A company runs a large containerized workload with about 100 services on Amazon ECS. Developers have started running tasks on AWS Fargate instead of EC2. Historically the account has nearly reached its maximum number of EC2 instances. The company is concerned about hitting the maximum number of ECS tasks for Fargate and wants to notify the dev team when Fargate usage reaches 80% of the service quota. What should a solutions architect implement?

The correct solution leverages CloudWatch's ability to monitor service quota metrics directly. AWS publishes service quota usage metrics under the AWS/Usage namespace, making it straightforward to track current usage against the quota. A CloudWatch alarm with a math expression can then calculate the percentage of quota used and trigger an Amazon SNS notification when it exceeds 80%. This is a native, efficient, and real-time monitoring solution. The first incorrect option is flawed because Sample Count for a service in ECS typically refers to the number of data points collected, not the number of running tasks, and it doesn't directly provide the service quota for calculation. The third option, using a Lambda function to poll metrics, is less efficient and more complex than using native CloudWatch features. The fourth option, using AWS Config, is designed for evaluating resource compliance against rules, not for real-time monitoring of dynamic service quota usage.