Container Repository Dependency Graph for Compatible Multi-App Updates
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Solution Overview
Problem
Existing multi-software application deployment systems face challenges in efficiently managing interdependencies between applications, leading to inefficiencies and errors during updates due to incompatibilities, as developers struggle to identify and update interdependent applications correctly.
Innovation Solution
A method and system for multi-application deployment that utilizes a dependency graph to automatically determine and update interdependent container repositories based on commands, ensuring compatibility by performing actions on image layers of dependent repositories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual update process is used for container repositories, then developers have control over each update, but time consumption and error rate increase due to difficulty in identifying interdependent applications
Solution Approach 1:
A dependency graph is introduced as an intermediary data structure to represent and manage interdependencies between container repositories. The graph stores nodes representing repositories and edges representing dependency relationships, enabling automated identification of interdependent applications without manual intervention while ensuring update compatibility.
Solution Approach 2:
The system performs self-service by automatically traversing the dependency graph to identify all interdependent container repositories when an update is initiated. The dependency determination module autonomously determines which repositories need updating based on the graph structure, eliminating the need for developers to manually track dependencies.
2Productivity
If automated dependency tracking is implemented, then update efficiency improves, but system complexity increases due to dependency graph management
Solution Approach 1:
The system is segmented into distinct functional modules: a dependency graph construction module that builds the dependency structure, a dependency determination module that queries the graph, and an update execution module that applies changes. This modular segmentation manages system complexity by separating concerns while maintaining high deployment efficiency through automated workflows.
Data Source
AI summary
Techniques according to the present disclosure may include receiving, at a computer, a command for performing an action on a first image layer of a first container repository. A second container repository is determined which has a dependency on the first container repository, based on a dependency graph storing dependencies of a plurality of container repositories. The action is performed on the first image layer of the first container repository and a corresponding action on a second image layer of the second container repository based on the command.