Program Resource Allocation Order for Load Threshold Scaling
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Solution Overview
Problem
Existing auto-scalar systems fail to efficiently balance resource allocation to optimize performance and cost in computing environments, often leading to increased expenses and reduced performance for other programs due to inefficient scaling of resource types.
Innovation Solution
A multi-dimensional auto-scalar system adjusts resource allocations based on program load thresholds, changing the order of adjustments depending on whether the load exceeds or is less than the threshold, optimizing resource usage by prioritizing cost-effective scaling of processing, memory, and instance quantities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resource allocation is increased to improve program performance, then program performance is improved, but operational costs increase
Solution Approach 1:
The system dynamically adjusts resource allocation by changing the order in which resource types are scaled based on real-time program load conditions. When program load exceeds the threshold, processing resources are scaled first; when below the threshold, memory resources are scaled first. This dynamic adaptation optimizes the balance between performance and cost.
Solution Approach 2:
The invention changes the parameter of resource allocation order based on program load conditions. By modifying the sequence in which resource types are allocated (processing resources vs. memory resources), the system optimizes cost efficiency while maintaining performance, rather than using a fixed allocation approach.
2Productivity
If resource allocation is increased to improve program performance, then program performance is improved, but performance of other programs deteriorates
Solution Approach 1:
The system dynamically adjusts resource allocation strategies based on real-time program load conditions. By changing the order of resource scaling (processing resources first when load is high, memory resources first when load is low), the system optimizes performance for the target program while minimizing impact on other concurrently running programs.
Solution Approach 2:
The invention applies different resource allocation strategies to different resource types based on local conditions. Instead of uniformly scaling all resources, the system selectively scales processing resources or memory resources depending on the specific program load conditions, optimizing the local quality of resource distribution.
Data Source
AI summary
In some examples, a system determines a program load of a program executing in a computing environment. The program load is determined based on a plurality of different usage parameters representing usage of different types of resources in the computing environment by the program, and based on respective resource allocation parameters representing allocations of the different types of resources. The system detects that the determined program load deviates from a load threshold for the program, and based on detecting that the determined program load deviates from the load threshold, adjusts a resource allocation parameter using an adjustment process that changes the resource allocation parameters in an order that depends upon whether the determined program load exceeds the load threshold or is less than the load threshold, wherein the adjusting of the resource allocation parameter modifies an allocation of a resource of the different types of resources to the program.