Which solution will meet these requirements with the LEAST operational overhead?
Configure Amazon CloudWatch dashboards to monitor EC2 instance utilization based on tags for department, business unit, and environment. Create an Amazon EventBridge rule that invokes an AWS Lambda function to stop underutilized development EC2 instances.
Configure AWS Systems Manager to track EC2 instance utilization and report underutilized instances to Amazon CloudWatch. Filter the CloudWatch data by tags for department, business unit, and environment. Create an Amazon EventBridge rule that invokes an AWS Lambda function to stop underutilized development EC2 instances.
Create an Amazon EventBridge rule to detect low utilization of EC2 instances reported by AWS Trusted Advisor. Configure the rule to invoke an AWS Lambda function that filters the data by tags for department, business unit, and environment and stops underutilized development EC2 instances.
Create an AWS Lambda function to run daily to retrieve utilization data for all EC2 instances. Save the data to an Amazon DynamoDB table. Create an Amazon QuickSight dashboard that uses the DynamoDB table as a data source to identify and stop underutilized development EC2 instances.
Explanations:
Using CloudWatch dashboards alone would require manual monitoring, which increases operational overhead. Additionally, there is no automated mechanism here to check utilization over multiple days and stop instances accordingly.
AWS Systems Manager does not natively track or report EC2 utilization data based on custom tags. This option would require additional custom setup to filter and stop instances, increasing operational overhead.
Trusted Advisor provides cost optimization checks and can detect underutilized EC2 instances. This solution uses an EventBridge rule and Lambda function to automate stopping instances, minimizing operational overhead.
This option requires a custom Lambda function, DynamoDB, and QuickSight, which is complex and requires manual data analysis, leading to increased operational overhead.