Hybrid Computing Scaling With Workload-Based Request Verification
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Solution Overview
Problem
Hybrid computing systems face inefficiencies in resource management, leading to wasted resources and application slowdowns due to unverified scaling requests, particularly in core cloud platforms with limited capacity.
Innovation Solution
A system and method that utilizes a server controller to obtain workload information, a predictor to determine scaling decisions based on this information, and a request controller to manage resource allocation across computing systems, ensuring efficient scaling based on actual workload demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If core cloud platforms accept scaling requests without verification, then the system responds quickly to scaling demands, but resources are wasted and applications may slow down or stop due to exceeded capacity
Solution Approach 1:
The patent applies preliminary action by verifying scaling requests against current workload and capacity before executing the scaling operation. The system proactively checks whether the core cloud platform can handle additional load or resource reduction, preventing resource wastage and application slowdowns before they occur, rather than reacting after the problem manifests.
2Productivity
If core cloud platforms accept scaling requests without verification, then scaling operations are performed immediately, but applications may slow down and finally stop due to resource exhaustion
Solution Approach 1:
The patent implements feedback by continuously monitoring the workload and capacity status of the core cloud platform, then using this information to verify scaling requests. The system feedback loop ensures that scaling operations only proceed when the platform has sufficient capacity, maintaining both productivity and application availability by preventing resource exhaustion.
3Device complexity
If traditional hybrid computing system management is used, then system simplicity is maintained, but resource management inefficiency occurs leading to wasted resources and application performance degradation
Solution Approach 1:
The patent introduces an intermediary verification mechanism between the scaling request and the core cloud platform. This intermediary layer checks workload information and capacity status before allowing scaling operations, improving resource management efficiency without significantly increasing overall system complexity by using a focused verification approach rather than complete system redesign.
Data Source
AI summary
A method, a system and a computer program product for hybrid computing system management are proposed. In the method, workload information associated with a set of application server instances running in a first computing system is obtained by a server controller in response to a scaling request for changing the number of instances in the set of application server instances from a request controller. The set of application server instances serves at least one application running in a second computing system. A scaling decision indicating whether to change the number of instances in the set of application server instances is determined by a predictor based on the workload information from the server controller. The second computing system is enabled by the request controller to handle requests associated with the at least one application for the set of application server instances based on the scaling decision.