Container Image Building via Local Content Extraction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing container image build processes are time-consuming and prone to errors due to the need for multiple downloads of large images from central repositories, leading to resource inefficiencies and suboptimal customization for specific use cases.
Innovation Solution
The method involves extracting and combining specific content from existing container images to create new container images, using atomic actions like 'first', 'rest', 'subtract', 'intersect', and 'merge' to reduce reliance on central repository downloads, thereby improving system memory utilization and customization efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If container images are downloaded from central repositories, then container images can be obtained for use, but the process is time-consuming and resource-inefficient
Solution Approach 1:
The patent extracts specific content from existing container images stored in system memory to create new container images, rather than downloading complete images from central repositories. This extraction approach selectively retrieves only the necessary components locally, significantly reducing download time and improving productivity.
Solution Approach 2:
The patent performs preliminary actions by storing container images and their content in system memory in advance. This allows the system to quickly access and extract required content without needing to download from external repositories during the container building process, thereby reducing time loss.
2Quantity of substance
If complete container images are downloaded, then all necessary content is available, but system memory utilization is inefficient
Solution Approach 1:
The system extracts only the specific content needed from container images and stores it in system memory, rather than loading entire container images. This selective extraction ensures that all necessary content is available while optimizing memory usage efficiency by avoiding storage of unnecessary data.
Solution Approach 2:
The patent segments container image content into distinct components and extracts only the required segments for building new container images. This segmentation approach allows the system to maintain content availability while improving memory utilization by storing only essential portions.
3Adaptability or versatility
If multiple container images are downloaded for customization, then diverse content is available, but resource consumption increases
Solution Approach 1:
The system extracts specific content from existing container images to create customized new container images, rather than downloading multiple complete images. This extraction method maintains diverse customization capability while reducing resource consumption by retrieving only the necessary content locally.
Solution Approach 2:
The patent combines content from multiple sources including extracted container image content, local files, and other inputs to create customized container images. This merging approach enables diverse customization while avoiding the need to download and store multiple complete container images, thereby reducing resource consumption.
Data Source
AI summary
Methods, computer program products, and systems are presented. The method, computer program products, and systems can include, for instance: obtaining configuration data that specifies a designated runtime container image; selecting a first subset of content of a first container image stored in a system memory, the selecting based on an action referenced in the configuration data; extracting the first subset of content from the first container image, the extracting including providing a second container image that includes the first subset of content of the first container image and is absent of a second subset of content of the first container image; and running the designated runtime container image to provide a runtime container, the designated runtime container image having the first subset of content of the first container image.