Flexer released its latest analysis report based on the experience of 750 enterprise executives. The report points out that most companies spend over $1 million on the cloud annually, with an average of 30% of cloud spending wasted.

As mentioned in the "Cloud Cost Management Guide": "To reduce cloud costs, you must first be able to identify waste by discovering inefficient use of cloud resources. Cloud cost management is not a one-time process, but if you solve the core problem of wasted cloud spending and budget overruns, you can immediately save on cloud infrastructure costs."

In response to customers' needs to reduce resource waste, AWS launched a powerful tool that uses machine learning to analyze waste in AWS account compute resources and recommend optimal AWS resources, reducing costs while improving workload performance. It's not only accurate and reliable, but more importantly, this tool is not only easy to use but also free.

Compute Optimizer

AWS Compute Optimizer helps you use machine learning to analyze historical utilization metrics to determine optimal AWS resource configurations, such as Amazon EC2 instance types, Amazon EBS volume configurations, and AWS Lambda function memory sizes. AWS Compute Optimizer provides a set of APIs and console experiences to help you reduce costs and improve workload performance by recommending optimal AWS resources for your workloads.

How It Works

AWS Compute Optimizer generates optimization recommendations by analyzing Amazon CloudWatch metrics and related configuration data (such as instance types, volume types, and memory sizes). It uses machine learning algorithms to analyze your resources' utilization history and identify optimal resource configurations.

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