Configurable Workload Modeling for Storage Testing
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Solution Overview
Problem
Conventional testing devices are limited in mimicking real-world workloads for storage devices, and modifying predefined workloads is cumbersome and time-intensive, failing to cover all necessary scenarios for customers.
Innovation Solution
A system and method for modeling workloads using user-configurable settings for file systems, emulated users, and interaction behavior, allowing for the creation of diverse workload scenarios through configurable objects like file system, user profile, and access objects, enabling users to customize and mix these objects to generate various workloads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If predefined workloads are used for testing, then testing can be performed with standard configurations, but the workloads are limited and do not cover all customer scenarios
Solution Approach 1:
The workload model is divided into multiple independent configurable objects including file system object, user profile object, and access object. Each object can be configured separately and then combined to form complete workload scenarios, enabling versatile testing while maintaining manageable complexity through modular configuration.
Solution Approach 2:
The configurable workload modeling system provides universal applicability across different customer scenarios by allowing customization of file system parameters, user profiles, and access patterns. The same basic framework can adapt to various testing needs through parameter configuration rather than requiring different testing devices for different scenarios.
2Adaptability or versatility
If predefined workloads are modified to cover more scenarios, then workload coverage improves, but the modification process becomes cumbersome and time intensive
Solution Approach 1:
The system provides pre-configured template objects for file systems, user profiles, and access patterns that can be selected and customized. This preliminary preparation of configurable templates eliminates the need for time-consuming manual construction of workload parameters from scratch, reducing configuration time while maintaining scenario coverage.
Solution Approach 2:
The workload configuration system allows dynamic adjustment of parameters through programmmatic interfaces and configuration files. Users can modify workload characteristics by changing parameters in configuration objects rather than manually editing complex test scripts, enabling rapid adaptation to different scenarios without time-intensive reconfiguration.
Data Source
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AI summary
Methods, systems, and computer readable media for modeling a workload are disclosed. According to one method, the method occurs at a computing platform. The method includes providing for user configuration of a file system associated with a device under test (DUT), providing for user configuration of at least one emulated user, and providing for user configuration of interaction behavior between the at least one emulated user and the file system.