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Answer: Use a target tracking policy to dynamically scale the Auto Scaling group.
## Explanation **Correct Answer: B** - Use a target tracking policy to dynamically scale the Auto Scaling group. **Why this is correct:** 1. **Target tracking scaling policies** are specifically designed to maintain a specific metric at a target value. In this case, the requirement is to keep CPU utilization at or near 40%. 2. **How target tracking works:** - You set a target value (40% CPU utilization) - Auto Scaling automatically creates CloudWatch alarms - It adjusts the number of instances to keep the metric as close to the target as possible - It handles both scale-out (when CPU > 40%) and scale-in (when CPU < 40%) 3. **Benefits over other options:** - **Simple scaling (Option A):** Requires manual configuration of CloudWatch alarms and scaling adjustments. Less precise for maintaining a specific target value. - **Lambda function (Option C):** Overly complex solution for a standard scaling requirement. Adds unnecessary complexity and potential points of failure. - **Scheduled scaling (Option D):** Based on time rather than actual utilization. Won't respond to actual CPU usage patterns. **Key AWS Concepts:** - Target tracking scaling policies are ideal for maintaining specific metric values - They automatically create and manage CloudWatch alarms - They provide smooth scaling without manual intervention - They're the most efficient way to maintain a specific performance target like 40% CPU utilization **Best Practice:** For maintaining specific metric targets (like CPU utilization, request count per target, or average network I/O), target tracking scaling policies are the recommended approach in AWS.
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An application runs on Amazon EC2 instances across multiple Availability Zones. The instances run in an Amazon EC2 Auto Scaling group behind an Application Load Balancer. The application performs best when the CPU utilization of the EC2 instances is at or near 40%. What should a solutions architect do to maintain the desired performance across all instances in the group?
A
Use a simple scaling policy to dynamically scale the Auto Scaling group.
B
Use a target tracking policy to dynamically scale the Auto Scaling group.
C
Use an AWS Lambda function to update the desired Auto Scaling group capacity.
D
Use scheduled scaling actions to scale up and scale down the Auto Scaling group.