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Difficulty: MediumAWS Cost Explorer and Cost Anomaly Detection

A company hosts several testing workloads in a development AWS account. Due to the ad-hoc nature of these tests, resource utilization fluctuates wildly, resulting in highly variable and unpredictable daily spending. The SysOps administrator must set up a solution that uses machine learning to automatically detect unexpected cost anomalies and immediately send alert notifications to the operations team's Slack channel. Which solution will meet these requirements with the least operational overhead?

  1. Create an AWS Cost Anomaly Monitor for the account, configure an alert subscription, and integrate it with AWS Chatbot to deliver notifications to the Slack channel.Answer
  2. B
    Create an AWS Budget with a daily cost alert based on historical average spending, configure it to publish to an Amazon SNS topic, and subscribe the Slack channel webhook directly to the SNS topic.
  3. C
    Enable detailed monitoring in Amazon CloudWatch, create a CloudWatch alarm with anomaly detection on the Billing metric EstimatedCharges, and route the alarm to the Slack channel using AWS Chatbot.
  4. D
    Configure an Amazon EventBridge rule that triggers on AWS Config rule evaluation failures for cost changes, and invoke an AWS Systems Manager Automation runbook that formats the alert and calls the Slack API.

Answer

Create an AWS Cost Anomaly Monitor for the account, configure an alert subscription, and integrate it with AWS Chatbot to deliver notifications to the Slack channel.
The correct solution leverages AWS Cost Anomaly Detection, which uses machine learning to dynamically model spend profiles and eliminate false positives from variable workloads. It then routes notifications natively through AWS Chatbot directly to Slack, resulting in the lowest possible operational overhead.

Step-by-Step Solution

1
Select a cost-monitoring service that utilizes machine learning for variable spend.
Choose AWS Cost Anomaly Detection.
Unlike static budgets, Cost Anomaly Detection uses machine learning to dynamically establish baselines and adjust to irregular usage patterns, minimizing false-alarm fatigue.
2
Determine the lowest-overhead method to route alerts to Slack.
Use AWS Chatbot integrated with Cost Anomaly Detection subscriptions.
AWS Chatbot natively supports AWS Cost Anomaly Detection alert subscriptions and can format and post messages to Slack directly, eliminating the need to write and maintain custom integration code.

Key Concept

AWS Cost Anomaly Detection uses machine learning models to detect unexpected spikes in spending while AWS Chatbot provides native integration to deliver these alerts to chat channels with minimal configuration.
Estimated Time:1m 30s
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Topics

AWS Cost Explorer and Cost Anomaly Detection

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