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Usage Metering

GPU Cloud Billing: From Usage Metering to Billing

Cloud providers building GPU or Neo Cloud services face a universal challenge: how to turn resource consumption into revenue with accuracy, automation, and operational efficiency. In our previous blog, we demonstrated how to programmatically retrieve usage data from Rafay’s Usage Metering APIs and generate structured CSVs for downstream processing in an external billing platform.

In this follow-up blog, we take the next step toward a complete billing workflow—automatically transforming usage into billable cost using SKU-specific pricing. With GPU clouds scaling faster than ever and enterprise AI workloads becoming increasingly dynamic, providers must ensure their billing engine is consistent, transparent, and tightly integrated with their platform. The enhancements described in this blog are designed exactly for that.

Architecture

GPU/Neo Cloud Billing using Rafay’s Usage Metering APIs

Cloud providers offering GPU or Neo Cloud services need accurate and automated mechanisms to track resource consumption. Usage data becomes the foundation for billing, showback, or chargeback models that customers expect. The Rafay Platform provides usage metering APIs that can be easily integrated into a provider’s billing system. '

In this blog, we’ll walk through how to use these APIs with a sample Python script to generate detailed usage reports.

Usage Metering