International business machines corporation (20240126526). Building Reliable and Fast Container Images simplified abstract

Building Reliable and Fast Container Images

Organization Name

international business machines corporation

Inventor(s)

Abhishek Malvankar of White Plains NY (US)

Alaa S. Youssef of Valhalla NY (US)

Chen Wang of Chappaqua NY (US)

Mariusz Sabath of Ridgefield CT (US)

Building Reliable and Fast Container Images - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240126526 titled 'Building Reliable and Fast Container Images

Simplified Explanation

The patent application describes mechanisms for improving the performance of container images by using machine learning models to classify image chunks and identify reasons for modification based on negative classifications.

• Trained machine learning models classify container image chunks based on performance characteristics.
• Negative classifications trigger identification of patterns in a knowledge base for modification reasons.
• Notification output specifies image chunks, classifications, and reasons for modification.

Potential Applications

The technology can be applied in software development, cloud computing, and DevOps for optimizing container image performance.

Problems Solved

1. Streamlining container image modification processes. 2. Enhancing container image performance based on machine learning insights.

Benefits

1. Improved efficiency in managing container images. 2. Enhanced performance of containerized applications. 3. Automated identification of areas for optimization.

Potential Commercial Applications

Optimizing containerized applications for cloud service providers. SEO Optimized Title: Commercial Applications of Container Image Performance Improvement Technology

Possible Prior Art

Prior art may include container image optimization tools and techniques, as well as machine learning applications in software development and performance enhancement.

Unanswered Questions

=== How does the technology handle real-time performance monitoring of container images? Answer: The article does not provide details on real-time monitoring capabilities of the technology.

=== What are the potential limitations or challenges in implementing this technology in large-scale containerized environments? Answer: The article does not address scalability issues or challenges in deploying the technology across extensive containerized systems.

Original Abstract Submitted

mechanisms are provided for improving performance of container images. container image chunks are generated from a container image file and input into one or more trained machine learning (ml) computer models, trained to classify container image chunks with regard to a plurality of container image performance characteristic classifications. for each container image chunk it is determined whether the a corresponding classification is negative, and in response to the classification being negative, an entry in a knowledge base having patterns of content matching content in the container image chunk is identified to determine one or more reasons for modification of the chunk specified in the entry. a notification output is generated specifying the container image chunks, their corresponding container image performance characteristic classifications, and the reasons for modification of the chunks.