Cloud Design Evaluation Platform for Reliability-Cost Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cloud computing systems lack an automated model to determine which components and subcomponents require replication for optimal architecture design, leading to inefficient cost management and inflexible Service Level Agreements (SLAs) that do not cater to varying customer reliability needs.
Innovation Solution
A cloud computing design evaluation platform that receives a master variant of components, determines the maximum number of parallel levels, creates potential variants by expanding with parallel components, calculates reliability and cost information, and automatically selects the most optimal architecture based on overall reliability and cost scores, while allowing for continuous monitoring and future performance predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If components are replicated in parallel to improve reliability, then system availability increases, but system cost increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the replication level of components based on calculated reliability parameters and cost constraints. The system evaluates different replication scenarios and selects the optimal configuration that achieves the required availability target while minimizing cost, rather than using fixed replication rules.
Solution Approach 2:
The patent implements dynamics by enabling automatic, real-time adjustment of component replication based on changing system conditions, failure rates, and cost parameters. The system continuously monitors performance and automatically modifies the architecture to maintain optimal reliability-cost balance without manual intervention.
2Adaptability or versatility
If manual selection of elements to replicate is performed, then system design flexibility is maintained, but design efficiency decreases and unnecessary costs are incurred
Solution Approach 1:
The patent applies self-service by implementing an automated system that performs the entire component replication selection process without human intervention. The system automatically analyzes system requirements, calculates optimal replication strategies, and generates the refined architecture, eliminating the need for manual design while maintaining adaptability through configurable parameters.
Solution Approach 2:
The patent replaces the manual mechanical design process with an automated computational system. Instead of human experts manually analyzing and designing component replication, the system uses algorithms to automatically evaluate scenarios and determine optimal replication strategies, substituting human cognitive work with automated computation.
3Ease of operation
If static SLA is offered to all customers, then service provider operational simplicity is maintained, but customer-specific reliability needs cannot be met
Solution Approach 1:
The patent applies local quality by enabling different SLA configurations and replication strategies to be applied to different customers or system components based on their specific requirements. Instead of a uniform approach, the system tailors the reliability and cost parameters to match individual customer needs, allowing high-availability customers to receive enhanced replication while standard customers receive baseline service.
Data Source
AI summary
A cloud computing design evaluation platform may receive a master variant for a cloud computing design, including a sequential sequence of a set of components. The evaluation platform may then determine a maximum number of parallel levels for the master variant and automatically create a plurality of potential variants of the master variant by expanding the master variant with parallel components in accordance with the maximum number of parallel levels. The evaluation platform determines reliability information (e.g., based on MTBF data) and cost information (e.g., a TCO) for each component. An overall reliability score and overall cost score for each of the automatically created potential variants is automatically calculated and an evaluation result of the calculation is indicated (reflecting an optimum design that meets SLA and TCO goals). Some embodiments may also provide continuous monitoring of design performance and/or predict future design performance based on historical data.