Small Leaks Sink Big Ships
Unwanted expenses, if unnoticed, could quite possibly be catastrophic for companies using AWS who do not have a designated team that monitors spending on AWS on a regular basis.
This issue highlights the need for a feature like Anomaly Detection that allows companies with sizeable footprints on AWS to accurately identify and plug such ‘leaks’ in their budget.
Anomaly Detection – Key Features:
Anomaly Detection provides users with the information to:
- Identify excessive or irregular spending.
- Pinpoint changes in resource usage patterns and assess whether they were expected or unexpected.
- Be aware and in control of their expenses on AWS without having to check their account on a daily basis. Notifications are also sent to users via email to inform them of anomalies in their spending patterns.
Why Is Anomaly Detection Important?
Cost Optimization and Rapid Feedback
It goes without saying that the optimization of budgets is one of the key priorities for most AWS users. Anomaly Detection facilitates this optimization by alerting users and helping them discover anomalies in their spending as early as possible. Having a feature that automatically identifies anomalies early on allows users to not only save a lot of time in their monitoring efforts, but it also allows them to make the changes they need to prevent (or predict) such anomalies in the future.
Anomaly Recognition and Effective Cost Breakdowns
Sifting through and deciphering the invoices provided by AWS and then try to draw a correlation between costs and resource usage can be quite a demanding task. Not to mention that even if you were to recognize the fact that there’s something irregular in your spending, you’d still need to be able to pinpoint the cause for this irregularity and figure out the changes you need to make to prevent unwanted spending in the future.
Fortunately, Anomaly Detection does most of the heavy lifting for users. Anomalies are automatically recognized and can be identified even by users with minimal technical expertise. Additional charts, graphs, and other visual tools provided by TrackIt’s AI then allow the user to dive deeper into the cost analysis and make the necessary technical changes in AWS.
Accurate Monitoring of Costs for New Resources Launched on AWS
Anomaly Detection allows you to accurately monitor the evolution of costs when new resources are launched on AWS. An anomaly occurs as soon as the new resource is deployed, and this allows users to scrupulously track the changes in spending during the early stages after deployment.
An Algorithm Borrowed from The Financial Realm:
The algorithm for Anomaly Detection is based on Bollinger Bands, a type of statistical chart used in the financial industry to provide a relative definition of high and lows prices of a market. Bollinger Bands serve as an indicator designed to provide traders with information regarding price volatility.
A Bollinger Band is typically a set of lines plotted two standard deviations (positively and negatively) away from a simple moving average of a specific security’s price.
The algorithm’s simplicity in terms of implementation and effectiveness in identifying abrupt changes in prices (or costs) allowed TrackIt’s team to use it to effectually identify anomalies in spending on AWS.
Discover the full version of this white paper by downloading the PDF and learn more about Anomaly Detection.
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