Cloud Service Availability Metrics for Objective Reliability Evaluation
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Solution Overview
Problem
Cloud software platforms face challenges in objectively evaluating the reliability and robustness of integrated services, relying on subjective user reviews that are prone to manipulation, making it difficult for developers to make informed decisions.
Innovation Solution
Automatically generating availability metrics such as overall availability, interruption availability, and recovery time for services, which are computed by the cloud software platform and presented in a services marketplace, providing objective measures for developers to assess service quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If subjective user reviews are used to evaluate service reliability, then developers can provide feedback on services, but the reviews become prone to manipulation and manipulation makes it difficult to make informed decisions
Solution Approach 1:
The patent replaces subjective human-based evaluation (user reviews) with an automated objective measurement system. The cloud software platform automatically collects operational data about service availability, interruptions, and recovery times, then computes quantitative availability metrics. This substitution of mechanical/automated measurement for human subjective evaluation eliminates manipulation while providing precise, comparable data for developers to make informed decisions about service reliability.
2Measurement precision
If automatic availability metrics are implemented, then objective service quality measures are provided, but the system complexity increases
Solution Approach 1:
The patent applies universality by designing a multi-functional availability tracking system that serves multiple purposes simultaneously. The same automated collection and computation infrastructure used to generate availability metrics also provides transparency to service developers, enables informed developer decisions, and gives platform operators visibility into service performance. This universal system handles multiple evaluation needs through a single integrated approach, reducing overall complexity compared to separate evaluation mechanisms.
Solution Approach 2:
The cloud software platform performs self-service by automatically collecting its own operational data about service availability and interruptions, then computing availability metrics without requiring external manual measurement. The platform monitors itself and provides the evaluation data autonomously, eliminating the need for complex external testing systems or manual assessment procedures while maintaining objectivity and precision in the measurements.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for computing availability metrics for an integrated service. One of the methods includes generating, for a service installed on a software platform, a plurality of availability logs, each availability log representing an occurrence of the service becoming unavailable. The plurality of availability logs are aggregated according to one or more aggregation criteria. The aggregated availability logs are processed to compute one or more availability metrics for the service, wherein each availability metric quantifies the availability of the service to process requests from the plurality of workloads in the presence of system failures and interruptions. An availability rating for the service is computed from the one or more availability metrics.