Zero Waste. More Money for R&D.
IT departments acquire their server infrastructure needs assuming ‘theoretical max’ workload requirements (i.e., ~100% utilization of their available computing resources). This is done to avoid performance issues for when encountering surging demand for resources needed, for example, a spike in website traffic. However, surges for most workloads are infrequent, which ends up resulting in organizational overbuying and staggering underutilization of available computing resources.
The real value to an organization are the computing resources its workloads actually consume. Despite this, commercial models for running on-premise or in the AWS or Microsoft cloud are based upon the time and “allocation” of computing resources (i.e., the total resources being supplied), instead of resources consumed, and customers are forced to accept that a vast unmeasured portion of their IT investment continuously goes to waste - often unknown to the C-Suite.
The following screenshot is an example of the Cloud Gauge in action. It shows how the consumer measured their server usage.
The Cloud Gauge
The Cloud Gauge delivers a solution that measures the underlying computing resources an organization actually uses to quantify its “True Consumption”. It monitors and collects usage metrics from disparate resources and converts them into a standardized unit of measure, known as the Workload Consumption Unit (“WCU”), enabling an apples-to-apples cost comparison and benchmark. It works similar to how an electricity meter measures WATT consumption when appliances are powered on. From a usage perspective, the WCU is equivalent regardless of the provider or hardware on which an application runs on. What makes is so unique is that it can seamlessly adapt to measures environments inclusive of GPUs - the backbone resource for computing AI, Machine Learning (ML), and High-Performance Computing (HPC) workloads.
The Cloud Gauge is available today in a cloud-hosted version, or can be installed to run exclusively behind your firewall (coming soon).