Automated Backup Recovery Log Anomaly Detection

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Solution Overview

Problem

Restoring complex IT systems from backups is challenging due to environmental discrepancies, incomplete backup procedures, and complex interdependencies, making disaster recovery time-consuming and costly, especially for smaller businesses.

Innovation Solution

A method involving creating a virtual environment to restore systems, comparing logs to identify anomalies, and iteratively modifying the configuration to resolve issues, ensuring correct system startup and interdependencies, using a stored configuration to automate the process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If manual restoration and testing procedures are used, then flexibility and adaptability are maintained, but time consumption and operational complexity increase significantly

Engineering Contradiction:

Improveease of restorationVSAvoidrestoration time

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The system performs self-diagnosis by automatically comparing restored system logs against baseline logs to identify anomalies, and self-corrects by modifying configuration files to resolve detected issues, eliminating the need for manual intervention during disaster recovery operations

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Baseline logs are pre-collected from healthy system states and stored for future comparison. Configuration files are pre-prepared with known good settings, enabling rapid restoration by simply applying these pre-vetted resources during disaster recovery

Inventive Principle:

Principle #10Preliminary action

2Reliability

If frequent restoration testing is conducted to improve reliability, then system recovery success rate increases, but operational costs and time investment increase

Engineering Contradiction:

Improverecovery success rateVSAvoidtesting efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system automatically compares logs from restored systems against baseline logs to generate feedback on restoration quality. Anomalies detected in the comparison provide actionable feedback that guides configuration modifications, enabling continuous improvement of restoration procedures through iterative testing

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Instead of performing full system restoration tests, the system creates and analyzes log copies from restored systems. This lightweight copying approach enables frequent testing without the substantial time and resource costs of complete restoration cycles

Inventive Principle:

Principle #26Copying

3Measurement precision

If comprehensive log comparison and automatic configuration modification are implemented, then restoration accuracy and fault detection capability improve, but system complexity and computational requirements increase

Engineering Contradiction:

Improvefault detection accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The log comparison process is segmented into discrete anomaly detection steps, each focusing on specific log patterns or error types. Configuration modifications are segmented into targeted changes based on detected anomalies, rather than comprehensive reconfiguration, reducing overall system complexity while maintaining detection accuracy

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS11782800B2Methods to automatically correct and improve system recovery and replication processes

Publication Date: 2023.10.10 CRISTIE SOFTWARE LTD

AI summary

A backup recovery and testing method is disclosed. The recovery method restores backed-up systems according to a stored configuration, and collects logs as the restored systems start up. The collected logs are compared with stored baseline logs, by a process which includes parsing the logs into templates and parameters, and identifying anomalies automatically for example by principal component analysis. Anomalies identified may be used to modify the stored configuration.