Automated Roll-Forward for Software Package Version Recovery
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Solution Overview
Problem
In computer networks, when software packages experience failures or errors, administrators face challenges in quickly identifying and rectifying issues, often requiring manual analysis and deployment of new software versions, which can lead to prolonged downtime and inefficiencies.
Innovation Solution
A method involving a roll-forward process using a set of APIs within a version control system to detect failures, extract and clone previous software package versions, import changes, commit them to generate a new version, and deploy it automatically, thereby minimizing downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual analysis and deployment of new software versions is performed, then software failures can be rectified, but downtime is prolonged and operational efficiency decreases
Solution Approach 1:
The system performs preliminary actions by automatically detecting software failures and initiating the roll-forward process without waiting for manual intervention. The version control system pre-identifies stable previous versions and automatically retrieves them, enabling immediate rectification of failures and minimizing downtime.
Solution Approach 2:
The system enables self-service by automating the entire software failure rectification process. The version control system automatically detects failures, identifies suitable previous versions, retrieves them, and deploys them without requiring administrator intervention, thereby significantly reducing downtime and improving operational efficiency.
2Ease of operation
If manual analysis and deployment processes are used, then software changes can be made, but operational efficiency and productivity are reduced
Solution Approach 1:
The system enables self-service by automating the entire software failure rectification process. The version control system automatically detects failures, identifies suitable previous versions, retrieves them, and deploys them without requiring administrator intervention, thereby significantly reducing downtime and improving operational efficiency.
Solution Approach 2:
The system replaces manual mechanical operations with automated computational processes. Instead of administrators manually analyzing failures and deploying updates, the version control system uses automated detection algorithms and API-driven processes to identify, retrieve, and deploy stable software versions, dramatically improving deployment efficiency.
3Extent of automation
If a roll-forward process with multiple API operations is implemented, then automated generation of new software versions is achieved, but device complexity increases
Solution Approach 1:
The system merges multiple discrete operations into a unified roll-forward process. By combining failure detection, version identification, data extraction, repository cloning, change import, and deployment into a single automated workflow, the system achieves high automation while managing complexity through integration rather than separate manual steps.
Solution Approach 2:
The version control system performs multiple functions through a single unified process. The same system detects failures, identifies stable versions, extracts software data, clones repositories, imports changes, and deploys updates, eliminating the need for separate specialized tools and reducing overall system complexity despite the multi-step process.
Data Source
AI summary
In order to facilitate automatic roll-forward updates, embodiments include detecting a failure in a software package. In response to the failure, data indicative of a current version of a software package is extracted from a release directory. In response to the application data, a base repository with a version history of the application is cloned. In response to the cloning, a prior set of changes from the base repository in the temporary directory, where the prior set of changes form an old application version of the application, is imported. In response to the import of the prior set of changes, the current version is overwritten with the prior set of changes to generate a new version. The new version is pushed directly to the base repository and a deployment API causes the new version to replace the current version.