Cloud Node Suitability Assessment via Synthetic Application Simulation
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Solution Overview
Problem
Current cloud hosting systems lack an effective method to assess the suitability of nodes for specific applications, leading to insufficient computing capacity and performance issues due to resource constraints.
Innovation Solution
The method involves defining synthetic application definitions that mimic the resource consumption patterns of candidate applications, deploying these definitions to nodes in a cloud system, and evaluating the performance to determine the suitability of nodes for hosting applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computing capacity is increased to provide quality performance for applications, then application performance is improved, but resource availability and system cost increase
Solution Approach 1:
The system performs preliminary assessment of node suitability for hosting applications by deploying synthetic applications that simulate resource consumption patterns. This advance evaluation identifies which nodes can accommodate specific applications without performance degradation, enabling proactive resource allocation decisions before actual application deployment and avoiding unnecessary resource provisioning.
Solution Approach 2:
Synthetic applications are created as simplified copies that replicate the resource consumption behavior of actual applications. These synthetic versions consume resources in patterns equivalent to target applications, allowing the system to evaluate node suitability without deploying the full-scale production applications, thereby reducing the resources needed for assessment.
2Measurement precision
If synthetic applications are deployed to assess node suitability, then assessment accuracy is improved, but system complexity increases
Solution Approach 1:
The synthetic application framework serves multiple functions: it assesses node suitability for different applications, evaluates resource allocation strategies, and identifies performance bottlenecks. A single synthetic application infrastructure can be configured to test various application types by adjusting the synthetic application definition, eliminating the need for separate assessment systems for each application.
Solution Approach 2:
The system adjusts parameters of synthetic applications to match the resource consumption profiles of target applications. By modifying synthetic application definitions to reflect different application behaviors (CPU-intensive, memory-intensive, I/O-intensive), the same assessment infrastructure can evaluate suitability for diverse application types without increasing structural complexity.
Data Source
AI summary
In accordance with the teachings of the present disclosure, a method of assessment of hosting suitability of multiple applications in a cloud is disclosed. The method may include defining, in a first synthetic application definition, a first plurality of resource consumptions, wherein the first plurality of resource consumptions are equivalent to consumptions by a first candidate application, and defining, in a second synthetic application definition, a second plurality of resource consumptions, wherein the second plurality of resource consumptions are equivalent to consumptions by a second candidate application. The method may also include consuming quantities of resources of pluralities of nodes of the computing system, recording performances of the synthetic, and evaluating the computing system based upon the recorded performances. The present disclosure additionally includes associated systems and apparatuses.