Welcome to the Cost Optimization lesson. The cloud is only cheap if you use it correctly. Over-provisioning servers is a rapid way to burn through an IT budget.
Companies value engineers who can save them money. By utilizing automated AWS tools to right-size your instances and track spending anomalies, you become a massive asset to your organization.
In this tutorial, you will learn about:
AWS Compute Optimizer uses machine learning to analyze your historical resource consumption patterns. If you have an m5.large EC2 instance running, but Compute Optimizer notices you never use more than 10% of the CPU, it will explicitly recommend that you "right-size" the server by downgrading it to an m5.medium to save money.
AWS Cost Anomaly Detection continuously monitors your cost and usage using machine learning to detect unusual spends. If a junior developer accidentally loops an API call that suddenly costs $500 in one hour, Anomaly Detection will flag the unusual spike and alert you immediately via Slack or email.
Which service uses machine learning to analyze your EC2 consumption and recommends downgrading the instance size to save money?