Overview

What Is Cost Anomaly Detection?

Cost Anomaly Detection uses machine learning to analyze your historical pay-per-use and yearly/monthly expenditures, establish a specific expenditure model for you, and identify root causes for cost surprises based on forecasted amounts. With simple steps, Cost Anomaly Detection helps you quickly take action based on detected cost anomalies to maintain your planned expenditures.

You can create monitors for all services, for just linked accounts, or based on cost tags. Only one monitor type is recommended for an account. Otherwise, duplicate anomalies may be recorded.

• All services: This type of monitor tracks the expenditure anomalies for all your services. It is recommended if you do not need to group costs within your enterprise. Only one monitor of this type can be created under an account.
• Linked accounts: This type of monitor tracks the pay-per-use expenditure anomalies for an individual linked account. It can be useful if you are using a master account for unified accounting management and want to group costs by linked accounts. The master account can create only one monitor of this type for each linked account.
• Cost tags: This type of monitor tracks the expenditure anomalies for an individual cost tag key-value pair. It is recommended if you want to group costs by cost tags. Only one monitor of this type can be created for each cost tag value.
• Cost categories: This type of monitor tracks the expenditure anomalies for an individual cost category. It is recommended if you want to group costs by cost categories.
• Enterprise projects: This type of monitor tracks pay-per-use and yearly/monthly expenditure anomalies for the specified enterprise project. It is recommended if you want to group costs by enterprise project.