Container-Based Software Update for Multi-Version Systems
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Solution Overview
Problem
Managing software updates across multiple active versions of a software artifact is challenging, especially in ABAP-based systems, where customers have flexibility in upgrading, leading to different users being on different versions.
Innovation Solution
A software update process that utilizes previously generated builds of multiple software versions within a containerized environment, allowing updates from the newest version to be integrated into previous versions, tested, and deployed iteratively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple versions of software are maintained in the productive environment, then customer flexibility and choice are improved, but the complexity of distributing updates to each version increases
Solution Approach 1:
A container-based intermediary environment is introduced between the development environment and the productive environment. This container serves as a mediator that hosts a specific version of the software artifact, allowing updates to be tested in isolation before being distributed to multiple productive environments. The container encapsulates the software artifact with its dependencies, creating a portable update package that can be consistently deployed across different versions without requiring separate update processes for each version.
Solution Approach 2:
The update is preliminarily tested in a containerized environment before being distributed to the productive environment. The process involves: (1) generating a container image with the updated software artifact in the development environment, (2) exporting and importing the container to a productive environment for testing, (3) verifying the update works correctly, and (4) then distributing it. This preliminary action in the container eliminates the need to manually test and distribute updates to each version separately.
2Reliability
If updates are tested in the productive environment, then real-world validation is improved, but the risk of affecting live systems increases
Solution Approach 1:
The container acts as an intermediary testing environment that mimics the productive environment while isolating the update from live systems. The container can be exported to the productive environment for testing, but it runs in an isolated namespace with its own file system and process space. This allows real-world validation of the update without directly affecting live customer systems, as the container encapsulates the software artifact and its dependencies in a controlled environment.
Solution Approach 2:
The software artifact is copied into a container image that can be exported and imported to different environments. The container creates a portable copy of the software with all its dependencies, allowing the same update to be tested in the productive environment without modifying the original live systems. The container image serves as a safe copy that can be deployed for testing and rolled back if necessary.
3Productivity
If container-based updating is implemented, then update efficiency and consistency are improved, but the learning curve and initial setup complexity increase
Solution Approach 1:
The container technology provides a universal platform that serves multiple functions: (1) as a development environment for creating software artifacts, (2) as a testing environment for validating updates, and (3) as a deployment vehicle for distributing updates. The same container image can be used across different versions and environments, eliminating the need for separate update processes for each version. This multi-functionality improves update efficiency despite the initial learning curve.
Solution Approach 2:
The system changes the state parameter of the software artifact from being version-specific to being container-encapsulated. By packaging the software artifact with its dependencies in a standardized container format, the update process becomes version-agnostic. The container image serves as a universal update package that can be deployed to multiple versions, transforming the update distribution process from a complex multi-version task to a standardized deployment operation.
Data Source
AI summary
Provided are systems and methods that facilitate the upgrade of multiple versions of a software application within a containerized environment. In one example, the method may include importing a software update of a software application into a prior version of the software application in a containerized environment, executing a test of the prior version of the software application with the software update included therein via the containerized environment and display results of the execution of the test via a user interface, modifying the prior version of the software application with the software update included therein while the prior version of the software application with the software update included therein is within the containerized environment, and delivering an instance of the modified prior version of the software application from the containerized environment to a productive environment.