Scaling policies (target tracking, step, simple) in AWS - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to specify the type of scaling policy for automatic scaling.

AWS

"PolicyType": "[1]"

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

AStepScaling

BTargetTrackingScaling

CManualScaling

DSimpleScaling

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing TargetTrackingScaling when asked for simple scaling type.

The SimpleScaling policy type triggers scaling based on a single adjustment.

2fill in blank

medium

Complete the code to set the target value for a target tracking scaling policy.

AWS

"TargetTrackingConfiguration": {"TargetValue": [1]

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

A75

B50

C100

D25

Attempts:

3 left

💡 Hint

Common Mistakes

Using 100 which might cause constant scaling up.

The TargetValue defines the metric value the scaling policy tries to maintain, commonly set to 50% for CPU utilization.

3fill in blank

hard

Fix the error in the step scaling adjustment configuration by completing the missing operator.

AWS

"StepAdjustments": [{"MetricIntervalLowerBound": 0, "ScalingAdjustment": [1]]

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

A1

B0

C-1

D2

Attempts:

3 left

💡 Hint

Common Mistakes

Using negative values which would scale in instead of out.

The ScalingAdjustment value of 1 means the capacity will increase by one unit when the metric exceeds the lower bound.

4fill in blank

hard

Fill both blanks to define a step scaling policy with a lower bound and scaling adjustment.

AWS

"StepAdjustments": [{"MetricIntervalLowerBound": [1], "ScalingAdjustment": [2]]

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

A10

B5

C1

D-1

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up lower bound and scaling adjustment values.

The lower bound is set to 10, and the scaling adjustment is 1 to increase capacity when the metric exceeds 10.

5fill in blank

hard

Fill all three blanks to configure a target tracking scaling policy with customized parameters.

AWS

"TargetTrackingConfiguration": {"PredefinedMetricSpecification": {"PredefinedMetricType": "[1]"}, "TargetValue": [2], "DisableScaleIn": [3]

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

AASGAverageCPUUtilization

B50

Ctrue

Dfalse

Attempts:

3 left

💡 Hint

Common Mistakes

Setting DisableScaleIn to true when scale-in is desired.

This configuration tracks average CPU utilization with a target of 50%, and allows scaling in by setting DisableScaleIn to false.

Practice

1. What is the main purpose of a target tracking scaling policy in AWS Auto Scaling?

easy

A. To automatically adjust resources to keep a metric close to a target value

B. To manually increase or decrease resources based on user input

C. To schedule scaling actions at fixed times regardless of load

D. To disable scaling during peak hours

Solution

1. Step 1: Understand target tracking policy function

   Target tracking automatically adjusts resources to keep a metric (like CPU usage) near a set target value.

2. Step 2: Compare with other options

   Manual scaling and scheduled scaling do not automatically adjust based on metrics, and disabling scaling is unrelated.

3. Final Answer:

   To automatically adjust resources to keep a metric close to a target value -> Option A

4. Quick Check:

   Target tracking = automatic metric-based scaling [OK]

Hint: Target tracking = auto adjust to keep metric near target [OK]

Common Mistakes:

• Confusing target tracking with manual scaling
• Thinking scheduled scaling is target tracking
• Assuming target tracking disables scaling

2. Which of the following is the correct JSON snippet to define a simple scaling policy in AWS Auto Scaling?

easy

A. {"PolicyName": "ScaleOut", "PolicyType": "TargetTrackingScaling", "TargetValue": 50}

B. {"PolicyName": "ScaleOut", "PolicyType": "StepScaling", "StepAdjustments": [{"MetricIntervalLowerBound": 0, "ScalingAdjustment": 1}]}

C. {"PolicyName": "ScaleOut", "PolicyType": "SimpleScaling", "AdjustmentType": "ChangeInCapacity", "ScalingAdjustment": 2}

D. {"PolicyName": "ScaleOut", "PolicyType": "ScheduledScaling", "Schedule": "cron(0 12 * * ? *)"}

Solution

1. Step 1: Identify simple scaling policy syntax

   Simple scaling uses PolicyType "SimpleScaling" with AdjustmentType and ScalingAdjustment fields.

