Container Data Consolidation via Access Command Interception
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Solution Overview
Problem
In computing systems, the high number of containers updating files leads to intense storage usage, causing storage shortages and performance issues due to the replication of shared data, which is not effectively managed by existing Single-Instance Storage techniques.
Innovation Solution
A method is introduced where access commands from containers are intercepted to determine candidate groups with common private data, which are then consolidated into shared data based on relevance policies, reducing data replication and storage usage while maintaining flexibility and dynamicity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If containers replicate private data in their own filesystems, then each container maintains data isolation and access speed, but storage space is wasted due to redundant data replication across multiple containers
Solution Approach 1:
The patent merges private data from multiple containers into a single shared data structure when the same data is detected in multiple containers. The consolidation module combines identical private data files from different containers into one shared copy, eliminating redundant storage while maintaining data accessibility for all containers that need it.
Solution Approach 2:
The shared data structure serves multiple containers simultaneously, making the storage system universal. Instead of dedicating separate storage space for the same data in each container, the shared data structure provides data to multiple containers through a single instance, achieving multi-functionality in data storage.
2Quantity of substance
If Single-Instance Storage techniques are used to consolidate data, then storage space is optimized, but the dynamicity and flexibility of container-specific data access is lost
Solution Approach 1:
The patent implements dynamic data sharing where the same private data can be shared among multiple containers when needed and unshared when container-specific modifications are required. The system dynamically adjusts the sharing state based on container operations, maintaining both storage efficiency and data access flexibility.
Solution Approach 2:
The patent segments data into private data that can potentially be shared and container-specific modifications. By separating the base private data from container-specific changes, the system can consolidate the common portions while preserving the ability for individual containers to have customized versions when needed.
3Quantity of substance
If private data is consolidated into shared data, then redundant data replication is eliminated and storage usage is reduced, but data access patterns must be managed across multiple containers
Solution Approach 1:
The patent introduces a consolidation module as an intermediary between containers and their private data. This module automatically detects when private data should be shared, consolidates it into the shared data structure, and manages access for multiple containers. The intermediary handles the complexity of data access management, making the process transparent to individual containers.
Data Source
AI summary
A solution is proposed for managing containers isolating corresponding application environments from one or more shared operating systems in a computing system. One or more relevant groups are determined among one or more candidate groups (each comprising private data in common among a plurality of the containers); the candidate groups are determined according to corresponding access commands submitted by the containers and the relevant groups are determined according to one or more relevance policies. The private data of the relevant groups are consolidated into corresponding shared data.