18125229. Dynamic Container Resizing simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

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Dynamic Container Resizing

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

Jonathan D. Dunne of Dungarvan (IE)

Sahdevsinh P Zala of Cary NC (US)

Abhay Choudhary of Dublin (IE)

Eduardo Aguiar Patrocinio of Apex NC (US)

Karim Ladouari of Rathnew (IE)

Dynamic Container Resizing - A simplified explanation of the abstract

This abstract first appeared for US patent application 18125229 titled 'Dynamic Container Resizing

Simplified Explanation: This patent application involves using regression analysis on telemetry data from a container to predict resource usage, adjusting resource allocation based on future predictions.

  • Predicts resource usage of a container by analyzing telemetry data.
  • Adjusts resource allocation based on future resource usage predictions.
  • Utilizes regression analysis and time series analysis to make accurate predictions.
  • Extracts data from telemetry to identify features predicting resource usage.
  • Helps optimize resource allocation for containers running applications.

Key Features and Innovation: - Regression analysis on telemetry data to predict resource usage. - Time series analysis for future resource usage predictions. - Adjusting resource allocation based on predicted usage. - Extracting features from telemetry data to make accurate predictions. - Optimization of resource allocation for containers running applications.

Potential Applications: This technology can be applied in various industries such as cloud computing, data centers, and IoT devices to optimize resource allocation and improve efficiency.

Problems Solved: - Predicting resource usage of containers accurately. - Optimizing resource allocation based on future predictions. - Improving efficiency and performance of applications running in containers.

Benefits: - Cost savings through efficient resource allocation. - Improved performance of applications in containers. - Enhanced scalability and flexibility in resource management.

Commercial Applications: Optimizing resource allocation in cloud computing environments can lead to cost savings for businesses and improved performance for applications. This technology can also be valuable in data centers to ensure efficient resource usage.

Prior Art: Readers can explore prior research on regression analysis, time series analysis, and resource allocation in container environments to understand the existing knowledge in this field.

Frequently Updated Research: Stay updated on the latest advancements in regression analysis, time series analysis, and resource optimization in container environments to enhance the application of this technology.

Questions about Container Resource Allocation: 1. How does regression analysis help in predicting resource usage in containers? 2. What are the potential implications of adjusting resource allocation based on future predictions?


Original Abstract Submitted

Using a regression analysis on first telemetry data of a container, an embodiment identifies a set of features predicting a resource usage of the container. The container comprises an executing application. Using a time series analysis of data of the set of features, an embodiment predicts a future resource usage of the container at a future time. The data of the set of features is extracted from second telemetry data of the container. At the future time according to the future resource usage, an embodiment adjusts a size of a resource available to the container.

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