How to Scale End-to-End Observability in AWS Environments

AWS Cost Anomaly Detection Uses Machine Learning

TL;DR

Amazon Web Services has recently launched the preview of AWS Cost Anomaly Detection to detect unusual spending patterns in AWS accounts. It aims to minimize unintended spending and improve cost controls.

AWS Cost Anomaly Detection Uses Machine Learning
AWS Cost Anomaly Detection Uses Machine Learning
Key Facts
  1. 1

    AWS Cost Anomaly Detection uses multi-layers machine learning technologies to learn the unique spend patterns of account holders.

  2. 2

    Account-holders receive an alert via email or SNS (Simple Notification Service) if unexpected or unusual spending is detected.

  3. 3

    Account-holders also receive an analysis of the root causes of the spending anomalies and the potential cost drivers.

  4. 4

    There are currently four different types of monitors- AWS Services, Linked account, Cost category, and Cost allocation tag.

  5. 5

    The AWS Cost Anomaly Detection is part of AWS Cost Management and currently free to use. Users, however, have to pay for SNS notifications generated.

Details

AWS Cost Anomaly Detection uses advanced machine learning technologies to detect unusual spending and its root causes.

It is quick to use: Users can create their own contextualized monitors and be alerted whenever there is anomalous spending, minimizing the risk of billing surprises. Users can configure their alerting preferences and customize the frequency of alerts. Users can configure their monitor for Anomaly Detection according to their business needs and how they want to control their cost and usage.

There are several challenges in cloud computing but managing cloud spending is probably the most difficult. When organizations use the cloud, they are billed continuously as consumption occurs instead of as and when they obtain their data center capacity. It makes creating accurate cost estimates very difficult for organizations, and they are often presented with bills that they hardly can explain.

Gartner Inc. forecasted that the cloud waste for 2019 amounted to nearly $14.1 billion. It is expected to hit a whopping $21 billion in 2021. Cloud waste occurs when organizations procure more cloud than they can utilize. For instance, many data centers let resources run full-time, even though they remain idle for most parts of the day.

Cloud spending is the amount of money that an organization spends on cloud infrastructure. One of the major reasons for cloud wastage is that most people do not understand how to manage cloud resources.


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How to Scale End-to-End Observability in AWS Environments

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