AWS Cost Anomaly Detection

The AWS Cost Anomaly Detection service is one such feature that can be used for identifying unusually high costs.

Introduction to AWS Cost Anomaly Detection

The AWS Cost Anomaly Detection service is a feature within the AWS Billing and Cost Management service that helps us identify and respond to unusual or unexpected changes in our AWS spending. The AWS Cost Anomaly Detection service uses machine learning to continuously analyze our AWS cost and usage patterns, detecting anomalies or significant deviations from the norm.

The service sends alerts when an anomaly is detected via AWS SNS or emails, enabling quick investigation and resolution. This tool is particularly useful for monitoring and managing cloud costs, preventing budget overruns, and ensuring cost-effective use of AWS services.

How the Cost Anomaly Detection service works

AWS Cost Anomaly Detection employs machine learning algorithms to continuously analyze AWS spending and usage patterns. Here’s a breakdown of how the Cost Anomaly Detection service works:

• Enabling the service: We enable and set up a Cost Anomaly Detection monitor. This involves specifying parameters such as the type of monitor, cost dimensions to track, and thresholds for alerting.

• Learning phase: The service starts by first learning the usual AWS usage and spending patterns over a period of time to establish a baseline for normal behavior.

• Continuous monitoring: The service then continuously monitors AWS costs and usage, comparing them against this established baseline. For a new service subscription, it monitors the service for a period of 10 days before detecting the anomalies.

• Anomaly detection: Using machine learning, the service detects significant deviations from the baseline, which are flagged as potential anomalies.

• Alerts: When an anomaly is detected, AWS Cost Anomaly Detection sends alerts to the user via email or an AWS SNS notification. These alerts contain details about the anomaly, including the affected services and the potential cost impact.

• Root cause analysis: Additionally, the service may provide insights into the possible causes of the anomaly, aiding us in understanding and addressing the issue.

Based on the alerts and anomaly details provided by AWS Cost Anomaly Detection, we can do a root cause analysis to take the appropriate action before we get an expensive bill.

Use cases

Here are some use cases of the AWS Cost Anomaly Detection service:

• The primary purpose of the AWS Cost Anomaly Detection service is to prevent and control unexpected high spending.

• The AWS Cost Anomaly Detection service can detect cost spikes that might indicate accidental overuse or misconfigured resources.

• The AWS Cost Anomaly Detection identifies unusual activity that could suggest security breaches or unauthorized use of AWS resources.

• The AWS Cost Anomaly Detection service alerts when spending exceeds expected thresholds, helping to keep budgets in check.

This lesson taught us how to detect cost anomalies on our AWS account with the help of the AWS Cost Anomaly Detection service that leverages machine learning.