2. Step 2: Verify JSON options

   {"PolicyName": "ScaleOut", "PolicyType": "SimpleScaling", "AdjustmentType": "ChangeInCapacity", "ScalingAdjustment": 2} matches simple scaling syntax; others are for target tracking, step scaling, or scheduled scaling.

3. Final Answer:

   {"PolicyName": "ScaleOut", "PolicyType": "SimpleScaling", "AdjustmentType": "ChangeInCapacity", "ScalingAdjustment": 2} -> Option C

4. Quick Check:

   Simple scaling = PolicyType "SimpleScaling" [OK]

Hint: Simple scaling uses PolicyType "SimpleScaling" with adjustment fields [OK]

Common Mistakes:

• Using TargetTrackingScaling type for simple scaling
• Confusing step scaling syntax with simple scaling
• Including schedule fields in simple scaling

3. Given this step scaling policy snippet:

{
  "PolicyType": "StepScaling",
  "StepAdjustments": [
    {"MetricIntervalLowerBound": 0, "ScalingAdjustment": 1},
    {"MetricIntervalLowerBound": 10, "ScalingAdjustment": 2}
  ]
}

If the metric increases by 12 units, how many instances will be added?

medium

A. 0

B. 1

C. 3

D. 2

Solution

1. Step 1: Understand step adjustments

   Each step defines scaling for metric intervals. For metric increase of 12, check which intervals apply.

2. Step 2: Find matching step

   12 is >=10, so the second step applies with ScalingAdjustment 2.

3. Final Answer:

   2 -> Option D

4. Quick Check:

   Metric 12 >= 10 -> add 2 instances [OK]

Hint: Metric value matches highest lower bound step [OK]

Common Mistakes:

• Adding adjustments from both steps
• Choosing the first step only
• Ignoring metric intervals

4. You configured a step scaling policy but it never triggers scaling actions even when the metric crosses thresholds. What is the most likely cause?

medium

A. The scaling adjustment values are negative

B. The metric alarms are not properly linked to the scaling policy

C. The target tracking policy is overriding the step scaling policy

D. The Auto Scaling group has no instances

Solution

1. Step 1: Check alarm linkage

   Step scaling policies rely on CloudWatch alarms to trigger. If alarms are not linked, no scaling occurs.

2. Step 2: Evaluate other options

   Target tracking does not override step scaling; negative adjustments cause scale-in, not no action; no instances means no scaling needed.

3. Final Answer:

   The metric alarms are not properly linked to the scaling policy -> Option B

4. Quick Check:

   Missing alarm linkage = no scaling trigger [OK]

Hint: Step scaling needs alarms linked to trigger [OK]

Common Mistakes:

• Assuming target tracking disables step scaling
• Ignoring alarm configuration
• Confusing negative adjustment with no scaling

5. You want to keep your application's CPU usage at 50% using AWS Auto Scaling. You also want to add 2 instances if CPU usage goes above 70%, and remove 1 instance if it drops below 30%. Which combination of scaling policies should you use?

hard

A. Use a target tracking policy for 50% CPU and step scaling for adding/removing instances at 70% and 30%

B. Use only a simple scaling policy with fixed adjustments

C. Use only a target tracking policy with target 50%

D. Use scheduled scaling to add and remove instances at fixed times

Solution

1. Step 1: Understand target tracking role

   Target tracking keeps CPU near 50% automatically adjusting capacity.

2. Step 2: Understand step scaling role

   Step scaling defines specific actions when CPU crosses 70% (add 2) or 30% (remove 1).

3. Step 3: Combine policies

   Use target tracking for steady state and step scaling for aggressive changes beyond thresholds.

4. Final Answer:

   Use a target tracking policy for 50% CPU and step scaling for adding/removing instances at 70% and 30% -> Option A

5. Quick Check:

   Target tracking + step scaling = precise control [OK]

Hint: Combine target tracking for steady and step scaling for thresholds [OK]

Common Mistakes:

• Using only one policy type for all needs
• Confusing scheduled scaling with metric-based scaling
• Ignoring removal scaling actions