CloudPhysics Unveils Cost Calculator
Allows organizations to examine VM workloads and accurately estimate and compare private cloud and public cloud costs.
CloudPhysics has introduced the Cost Calculator for Private Cloud with the Public Cloud Comparison tool. This data-driven solution automates the process of determining the accurate costs of a customer’s currently resourced on-premises Virtual Machines (VMs). Customers can compare those amounts to the costs for the same VMs if they were migrated to a public cloud.
The Cost Calculator for Private Cloud allows the customer to rightsize VMs by comparing a VM’s current resources, such as CPU and storage, with the amount the VM actually requires to perform its functions. Because many VMs are overprovisioned with resources, rightsizing helps a customer save costs per workload, whether on-premises or in the cloud. By rightsizing workloads, customers are assured that VM provisioning fits actual usage.
The calculator also offers customers the unique ability to conduct “apples-to-apples” comparison of virtual workloads in a private cloud model, where resources are shared — vs. the public cloud model, where resources are subscribed from a cloud service provider. Users can create scenarios that compare their private cloud costs vs. public cloud estimates with utilization levels at Peak, 95th, and 99th percentiles. They can then accurately determine what these workloads cost to operate in the public cloud at those respective levels.
“Organizations typically do not have a current cost-per-workload model in their private cloud, and have very poor tools to allow for the pricing and comparison of private vs. public cloud costs,” said Chris Schin, VP, Products at CloudPhysics. “Our Cost Calculator for Private Cloudensures that IT decision makers have real, actionable data regarding the savings a public cloud can potentially provide vs. their current operational costs.”
The Cost Calculator for Private Cloud determines cost based on selected workloads, hosts, clusters, or data centers and calculates the cost per workload/virtual machine (VM). This allows IT administrators to understand the cost of a workload based on size and resource utilization in a private cloud environment. Once private cloud costs are known, workloads can accurately be compared against public cloud hosting costs to determine if savings can be achieved on a workload-by-workload basis.