Adobe Inc.
Auto-scaling cloud-based computing clusters dynamically using multiple scaling decision makers

Last updated:

Abstract:

Systems, methods, and non-transitory computer-readable media are disclosed for determining an accurate and efficient auto-scaling action for a cloud-based computing cluster based on multiple proposed auto-scaling actions from multiple scaling models. For example, the disclosed systems can determine an auto-scaling action to perform on a cloud-based computing cluster by weighing multiple proposed auto-scaling actions from multiple scaling models based on confidence scores associated with the proposed auto-scaling actions. Moreover, the disclosed systems can modify the cloud-based computing cluster using the determined auto-scaling action (e.g., to accurately and efficiently provision computing resources for a cloud-based computing system).

Status:
Grant
Type:

Utility

Filling date:

9 Oct 2019

Issue date:

23 Nov 2021