Cloud Resource Performance Evaluation via Uniform Data Stream Normalization
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Solution Overview
Problem
Evaluating resource performance across different cloud platforms is challenging due to misaligned metric and reporting parameters, making it difficult to compare and optimize virtual and non-virtual cloud resources effectively.
Innovation Solution
A system that collects performance data from various cloud providers, normalizes it to create uniform data streams, and evaluates resource utilization to determine if resources are overloaded or underutilized, allowing for reconfiguration of cloud resources across platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud resources are monitored using different metric parameters and reporting parameters across cloud providers, then each cloud platform can capture resource metrics independently, but the data from various clouds become misaligned and not comparable with each other
Solution Approach 1:
The patent transforms misaligned cloud resource metrics from different cloud providers by normalizing multiple metric parameters and reporting parameters into a unified set of parameters. This allows data from various clouds to be aligned and comparable while preserving the ability to work with different cloud platforms independently.
Solution Approach 2:
The patent introduces an intermediary normalization layer that sits between diverse cloud provider metrics and the evaluation system. This intermediary transforms and aligns the misaligned metrics into a common framework, enabling comparison across platforms without requiring changes to the original cloud provider systems.
2Ease of manufacture
If conventional methods are used to compare resource performance amongst different cloud platforms, then implementation is simple, but the comparison is limited because data from various clouds are misaligned and not comparable
Solution Approach 1:
The patent performs preliminary normalization of cloud resource metrics before evaluation and comparison. By pre-aligning the metric parameters and reporting parameters from different cloud providers into a unified format, the system ensures accurate and reliable performance evaluation while maintaining implementation simplicity.
3Productivity
If cloud resources are monitored without normalization, then data collection is straightforward, but resource performance evaluation across platforms is difficult due to misaligned data
Solution Approach 1:
The patent efficiently collects cloud resource metrics and then applies parameter transformation to normalize the collected data. This two-step approach maintains high data collection productivity while systematically addressing the alignment complexity through unified parameter transformation.
Data Source
AI summary
A processing device sends a request to a cloud provider for data for a metric for a particular resource being provided by the cloud provider, receives one or more data steams for the metric for the particular resource from the cloud provider. The one or more data streams includes data points over a specified period of time. The data points have one or more different time intervals between the data points. The processing device creates a uniform data stream from data in the one or more data streams. The uniform data stream includes data points that have the same time intervals between the data point. The processing device determines the utilization of the particular resource from the uniform data stream.