API Default Parameter Setting for Hybrid Cloud Device Configurations
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Solution Overview
Problem
In hybrid cloud storage management, existing methods struggle with setting optimal API parameters due to varying device configurations and the need for extensive knowledge and manual effort, leading to potential failures and increased management costs.
Innovation Solution
An information processing apparatus and method that collects and classifies API parameter information, using a higher-level API call to determine default values based on device configuration and execution logs, automatically setting parameters for lower-level API calls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed default values are used for API parameters, then the number of parameters to be designated by the user can be reduced, but the optimal parameter settings cannot be adapted to varying device configurations
Solution Approach 1:
The system performs preliminary actions by automatically collecting API execution logs and configuration information from target devices, classifying them according to device configurations, and determining optimal default values in advance. This preliminary data collection and analysis enables the system to provide adapted default values that match specific device configurations, resolving the contradiction between ease of operation and adaptability.
Solution Approach 2:
The system implements dynamics by making default values changeable and adaptable based on device configuration. Instead of using fixed default values, the system dynamically determines appropriate default values by classifying API execution logs according to device configurations and selecting the most frequent setting values. This allows the default values to adapt to varying device configurations while maintaining ease of parameter setting.
2Reliability
If manual determination of default values is performed, then optimal parameter settings can be achieved, but knowledge and manual man-hours are required
Solution Approach 1:
The system implements self-service by automatically collecting API execution logs and configuration information from target devices, classifying the data according to device configurations, and determining optimal default values without requiring external manual intervention. The system serves itself by using its own collected data to generate adapted default values, eliminating the need for external knowledge and manual man-hours while maintaining reliability.
Solution Approach 2:
The system uses feedback by collecting actual API execution logs from target devices and using this real-world data to determine optimal default values. The feedback loop involves collecting execution data, classifying it by device configuration, analyzing the most frequent setting values, and using this information to establish adapted default values. This data-driven feedback mechanism ensures reliability while automating the process to reduce time loss.
3Ease of operation
If existing setting templates are used, then the number of parameters to be set by a user can be reduced, but the templates cannot adapt to new device configurations or updated knowledge
Solution Approach 1:
The system performs preliminary actions by continuously collecting API execution logs and configuration information from target devices before determining adapted default values. This preliminary data collection enables the system to proactively adapt to new device configurations and updated knowledge, allowing existing setting templates to be dynamically updated without manual intervention, thus maintaining ease of operation while improving automation adaptability.
Solution Approach 2:
The system implements dynamics by making setting templates flexible and adaptable to new device configurations. Instead of using static existing templates, the system dynamically generates and updates setting templates by classifying API execution logs according to device configurations and determining the most frequent setting values. This dynamic approach maintains ease of parameter setting while enabling automation to adapt to new configurations and knowledge.
Data Source
AI summary
Information regarding an API parameter of a target device is collected from the outside as a manual and knowledge, a description regarding a device configuration, a main parameter, and a specific parameter for which a value is to be set is extracted from the collected manual and knowledge, and a classification axis is created based on the device configuration and the main parameter included in the extracted description. An API execution log and configuration information are collected from the target device, the collected API execution log is classified according to the classification axis, a setting value of the specific parameter in the API execution log is aggregated for each classification, a most frequent setting value is determined as a default value of the parameter, and when the specific parameter is not set in the higher-level API call, the default value is set to make a lower-level API call.