Limited Time Offer!

For Less Than the Cost of a Starbucks Coffee, Access All DevOpsSchool Videos on YouTube Unlimitedly.
Master DevOps, SRE, DevSecOps Skills!

Enroll Now
Uncategorised

AWS Cost Anomaly Detection

November 14, 2023 Leave a Comment

Message from AWS

As part of your enablement of AWS Cost Explorer, we have configured AWS Cost Anomaly Detection for your account. Cost Anomaly Detection is a cost management service that helps you reduce cost surprises and enhance control without slowing innovation. It uses advanced machine learning models to detect and alert on anomalous spend patterns across your deployed AWS services. The cost monitor and daily email alert subscription we set up for you are free. You can change the default configuration via our console or API to customize the alerts you receive. You can also configure immediate alerts via SNS, though additional charges for using SNS may apply.
To get you started with AWS Cost Anomaly Detection, we pre-configured your account with an AWS Services monitor and a daily summary alerting subscription. With this setup, you will be alerted about anomalous spend that exceeds $100 and 40% of your expected spend across the majority of your AWS services in your accounts. See limitations here. If you want to modify your monitor or alert subscription setting, you can visit the Cost Anomaly Detection console or the public API to configure your cost monitors and alerting subscriptions to your specific needs. You can read more about how to use the service in our announcement blog, on our product page, and in our documentation.
FAQ:
Q: Why am I receiving this email?
In an effort to help our customers detect unintended spend, we are enabling Cost Anomaly Detection for all our new AWS Cost Explorer customers. This email is associated with your AWS account. If you are not interested in this service, you can opt-out by deleting your monitor and subscription in the console or via the API
Q: What is Cost Anomaly Detection?
Cost Anomaly Detection is an AWS cost management service that monitors customers’ spend continuously, uses machine learning to detect anomalies, and generates alerts with root cause analysis of what caused the anomaly. With the service, you can reduce unplanned spend and minimize time and resources in triaging root causes. You can read more about the service on our product page and in our documentation.
Q: What is the pricing of Cost Anomaly Detection?
There is no charge for Cost Anomaly Detection. The cost monitor and daily email alert subscription we set up for you are free. You can change the default configuration via our console or API to customize the alerts you receive. You can also configure immediate alerts via SNS, though additional charges for using SNS may apply.
Q: What type of anomalies will Cost Anomaly Detection detect?
With the default setup, Cost Anomaly Detection will monitor costs on the majority of your AWS services in your accounts. See limitations here.
Q: How will I be alerted about anomalies?
Any anomalous spend related to your account(s) will show up in the Cost Anomaly Detection console and via the API. In addition, if the anomaly is above $100 and exceeds 40% of expected spend, you will receive a daily summary email to the primary email associated with your account, detailing the cost impact, account name, the name of the monitor, the start and end dates, and the service where it was observed. The email will also include potential root causes for the anomaly.
Q: How do I opt out?
If you are not interested in this service, you can opt-out by deleting your monitor(s) and subscription(s) in the console or via the API. Read more in our documentation.
Q: What happens if I opt out? Can I still enable Cost Anomaly Detection at a later date?
Yes, if you decide to opt out now, you will still be able to enable Cost Anomaly Detection at a later time. When you opt out, you will still be able to use Cost Explorer without Cost Anomaly Detection.
Rajesh Kumar
Follow me
Latest posts by Rajesh Kumar (see all)
Subscribe
Notify of
guest
0 Comments
Newest
Oldest Most Voted
Inline Feedbacks
View all comments
0
Would love your thoughts, please comment.x
()
x