Computing Account Object Classification for Resource Optimization
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Solution Overview
Problem
Existing systems fail to optimize computing accounts by optimizing computing account objects associated with computing applications, particularly in reducing resource consumption and metadata management.
Innovation Solution
A computer-implemented method that identifies operational data to determine a deactivated status, parses computing account datasets to identify objects, applies a classification model, and generates representation requests to corresponding applications for deactivation or activation triggers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If computing account objects are not optimized, then resource consumption remains high, but implementing optimization increases system complexity
Solution Approach 1:
The patent segments the computing account into multiple computing account objects, each representing a specific computing application. This segmentation allows individual optimization of each object without requiring complete system redesign, thereby reducing resource consumption while managing complexity through modular decomposition of the account structure.
Solution Approach 2:
The system performs preliminary classification of computing account objects using a classification model before optimization. By pre-categorizing objects into different types (e.g., development, production, testing), the system can apply targeted optimization strategies to each category, reducing overall resource consumption while avoiding the complexity of ad-hoc optimization decisions.
2Loss of energy
If computing account objects are classified and optimized individually, then resource consumption is reduced, but the processing time increases
Solution Approach 1:
The patent implements periodic optimization cycles where computing account objects are classified and optimized at scheduled intervals rather than continuously. The system monitors operational data and triggers classification and optimization actions periodically, reducing resource consumption over time while avoiding the continuous processing overhead that would increase execution time.
Solution Approach 2:
The classification model operates autonomously to categorize computing account objects based on their operational characteristics. Once classified, objects self-optimize through automated triggers that adjust their resource allocation and configuration without manual intervention, reducing resource consumption while minimizing the time required for optimization decisions.
3Productivity
If operational data is monitored continuously to detect deactivated status, then account optimization is improved, but data processing requirements increase
Solution Approach 1:
The patent applies different monitoring thresholds and data collection frequencies to different types of computing account objects based on their classification. Critical objects receive continuous monitoring with detailed operational data collection, while less critical objects use sampling or threshold-based monitoring. This localized quality approach improves overall account optimization by focusing processing resources on high-priority objects while reducing data processing requirements for the broader system.
Data Source
AI summary
Systems, apparatuses, methods, and computer program products are provided. For example, a method provided herein may include identifying operational data representative of an activity amount associated with a computing account. In some embodiments, the method may include determining that the computing account is associated with a deactivated status based at least in part on the operational data. In some embodiments, the method may include parsing a computing account dataset associated with the computing account to identify a plurality of computing account objects. In some embodiments, the method may include applying the plurality of computing account objects to a computing account objects classification model. In some embodiments, the method may include generating a plurality of computing account representation requests. In some embodiments, the method may include transmitting each of the plurality of computing account representation requests to a corresponding computing application of the plurality of computing applications.