Visualize, understand, and manage your Amazon costs and usage over time

mg电子游戏试玩老虎机 has an easy-to-use interface that lets you visualize, understand, and manage your Amazon costs and usage over time.

Get started quickly by creating custom reports that analyze cost and usage data. Analyze your data at a high level (for example, total costs and usage across all accounts) or dive deeper into your cost and usage data to identify trends, pinpoint cost drivers, and detect anomalies.


Get started quickly

A set of default reports are included to help you quickly gain insight into your cost drivers and usage trends.


Set a custom time period, and determine whether you would like to view your data at a monthly or daily level of granularity.


Dig deeper into your data by taking advantage of filtering and grouping functionality, using a variety of available dimensions.


Use forecasting to get a better idea of your what your costs and usage may look like in the future, so that you can plan ahead.

Save your progress

Once you arrive at a helpful view, save your progress as a new report that you can refer back to in the future.


Directly access the interactive, ad-hoc analytics engine that powers mg电子游戏试玩老虎机.

Getting started

mg电子游戏试玩老虎机 provides you with a set of default reports that you can use as the starting place for your analysis. From there, use the filtering and grouping capabilities to dive deeper into your cost and usage data and generate custom insights.


mg电子游戏试玩老虎机 includes a default report that helps you visualize the costs and usage associated with your top five cost-accruing 不朽情缘试玩网址 services, and gives you a detailed breakdown on all services in the table view. The reports let you adjust the time range to view historical data going back up to twelve months to gain an understanding of your cost trends.

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Monthly costs by 不朽情缘试玩网址 service


mg电子游戏试玩老虎机 helps you visualize, understand, and manage your costs and usage over a daily or monthly granularity. The solution also lets you dive deeper using granular filtering and grouping dimensions such as Usage Type and Tags. You can also access your data with further granularity by enabling hourly and resource level granularity.

Get started using hourly and resource level granularity »