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Anomaly Detection

Be notified when our machine learning engine identifies anomalies in your cloud spend

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You don’t have to dig through a bunch of reports – Anomaly Detection points you to what you need to pay attention to, so that you can take corrective action before an anomaly becomes a big problem. For example, several customers have been able to identify and correct cryptojacking, which is a growing problem. In one case, if left unchecked it would have impacted their cloud spend by 30%. Another common example of an anomaly is when somebody on one of your tech teams is kicking the tires on a new service and forgets to turn it off.


We designed this feature to be as transparent and simple as possible, requiring almost no setup. We look for anomalies in every service across clouds, so there's no need to opt-in to particular services. This is critical, because often anomalies come from testing new services.


Use Views to define the scope of cloud resources for which you want to see anomaly detection and receive notifications.


We've calibrated a variety of algorithms to check for spending patterns that depart from the norm. Because most humans don't want to talk about Holt-Winters smoothing parameters, autocorrelation functions, seasonal-trend decomposition or even median absolute deviation thresholds, our service requires no tuning of any model parameters.

Instead, if we see an anomaly of at least $500, we'll send you an email. If you're getting too many or too few anomalies, you can adjust this dollar value threshold in your email subscription. In the UI, you'll always be able to see all your anomalies.

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