Explanation:
CloudWatch metrics explorer is a tag-based tool that allows you to aggregate and visualize metrics across resources. By filtering by the aws:autoscaling:groupName tag, the dashboard widget will automatically include any new instances launched by that Auto Scaling group because they automatically inherit the ASG tag. This is more efficient than using Lambda to manually update dashboard JSON (Option A).
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Question 18. A company runs an application on Amazon EC2 instances behind an Application Load Balancer. The EC2 instances are in an Auto Scaling group. The application sometimes becomes slow and unresponsive. Amazon CloudWatch metrics show that some EC2 instances are experiencing high CPU load. A SysOps administrator needs to create a CloudWatch dashboard that can automatically display CPU metrics of all the EC2 instances. The metrics must include new instances that are launched as part of the Auto Scaling group. What should the SysOps administrator do to meet these requirements in the MOST operationally efficient way?
A
Create a CloudWatch dashboard. Use activity notifications from the Auto Scaling group to invoke a custom AWS Lambda function. Use the Lambda function to update the CloudWatch dashboard to monitor the CPUUtilization metric for the new instance IDs.
B
Create a CloudWatch dashboard. Run a custom script on each EC2 instance to stream the CPU utilization to the dashboard.
C
Use CloudWatch metrics explorer to filter by the aws:autoscaling:groupName tag and to create a visualization for the CPUUtilization metric. Add the visualization to a CloudWatch dashboard.
D
Use CloudWatch metrics explorer to filter by instance state and to create a visualization for the CPUUtilization metric. Add the visualization to a CloudWatch dashboard.
E
None
F
None
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