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Difficulty: HardAWS Cost Monitoring, Budgeting, and Optimization Tool Analysis

A company runs a data processing application on Amazon EC2. Due to occasional application deployment defects, the instances sometimes fail to terminate and run indefinitely, resulting in unexpected cost spikes. The operations team needs a solution to detect these anomalous spend patterns dynamically within 24 hours of occurrence without manually setting fixed threshold limits, as workload demands vary seasonally. Which solution will meet these requirements with the least operational overhead?

  1. A
    Configure AWS Cost Explorer to generate daily reports on usage cost variations, and set up an Amazon Simple Notification Service (Amazon SNS) topic to broadcast these reports.
  2. Implement AWS Cost Anomaly Detection, create a monitor for AWS services, and configure an anomaly subscription with daily or immediate alerting to an Amazon Simple Notification Service (Amazon SNS) topic.Answer
  3. C
    Create a CloudWatch billing alarm for the EstimatedCharges metric that triggers an Amazon Simple Notification Service (Amazon SNS) alert when charges exceed a statically defined monthly threshold.
  4. D
    Set up an AWS Budget to monitor Amazon RDS database costs, and configure a budget action to automatically purchase a Compute Savings Plan to mitigate any unexpected database spend spikes.

Answer

Implementing AWS Cost Anomaly Detection with a service monitor and an Amazon SNS subscription.
AWS Cost Anomaly Detection is a self-learning service that uses machine learning models to continuously monitor cost and usage, detect anomalies, and alert users. It does not require manual threshold definition, adjusts dynamically to seasonal variations, and can send alerts via Amazon SNS, fulfilling the requirements with minimal operational overhead.

Step-by-Step Solution

1
Analyze the requirement for dynamic, baseline-free anomaly detection.
Determine that static threshold-based alerting (like standard AWS Budgets or CloudWatch billing alarms) is unsuitable due to seasonal workload variations.
Fixed thresholds lead to false alarms during peak seasons or missed anomalies during low seasons.
2
Select the appropriate AWS cost management tool for proactive ML-driven detection.
Identify AWS Cost Anomaly Detection as the service that utilizes machine learning to continuously baseline and identify unexpected cost spikes.
It automates baseline adjustments and detects deviations without manual intervention.
3
Configure the notification mechanism for immediate alerts.
Configure an anomaly monitor with an Amazon Simple Notification Service (Amazon SNS) topic subscription.
This delivers proactive alerts to the operations team within 24 hours of anomaly detection.

Key Concept

AWS Cost Anomaly Detection provides proactive, machine learning-driven anomaly detection to identify cost anomalies with minimal latency, unlike retrospective analysis tools or static threshold budgets.
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AWS Cost Monitoring, Budgeting, and Optimization Tool Analysis