18299260. GLOBAL VERTICAL AUTO-SCALING FOR APPLICATION CONTAINERS simplified abstract (International Business Machines Corporation)

GLOBAL VERTICAL AUTO-SCALING FOR APPLICATION CONTAINERS

Organization Name

International Business Machines Corporation

Inventor(s)

Lior Aronovich of Thornhill (CA)

GLOBAL VERTICAL AUTO-SCALING FOR APPLICATION CONTAINERS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18299260 titled 'GLOBAL VERTICAL AUTO-SCALING FOR APPLICATION CONTAINERS

Simplified Explanation: The patent application describes a computer-implemented method for global vertical auto-scaling for processing units. This method involves learning functions based on resource consumption metrics, predicting resource consumption values, determining global priorities, and using these values for vertical auto-scaling of processing units.

Key Features and Innovation:

• Computer learns functions based on resource consumption metrics.
• Predicts maximal and minimal resource consumption values per resource for a processing unit.
• Determines global priority of the processing unit.
• Calculates prioritized predicted consumption values per resource based on global priority.
• Uses prioritized predicted consumption values for vertical auto-scaling of processing units.

Potential Applications: This technology can be applied in cloud computing environments, data centers, and any system requiring efficient resource management and auto-scaling capabilities.

Problems Solved: This technology addresses the challenges of efficiently managing resources and auto-scaling processing units based on predicted consumption values.

Benefits:

• Improved resource utilization and efficiency.
• Enhanced scalability and performance of processing units.
• Automated resource management for optimal system operation.

Commercial Applications: The technology can be utilized in cloud service providers, large-scale data centers, and enterprises with dynamic computing needs to optimize resource allocation and performance.

Prior Art: Prior art related to this technology may include research on auto-scaling algorithms, resource management in cloud computing, and predictive analytics for system optimization.

Frequently Updated Research: Researchers are constantly exploring new algorithms and techniques for efficient resource management and auto-scaling in dynamic computing environments.

Questions about Global Vertical Auto-Scaling for Processing Units: 1. How does the computer determine the global priority of a processing unit? 2. What are the potential implications of using prioritized predicted consumption values for vertical auto-scaling in cloud computing environments?

Original Abstract Submitted

A computer-implemented method, a computer program product, and a computer system for global vertical auto-scaling for processing units. A computer periodically learns one or more functions, based on resource consumption metrics samples of processing units. A computer uses the one or more functions to obtain a predicted maximal resource consumption value per resource and a predicted minimal resource consumption value per resource for a processing unit. A computer determines a global priority of the processing unit. A computer calculate a prioritized predicted consumption value per resource for the processing unit, based on the global priority, the predicted maximal resource consumption value, and the predicted minimal resource consumption value. A computer uses the prioritized predicted consumption value for vertical auto-scaling of the processing unit by a processing unit management system.