Automated Software Release Pipeline Dependency Tracking
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Solution Overview
Problem
Conventional software release and deployment models are error-prone, inefficient, and time-consuming due to manual efforts and disconnections between teams, leading to inaccuracies and delays in software application deployment.
Innovation Solution
An integrated platform for continuous deployment of software application delivery models that automates the release and deployment process by tracking and moving software applications through a pipeline, using data structures and machine learning techniques to identify dependencies and propagate releases efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual efforts are used for release management and team coordination, then flexibility and adaptability are maintained, but error rate increases and productivity decreases
Solution Approach 1:
The system enables self-service automation where the release management system automatically tracks releases, determines dependencies, and notifies teams without manual intervention. The system serves itself by autonomously managing the release pipeline, reducing human error while maintaining operational flexibility through configurable workflows.
Solution Approach 2:
Manual mechanical processes of release tracking and coordination are replaced with an automated digital system. The patent substitutes human-manual tracking with automated tracking records, replaces manual dependency analysis with algorithmic determination, and substitutes manual notifications with automated communication systems, thereby reducing errors while maintaining adaptability.
2Productivity
If manual tracking and coordination of releases across teams is performed, then information accuracy can be maintained through human review, but time consumption increases and productivity decreases
Solution Approach 1:
The system performs preliminary automated tracking of releases as they progress through the pipeline, determining dependencies and preparing notifications in advance. By proactively monitoring and pre-processing release information, the system eliminates time-consuming manual review steps while maintaining accuracy through automated validation rules.
Solution Approach 2:
The automated release tracking system operates continuously without interruption, constantly monitoring release progress and updating tracking records in real-time. This continuous automated operation eliminates the downtime and delays inherent in manual batch processing, accelerating deployment speed while maintaining information accuracy through persistent monitoring.
3Productivity
If disconnections between teams and tools are maintained for independence, then team autonomy is preserved, but information aggregation becomes difficult and productivity decreases
Solution Approach 1:
The release management system provides universal functionality that works across multiple teams and tools through standardized interfaces. The system aggregates information from diverse sources using common tracking records and dependency determination algorithms, enabling efficient release management across the organization without requiring complex custom integrations for each team.
Solution Approach 2:
The patent introduces an intermediary release management system that acts as a mediator between independent teams and their various tools. This intermediary layer standardizes communication protocols and data formats, allowing information aggregation from disparate sources without requiring direct complex integrations between all teams and tools, thereby simplifying the overall system architecture.
4Measurement precision
If manual identification of affected software portions is performed, then accuracy of impact analysis can be maintained, but time consumption increases and productivity decreases
Solution Approach 1:
The system performs preliminary automated analysis of software portions affected by releases by examining tracking records and dependency information in advance. This pre-computation of impact analysis eliminates the need for time-consuming manual identification during release coordination, while maintaining accuracy through systematic algorithmic analysis of the software architecture and dependency relationships.
Data Source
AI summary
Various aspects described herein are directed to a method or system that automates the release and deployment of a software application delivery model for the continuous release and deployment of the software application delivery model. These techniques identify a release and pertinent information thereof for a software application delivery model and determine dependencies among at least some of the pertinent information. Tracking records may be generated at least by tracking the release based in part or in whole upon the dependencies. The release or a portion of the release may be advanced from a current stage to a next stage along a release pipeline based in part or in whole upon the tracking records.