AWS Cost Anomaly Detection
A machine learning-based service that identifies unusual spending patterns in AWS accounts.
Description
AWS Cost Anomaly Detection is a feature offered by Amazon Web Services that leverages machine learning algorithms to monitor and analyze spending patterns across AWS accounts. By continuously assessing usage data, the service can detect anomalous spending that deviates from typical patterns, helping organizations to identify potential overspending or inefficiencies. This proactive approach to cost management allows businesses to react swiftly to unexpected changes in their AWS bills, which could arise from various factors such as unexpected spikes in usage, misconfigurations, or unauthorized resource usage. By alerting users to these anomalies, organizations can take corrective actions to optimize their cloud spending and maintain better budget control. This service is particularly beneficial for businesses with fluctuating workloads, as it provides insights into cost trends and helps in forecasting future expenses, thus facilitating more informed financial planning.
Examples
- A company experiences a sudden 300% increase in EC2 instance usage due to an unintentional configuration change, which is flagged by AWS Cost Anomaly Detection.
- An organization notices an unexpected spike in data transfer costs when a new application is deployed; the service alerts them, allowing for timely investigation.
Additional Information
- AWS Cost Anomaly Detection integrates with AWS Budgets, allowing users to set custom thresholds for alerts.
- The service provides a dashboard where users can view historical spending trends and identified anomalies, enhancing visibility into their AWS expenditures.