capacity of an Auto Scaling group.

AWS

DesiredCapacity = [1]

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

A0

BMinSize

C3

DMaxSize

Attempts:

3 left

💡 Hint

Common Mistakes

Setting DesiredCapacity to MinSize or MaxSize variables directly without values.

Using zero when you want some instances running.

DesiredCapacity is the number of instances the group tries to maintain, often set to a positive integer like 3.

3fill in blank

hard

Fix the error in the Auto Scaling policy action type.

AWS

ScalingPolicy = {
  "AdjustmentType": "[1]",
  "ScalingAdjustment": 1
}

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

AChangeInCapacity

BExactCapacity

CPercentChangeInCapacity

DIncreaseCapacity

Attempts:

3 left

💡 Hint

Common Mistakes

Using invalid strings like 'IncreaseCapacity' causes errors.

Confusing 'ExactCapacity' with 'ChangeInCapacity'.

"ChangeInCapacity" is a valid AdjustmentType that increases or decreases the number of instances by a fixed amount.

4fill in blank

hard

Fill both blanks to create a scaling policy that increases capacity by 2 when CPU usage is high.

AWS

ScalingPolicy = {
  "AdjustmentType": "[1]",
  "ScalingAdjustment": [2]
}

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

AChangeInCapacity

BExactCapacity

C2

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using ExactCapacity with a number that is not the exact desired count.

Setting ScalingAdjustment to a string instead of a number.

Use "ChangeInCapacity" to adjust by a number, and 2 to increase capacity by two instances.

5fill in blank

hard

Fill all three blanks to define an Auto Scaling group with min size 1, max size 4, and desired capacity 2.

AWS

AutoScalingGroup = {
  "MinSize": [1],
  "MaxSize": [2],
  "DesiredCapacity": [3]
}

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

A1

B2

C4

D3

Attempts:

3 left

💡 Hint

Common Mistakes

Setting DesiredCapacity higher than MaxSize causes errors.

Using MinSize greater than MaxSize is invalid.

MinSize is 1, MaxSize is 4, and DesiredCapacity is 2 to keep the group balanced.

Practice

1. Why is auto scaling important in cloud infrastructure?

easy

A. It automatically adjusts the number of servers to match demand.

B. It manually requires admins to add servers during traffic spikes.

C. It reduces the need for backups and data recovery.

D. It guarantees zero downtime without any configuration.

Solution

1. Step 1: Understand auto scaling purpose

   Auto scaling automatically changes server count based on demand to keep apps running smoothly.

2. Step 2: Compare options

   Only It automatically adjusts the number of servers to match demand. describes automatic adjustment. Others describe manual work, unrelated features, or guarantees that are not true.

3. Final Answer:

   It automatically adjusts the number of servers to match demand. -> Option A

4. Quick Check:

   Auto scaling = automatic server adjustment [OK]

Hint: Auto scaling means automatic server count changes [OK]

Common Mistakes:

• Thinking auto scaling is manual
• Confusing auto scaling with backups
• Assuming zero downtime without setup

2. Which AWS service is used to set up auto scaling for EC2 instances?

easy

A. AWS Lambda

B. AWS CloudTrail

C. Amazon EC2 Auto Scaling

D. Amazon S3

Solution

1. Step 1: Identify service for auto scaling EC2

   AWS provides a specific service called Amazon EC2 Auto Scaling to manage scaling of EC2 instances.

2. Step 2: Eliminate unrelated services

   AWS Lambda runs code, S3 stores files, CloudTrail logs activity. None handle auto scaling EC2.

3. Final Answer:

   Amazon EC2 Auto Scaling -> Option C

4. Quick Check:

   EC2 auto scaling service = Amazon EC2 Auto Scaling [OK]

Hint: EC2 auto scaling uses Amazon EC2 Auto Scaling service [OK]

Common Mistakes:

• Confusing Lambda with auto scaling
• Choosing storage or logging services
• Not knowing specific auto scaling service

3. Given this auto scaling policy: scale out when CPU > 70%, scale in when CPU < 30%. If CPU usage is 75%, what happens?

medium

A. The number of servers increases.

B. The number of servers decreases.

C. No change in server count.

D. The servers are replaced.

Solution

1. Step 1: Analyze the scale out condition

   The policy says to add servers when CPU usage is above 70%. CPU is 75%, so condition is met.

2. Step 2: Determine action

   Since CPU is high, auto scaling will increase server count to handle load.

3. Final Answer:

   The number of servers increases. -> Option A

4. Quick Check:

   CPU > 70% triggers scale out = increase servers [OK]

Hint: High CPU triggers scale out (add servers) [OK]

Common Mistakes:

• Confusing scale out with scale in
• Thinking servers are replaced automatically
• Assuming no change on high CPU

4. You set an auto scaling policy but notice your app still crashes during traffic spikes. What is a likely cause?

medium

A. The app does not need more servers during spikes.

B. Auto scaling automatically fixes all crashes without setup.

C. Auto scaling only works for storage, not servers.

D. The scaling policy thresholds are set too high, delaying scaling.

Solution

1. Step 1: Understand scaling delay impact

   If thresholds are too high, scaling triggers late, causing crashes during spikes.

2. Step 2: Eliminate incorrect options

   Auto scaling needs proper setup, does not fix all crashes automatically. It works for servers, not just storage. App likely needs more servers during spikes.

3. Final Answer:

   The scaling policy thresholds are set too high, delaying scaling. -> Option D

4. Quick Check:

   High thresholds delay scaling = crashes [OK]

Hint: Check if scaling thresholds are too high [OK]

Common Mistakes:

• Assuming auto scaling fixes crashes automatically
• Thinking auto scaling only manages storage
• Ignoring app server needs during spikes

5. You want to optimize costs by scaling down servers during low traffic but avoid frequent scaling actions. Which approach is best?

hard

A. Set aggressive scale-in thresholds with short cooldown periods.

B. Use moderate scale-in thresholds with longer cooldown periods.

C. Disable scale-in to keep servers always running.

D. Manually add and remove servers daily.

Solution

1. Step 1: Understand cost optimization and stability

   To save costs, scale down servers when traffic is low but avoid too frequent scaling to prevent instability.

2. Step 2: Evaluate options

   Aggressive thresholds and short cooldown cause frequent scaling (not good). Disabling scale-in wastes money. Manual scaling is inefficient. Moderate thresholds with longer cooldown balance cost and stability.

3. Final Answer:

   Use moderate scale-in thresholds with longer cooldown periods. -> Option B

4. Quick Check:

   Moderate thresholds + longer cooldown = cost and stability [OK]

Hint: Balance thresholds and cooldown for cost and stability [OK]

Common Mistakes:

• Setting too aggressive scale-in causing flapping
• Disabling scale-in wastes money
• Relying on manual scaling