Automated Progressive Software Update Rollout
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Solution Overview
Problem
Software updates in computing systems require significant manual effort, leading to lengthy and often problematic rollout processes due to the need for manual analysis and correction of issues, which can take several days to complete.
Innovation Solution
A progressive rollout method is implemented, allowing users to create multiple phases for software updates, where a portion of users receive the update based on configurable criteria, with automatic approval phases determining key performance indicator satisfaction and update effectiveness, enabling automated rollout and review without administrator intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual rollout and analysis methods are used, then administrators can control and verify each update, but the update process takes many days to complete and requires considerable manual work
Solution Approach 1:
The patent segments the update rollout process into multiple phases (e.g., 10%, 25%, 50%, 100% rollout stages) with automated verification at each phase. This allows systematic progression while reducing manual intervention time, resolving the contradiction between reliable verification and fast completion.
Solution Approach 2:
The system implements automated feedback loops where update performance is continuously monitored and analyzed by machines. Success criteria are automatically evaluated at each rollout phase, enabling rapid decision-making without manual analysis, thus reducing update completion time while maintaining verification reliability.
2Measurement precision
If manual analysis and correction of update issues are performed, then update problems can be identified and corrected, but each update takes many days to complete
Solution Approach 1:
The patent replaces manual mechanical analysis with automated machine-based monitoring and analysis systems. These systems continuously collect performance data, automatically detect issues, and trigger rollback procedures when success criteria are not met, eliminating manual analysis delays while maintaining precise issue detection.
Solution Approach 2:
The system performs preliminary automated analysis and validation before full deployment. By pre-configuring success criteria and automated monitoring rules, the system can quickly identify and respond to issues without waiting for manual analysis, thus improving update deployment speed while maintaining detection precision.
3Productivity
If automated progressive rollout is implemented, then update deployment speed increases and manual work is reduced, but the system complexity increases with multiple phases and approval rules
Solution Approach 1:
The patent implements a universal automated rollout system that handles multiple update scenarios, phases, and verification criteria through a single integrated platform. This multi-functional system manages complex phased rollouts, automated monitoring, and rollback procedures uniformly, reducing the perceived complexity while maintaining high deployment efficiency.
Solution Approach 2:
The system manages complexity by parameterizing rollout configurations (e.g., phase percentages, success criteria thresholds, timing parameters). Administrators can control the complex automated process by simply adjusting parameters rather than designing entire workflows, thus improving deployment efficiency while making the system easier to manage.
4Stability of the object's composition
If progressive phases with increasing user portions are used, then risk is reduced and update stability is improved, but the rollout process requires multiple stages increasing process complexity
Solution Approach 1:
The patent divides the rollout process into segmented phases (e.g., 10%, 25%, 50%, 100%) where each phase automatically verifies stability before proceeding. This segmentation provides structured stability verification while the automation reduces the complexity of managing multiple phases, resolving the contradiction between update stability and process complexity.
Data Source
AI summary
The present system automatically allows a user to create a pipeline for performing a progressive rollout and automatically performs the rollout in progressive steps. As part of creating a pipeline, a user creates multiple rollout phases and multiple approval phases. At each rollout phase, a portion of users using the current version of a software receive a rollout or update. The types of users may be configured based on user attributes. The approval phase for each rollout may determine if the software at the customer location is satisfying certain key performance indicator (KPI) requirements and whether the software update is correcting what it was intended to address. The present technology may automatically apply the updates, automatically review the performance of the updated application, and automatically approve the rollout to move onto the next phase, all without any administrator decisions.