Amazon's Elastic Container Service (ECS) requires robust monitoring to ensure efficient management of containerized functions, with specific metrics differing based on whether EC2 or Fargate compute functions are used. ECS monitoring includes tracking CPU and memory reservation and utilization, as well as the number of running tasks to prevent outages. AWS provides tools for collecting and processing ECS data, but custom metrics and alarms must be set up manually in CloudWatch to track application-level metrics like error logs. Third-party platforms such as Coralogix offer enhanced analytics and automatic alerts for ECS monitoring, using machine learning to detect anomalies and potential issues with minimal customization.