Automated Software Backup via Usage Metadata Valuation
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Solution Overview
Problem
Current software backup and restoration procedures for Information Handling Systems (IHSs) are complex and error-prone, requiring users to manually identify and configure directories and files, leading to ineffective backups and resource wastage due to the inclusion of unnecessary files, especially in environments with varied and non-standard software applications and hardware configurations.
Innovation Solution
Implementing local monitors on IHSs to generate metadata on software application usage, which is processed by a remote analytics engine to determine the valuation of files and applications, allowing for automated identification of critical files for backup and selective reinstallation during restoration, thereby streamlining the backup and restoration processes without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If selective backup procedures are implemented to back up only specific files and directories, then storage space is conserved and backup efficiency is improved, but the complexity of configuration increases and error-proneness rises
Solution Approach 1:
The system automatically monitors file operations, generates metadata, determines file valuations, and configures backup procedures without user intervention. The backup system serves itself by autonomously identifying critical files and setting up appropriate backup configurations based on observed usage patterns.
Solution Approach 2:
The system performs preliminary monitoring of file operations and generates metadata before the actual backup configuration is needed. By advance analysis of file access patterns and valuation determination, the system prepares backup configurations proactively, eliminating the need for complex user configuration at backup time.
2Reliability
If manual configuration of backup procedures is required to identify directories and files, then backup selectivity is improved, but the ease of operation deteriorates and user error increases
Solution Approach 1:
The system automatically monitors file operations, generates metadata, determines file valuations, and configures backup procedures without user intervention. The backup system serves itself by autonomously identifying critical files and setting up appropriate backup configurations based on observed usage patterns.
Solution Approach 2:
The system continuously monitors file operations and uses this feedback to dynamically adjust backup configurations. By observing actual file access patterns and usage, the system refines its understanding of critical files and optimizes backup selections based on real-world behavior rather than static user input.
3Measurement precision
If automated file monitoring and valuation systems are implemented, then backup configuration complexity is reduced and accuracy is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The system segments the backup problem into distinct components: file operation monitoring, metadata generation, valuation determination, and backup configuration. Each component handles a specific aspect of the task, allowing complex functionality to be achieved through modular, specialized subsystems that can be independently optimized.
Solution Approach 2:
The system introduces metadata as an intermediary layer between file operations and backup decisions. Instead of directly analyzing raw file operations for backup configuration, the system first transforms operations into structured metadata, which then serves as the basis for valuation and backup decisions, simplifying the overall processing logic.
Data Source
AI summary
Embodiments provide the ability to configure software backup and restoration procedures on an IHS (Information Handling System) with minimal or no input from a user. Embodiments utilize local monitors on an IHS in order to generate metadata describing the use of software applications installed on the IHS. A remote analytics engine process the metadata received from multiple participating IHSs to generate inputs used by the restoration and backup procedures implemented by the IHS. The metadata generated by an IHS is used to determine valuations for the applications and files installed on the IHS. These valuations may then be utilized to identify files of significant value to the user, which may then be designated for backup by the backup procedures implemented by the IHS. The generated valuations may also be used to select the applications that should be reinstalled in order to restore the IHS to an approximated prior operating state.