Scaling policies (target tracking, step, simple) in AWS - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

How does a target tracking scaling policy behave?

Consider an AWS Auto Scaling group with a target tracking scaling policy set to maintain an average CPU utilization of 50%. What happens when the average CPU utilization rises to 70%?

A The policy increases the number of instances to bring CPU utilization back to 50%.

B The policy decreases the number of instances to reduce CPU utilization further.

C The policy does nothing because CPU utilization is above the target.

D The policy terminates all instances to reset the group.

💡 Hint

Think about how target tracking tries to keep a metric close to a set value.

Target tracking scaling policies automatically adjust the number of instances to keep the specified metric (CPU utilization) near the target value (50%). When CPU utilization rises above 50%, the policy adds instances to reduce the load per instance.

❓ Architecture

intermediate

Choosing between step scaling and simple scaling

You want to scale your application based on CPU usage spikes. You want to add more instances quickly when CPU usage exceeds 80%, and remove instances slowly when CPU usage drops below 30%. Which scaling policy fits best?

A Use a target tracking policy set to 55% CPU utilization.

B Use a simple scaling policy with the same cooldown for scaling out and in.

C Use manual scaling to add and remove instances as needed.

D Use a step scaling policy with different step adjustments for scaling out and scaling in.

💡 Hint

Consider which policy allows different responses based on how much the metric changes.

Step scaling policies allow you to define multiple thresholds with different scaling actions. This lets you add many instances quickly when CPU usage is high and remove instances more slowly when usage is low.

❓ security

advanced

Security considerations for scaling policies

Which IAM permission is required to allow an Auto Scaling group to execute scaling policies?

A cloudwatch:PutMetricAlarm

B ec2:ModifyInstanceAttribute

C autoscaling:ExecutePolicy

D iam:PassRole

💡 Hint

Think about the permission that lets Auto Scaling perform scaling actions.

The autoscaling:ExecutePolicy permission allows the Auto Scaling group to run scaling policies that add or remove instances.

🧠 Conceptual

advanced

Cooldown period effect on simple scaling

What is the effect of setting a cooldown period in a simple scaling policy?

A It prevents additional scaling actions until the cooldown period ends, allowing the system to stabilize.

B It immediately triggers multiple scaling actions to quickly adjust capacity.

C It disables scaling actions during peak hours.

D It resets the scaling policy to default settings after each action.

💡 Hint

Think about why you might want to wait before scaling again.

The cooldown period prevents the Auto Scaling group from launching or terminating additional instances until the previous scaling activity is complete and the system stabilizes.

✅ Best Practice

expert

Optimizing cost and performance with scaling policies

You manage an Auto Scaling group for a web app with variable traffic. You want to minimize cost while maintaining performance. Which combination of scaling policies is best?

A Use step scaling only with large step adjustments for all traffic changes.

B Use target tracking for average CPU utilization and step scaling for sudden traffic spikes.

C Use manual scaling to control instance count precisely.

D Use only simple scaling with a short cooldown period.

💡 Hint

Consider combining policies to handle steady and sudden changes efficiently.

Target tracking maintains steady performance by adjusting capacity automatically, while step scaling handles sudden spikes quickly. This combination balances cost and responsiveness.

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