Software Usage Metering via Data Store Operations
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Solution Overview
Problem
Current methods for measuring software application usage are inadequate as they rely on hardware consumption or time-based models, failing to accurately reflect actual business operations and charge for individual applications, features, or functions.
Innovation Solution
A system and method that meters usage by tracking data store operations associated with software applications, features, or functions, allowing for detailed and accurate usage data collection independent of hardware usage, with customizable metering profiles for different customer scenarios and usage scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hardware consumption or time-based usage models are used to measure software application usage, then measurement can be implemented, but the measurement precision is insufficient to accurately reflect actual business operations
Solution Approach 1:
The patent introduces data store operations as an intermediary metric to bridge the gap between hardware usage and actual business operations. By monitoring data reads, writes, and other data store activities, the system captures meaningful usage information that directly reflects business operations without requiring complex application-level instrumentation.
Solution Approach 2:
The patent replaces traditional mechanical/hardware-based metering mechanisms with a software-based data store monitoring approach. Instead of measuring CPU cycles, memory usage, or uptime, the system substitutes these with measurements of data store operations, providing a more business-relevant metric with simpler implementation.
2Adaptability or versatility
If capacity-based or time-based billing models are used, then billing can be implemented, but the ability to measure and charge for actual usage of individual applications, features or functions is lost
Solution Approach 1:
The patent segments usage measurement at the data store operation level, allowing individual tracking of reads, writes, deletes, and other operations. This granular segmentation enables flexible billing models where specific applications, features, or functions can be charged based on their actual data store consumption patterns.
Solution Approach 2:
The patent changes the measurement parameter from hardware resources (CPU, memory, time) to data store operations (reads, writes, queries). This parameter transformation enables new billing models that charge based on actual data access patterns rather than resource allocation or time elapsed.
3Ease of operation
If hardware usage metrics are used to report application usage, then reporting can be implemented, but the reliability of usage data to reflect actual business operations deteriorates
Solution Approach 1:
The patent implements self-service metering where the data store infrastructure automatically generates and reports usage metrics. The data store itself provides the measurement data through its operation logs and performance counters, eliminating the need for external monitoring agents and ensuring reliable, authoritative usage information.
Data Source
AI summary
A system and method for usage metering software applications (or features or functions) by monitoring the data store underlying the software application. The data store function may be implemented in many ways, such as a Relational Database, Transactional Database, Network and Graph Database, Object-Oriented Database, Embedded Database, In-memory Database, Schema-less Database, Files and Directories, whether structured or unstructured, Configuration Registries, or Non-traditional Repositories. Business activities performed by the software application are tracked and are independent of hardware usage. Such usage data is valuable in a variety of contexts, including billing based on business activity.