Cross Cloud Serving Configuration Evaluation
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Solution Overview
Problem
Existing technologies face challenges in efficiently serving cloud workloads across multiple cloud services while minimizing computational overhead and ensuring compliance with tail latency constraints.
Innovation Solution
The implementation of a computer-implemented method and system, known as xCloudServing, which evaluates configurations across multiple cloud services to select the most cost-effective and latency-compliant configuration for deploying cloud workloads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud workload is served across multiple cloud services, then service availability and flexibility are improved, but computational overhead and complexity increase
Solution Approach 1:
The patent introduces an intermediary evaluation system that acts as a mediator between multiple cloud services and the workload. This evaluation system pre-assesses configurations across cloud services, caching results to avoid repeated evaluations. The intermediary manages the complexity by centralizing the evaluation logic and providing a standardized interface, thus improving service availability without proportionally increasing computational overhead.
Solution Approach 2:
The patent implements preliminary evaluation of configurations before actual workload deployment. By pre-evaluating and caching configuration results across multiple cloud services, the system prepares ahead of time, avoiding the need to perform complex evaluations in real-time. This preliminary action reduces the computational overhead during actual service delivery while maintaining high adaptability.
2Measurement precision
If comprehensive configuration evaluation is performed across multiple cloud services, then selection accuracy is improved, but evaluation time and resources increase
Solution Approach 1:
The patent applies local quality by evaluating and caching configurations specific to each cloud service and workload type. Rather than performing exhaustive evaluations for every possible scenario, the system evaluates configurations locally for specific contexts and caches these results. This approach maintains high selection accuracy for each specific case while reducing overall evaluation time by avoiding redundant assessments.
Solution Approach 2:
The patent uses copying by caching evaluation results that can be reused across similar workloads and cloud service configurations. Once a configuration is evaluated and cached, the system copies this evaluation result for use in similar scenarios, maintaining measurement precision for the cached configurations while significantly reducing the time and resources required for repeated evaluations.
3Productivity
If configuration caching is implemented, then evaluation efficiency is improved, but memory usage and data management complexity increase
Solution Approach 1:
The patent extracts only the essential configuration parameters and evaluation results needed for caching, rather than storing complete configuration sets. By extracting and caching only the critical evaluation data (performance metrics, compatibility information, and key configuration parameters), the system improves evaluation efficiency while keeping memory usage manageable. Non-essential data is omitted from the cache, reducing storage requirements.
Data Source
AI summary
A computer product and methodology for serving a cloud workload across multiple cloud service providers. A first evaluation is performed for a first configuration in a first cloud service of the plurality of cloud services, and a second evaluation is performed for a second configuration in a second cloud service of the plurality of cloud services. A first result of the first evaluation and a second result of the second evaluation are used to select an unevaluated configuration in one of the first and second cloud services for performing another evaluation.