Database Backup Frequency Management via Configuration File Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Identifying and ensuring a minimum backup frequency for all databases used directly or indirectly by a specified application is challenging due to their physical and administrative dispersion across distinct sites and platforms, leading to potential data inconsistencies and outdated backups.
Innovation Solution
A system and method that uses a programmed computer processor to query configuration files, identify dependent databases, and determine their backup frequencies, generating notifications or adjustments to ensure that all databases are backed up at least as frequently as the minimum required by the primary application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual identification of databases is used, then the system complexity is reduced, but the completeness of database backup coverage deteriorates
Solution Approach 1:
The system performs self-identification of databases by automatically querying configuration files and tracing application dependencies. The processor autonomously discovers which databases are directly or indirectly used by the application without requiring manual input, thereby maintaining low operational complexity while achieving complete backup coverage.
Solution Approach 2:
The system queries configuration files to obtain feedback information about application dependencies and database relationships. By continuously gathering information from configuration files and tracing the feedback loop of application queries, the system automatically identifies all relevant databases that need to be backed up.
2Reliability
If automated identification of all dependent databases is implemented, then the backup coverage completeness is improved, but the system complexity increases
Solution Approach 1:
The system segments the database identification process into distinct phases: first querying configuration files for direct dependencies, then tracing indirect dependencies through application queries. This segmentation allows the complex task of identifying all databases to be broken down into manageable steps, reducing overall system complexity while maintaining completeness.
Solution Approach 2:
The system performs preliminary actions by querying configuration files before executing the main backup process. By pre-identifying all databases that need to be backed up through configuration file analysis and dependency tracing, the system prepares the complete database list in advance, simplifying the subsequent backup execution.
3Ease of operation
If backup frequency is not monitored, then the operational simplicity is maintained, but the data consistency deteriorates
Solution Approach 1:
The system implements automatic monitoring of backup frequencies by querying configuration files and comparing actual backup frequencies against required frequencies. This feedback mechanism ensures data consistency without requiring manual intervention, maintaining operational simplicity while preventing outdated backups.
Solution Approach 2:
The system performs self-monitoring of backup frequencies and automatically generates notifications when databases are not backed up sufficiently. By autonomously tracking and reporting backup status, the system maintains data consistency without adding operational complexity for users.
4Ease of operation
If manual database identification is used, then the ease of operation is improved, but the backup frequency adequacy deteriorates
Solution Approach 1:
The system autonomously identifies databases and determines their backup frequency requirements by querying configuration files and tracing application dependencies. This self-service capability eliminates the need for manual identification while ensuring that all databases are backed up at adequate frequencies, maintaining ease of operation without sacrificing backup adequacy.
Data Source
AI summary
A method and associated systems for backing up a target computer application that comprises identifying and backing up databases and other information repositories upon which the target application depends. The target application is identified and related to a backup requirement that specifies a minimum application-backup frequency. The application's “dependencies” are automatically identified from sources that include configuration files, where each dependency identifies one or more databases or other information repositories that store information upon which the application directly or indirectly depends. If any of these databases or repositories is associated with a backup frequency less than the application's minimum backup frequency, the database or repository is flagged. Each flagged entity's backup schedule is then revised so that the flagged entity's backup frequency is equal to or greater than the application's minimum backup frequency.