Last year, Cloudability launched its rightsizing recommendations for AWS – a feature that has now been adopted by many of its customers. The Portland-based firm has now announced the release of Rightsizing Recommendations for Microsoft Azure.
The Rightsizing Recommendations feature can be used to help with cost optimization. Organizations are provided with recommendations on how they can build and scale their cloud infrastructure to meet the needs of the business, while eliminating wastage by ensuring only the resources that are required by the business are provisioned. By using the Rightsizing Recommendations feature for AWS and Azure, resources can be closely matched to usage, helping business to make considerable savings on their cloud bills.
Rightsizing Recommendations can be used by customers whose primary cloud service provider is AWS or Azure, as well as for multi-cloud environments.
The feature gives businesses insight into how their compute resources are being utilized over time, with a range of utilization metrics provided per resource. Cloudability uses statistical models and its own algorithms to determine the cost savings that can be made and the level of risk involved. Customers can then choose implement one of several recommendations based on their level of risk tolerance.
The feature determines usage over a set time frame and takes peaks into account in its statistical models and algorithms to ensure there will be sufficient capacity. Cloudability has used extensive customer data to determine performance characteristics across instance families and types and has a high level of confidence in its recommendations.
The recommendations can be presented in graphical form, with the option of overlaying current workload utilization usage data and anticipated performance to help with risk assessment. This option clearly shows the margins of error and how much headroom they will have before actioning rightsizing initiatives.
The recommendations are made per resource and are ordered by the cost savings that can be made with the level of risk involved clearly indicated. Customers can then determine which option is the best choice and most accurately meets their needs.