When we use cloud services, it's important not only to find ways to reduce costs, such as purchasing cost-saving plans offered by various cloud platforms, but also to monitor "cost anomalies." Regularly monitoring cost status allows us to determine if there are any anomalies and analyze the reasons behind them, enabling us to adjust configurations and reduce the chances of recurrence. Today, we will briefly introduce the Cost Anomaly Detection feature provided by AWS. Let's take a look!
3 Steps to Implement AWS Cost Anomaly Detection
AWS Cost Anomaly Detection identifies anomalous cost expenditures and investigates the root causes using Machine Learning technology.
First, you can create a Cost Monitor with custom anomaly thresholds to evaluate anomalous expenditures for all AWS services or specific member accounts, cost allocation tags, and cost categories under a particular organization. Using machine learning, it assesses your spending patterns to minimize false alarms by understanding weekly or monthly seasonal growth and natural increases based on seasonal awareness patterns.
Next, you can set up alert preferences. When anomalous expenditures are detected, you can choose to receive notifications daily or weekly via email or SNS. After setting up the cost monitor and subscribing to anomaly alert notifications, Cost Anomaly Detection will be activated within 24 hours. You will receive notifications when costs reach the anomaly thresholds you set. However, note that detecting new services requires 10 days of historical data.
Finally, upon detecting an anomalous expenditure, you can monitor and analyze the root causes of the anomaly using the Cost Anomaly Detection dashboard. This includes identifying which AWS service, account, region, or usage type caused the cost spike. Further analysis of your usual cost drivers provides more accurate anomaly detection results. Additionally, you can perform anomaly analysis in AWS Cost Explorer to reduce the risk of unexpected bills.
Are you eager to try it out? Join us on AWS to experience the operation of Cost Anomaly Detection!
References: https://aws.amazon.com/tw/aws-cost-management/aws-cost-anomaly-detection/