Database Rollout Manager for Regression Mitigation
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Solution Overview
Problem
The process of rolling out database changes is often time-consuming, error-prone, and requires manual intervention, leading to increased overhead and potential discrepancies in database system behavior.
Innovation Solution
The implementation of a Database Changes Rollout Manager (DCRM) that automates the rollout process, utilizing an infrastructure layer to manage and configure automated steps such as monitoring, regression detection, root cause analysis, and rollback decisions, thereby reducing manual effort and enhancing safety and standardization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used for database changes, then flexibility and control are maintained, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system enables self-service automation where the database change management system automatically performs monitoring, regression detection, root cause analysis, and rollback decisions without requiring manual intervention at each step, thereby reducing errors while maintaining efficiency
Solution Approach 2:
The system implements continuous feedback loops through automated monitoring and regression detection mechanisms that provide real-time information about database change outcomes, enabling automatic corrective actions and reducing both errors and deployment time
2Productivity
If automated rollout is implemented, then deployment speed increases, but system complexity increases
Solution Approach 1:
The database change management system performs multiple functions including monitoring, regression detection, root cause analysis, and rollback decision-making within a single automated framework, increasing deployment speed while managing complexity through functional integration
Solution Approach 2:
The system introduces an automated change management intermediary layer that mediates between database changes and the production environment, handling complexity internally while presenting a simplified interface for deployment acceleration
3Measurement precision
If multiple stored procedures are used for regression testing, then regression detection accuracy improves, but processing overhead increases
Solution Approach 1:
The system segments regression testing into multiple specialized stored procedures, each handling specific aspects of regression detection, thereby improving detection accuracy while organizing processing overhead into manageable, targeted operations
Data Source
AI summary
A method includes updating, by at least one hardware processor, a table with a detected regression associated with database code of a database. A first stored procedure is performed to determine a root cause of the detected regression. A second stored procedure is performed to determine an impact of the detected regression based at least on the root cause. A determination is made on whether to perform mitigation of the detected regression based on the impact.