Automated Database Deployment Validation via Script Parsing
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Solution Overview
Problem
Existing database deployment validation techniques are time-consuming and lead to increased downtime of applications, as they require manual review of changes made to the target database.
Innovation Solution
An automated validation process that parses database scripts to identify object characteristics, generates validation scripts with queries based on these characteristics, and executes these scripts to validate changes made to the database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual validation of database changes is performed, then validation accuracy is improved, but validation time increases
Solution Approach 1:
The system performs self-validation by automatically generating validation scripts that examine database objects and their dependencies. The validation process serves itself by using the same database scripts that define the changes to automatically create the validation logic, eliminating the need for external manual validation while maintaining high accuracy.
Solution Approach 2:
The patent replaces the mechanical manual validation process with an automated computational system. Instead of human reviewers manually checking database changes, the system uses automated script generation and execution to validate database objects, substituting human cognitive work with algorithmic processing.
2Reliability
If comprehensive database validation is performed, then deployment reliability is improved, but application downtime increases
Solution Approach 1:
The system performs validation script generation in advance by parsing database scripts and creating validation logic before the actual deployment execution. This preliminary preparation allows the validation to be ready and efficient when deployment time arrives, reducing the overall downtime required.
Solution Approach 2:
The validation process runs continuously alongside the deployment process rather than as a separate sequential step. The automated generation and execution of validation scripts occurs in an integrated manner with the deployment workflow, maintaining continuous progress without idle waiting periods.
3Productivity
If automated validation script generation is implemented, then productivity is improved, but system complexity increases
Solution Approach 1:
The system uses universal database scripting languages and standardized validation query structures that can handle multiple types of database objects and changes. This multi-functionality allows a single automated validation framework to work across different database schemas and change types without requiring complex specialized handling for each case.
Solution Approach 2:
The system creates simplified copies of the database change logic in the form of validation scripts. By copying the essential structure and dependencies from the original database scripts into validation queries, the system achieves automated validation without needing to understand or replicate the full complexity of the database management system.
Data Source
AI summary
Methods, apparatus, and processor-readable storage media for automated validation of database deployments are provided herein. An example computer-implemented method includes obtaining database scripts to be executed on at least one database, wherein each database script is associated with one or more database objects; parsing respective ones of the database scripts to identify object information corresponding to the one or more database objects associated with the corresponding database script; automatically generating a validation script comprising one or more validation queries for respective ones of the one or more database objects associated with a corresponding one of the database scripts, wherein each validation query is based at least in part on the identified object information of the corresponding database object; and initiating an execution of the validation script to validate one or more changes of the at least one database resulting from an execution of the database scripts.