Automated Crash Recovery via Feature Flag Isolation
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Solution Overview
Problem
Conventional crash reporting processes are slow, leading to prolonged downtime for user devices and negatively impacting application performance, revenue generation, and user satisfaction, as they require remote analysis and update deployment.
Innovation Solution
Implementing an automated crash recovery mechanism that identifies and disables the faulty application feature locally using feature flags, allowing the application to recover without human intervention and reducing downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional crash reporting processes are used, then the application can be updated with crash fixes, but the process takes too much time causing prolonged downtime
Solution Approach 1:
The system performs preliminary actions by collecting crash information and environmental data before the crash fully impacts the user experience. The automated mechanism prepares crash reports and analyzes causes in the background, enabling faster response and reducing the actual downtime when fixes need to be deployed.
Solution Approach 2:
The system implements self-service through automated crash detection, reporting, and analysis mechanisms that operate without human intervention. The automated crash recovery mechanism independently identifies crashes, collects relevant data, determines causes, and triggers appropriate responses, eliminating the need for manual monitoring and reducing response time.
2Measurement precision
If manual crash analysis and update deployment are used, then the cause of crash can be determined accurately, but the process requires human intervention and takes too long
Solution Approach 1:
The system implements feedback mechanisms where crash information and environmental data are continuously collected, analyzed, and used to automatically determine crash causes. The automated mechanism processes crash reports, compares them against known issues, and provides feedback that enables rapid identification of crash causes without manual intervention, maintaining accuracy while improving speed.
Solution Approach 2:
The system replaces the manual mechanical process of crash analysis with an automated electronic system. The automated crash recovery mechanism uses software-based analysis, data processing, and algorithmic determination of crash causes, substituting human analysts with automated computational processes that operate faster while maintaining or improving diagnostic accuracy.
3Productivity
If the application continues to run with known crash issues, then the application remains available to users, but the application keeps crashing and generating negative consequences
Solution Approach 1:
The system applies beforehand cushioning by implementing automated crash detection and response mechanisms that prepare for and mitigate crashes before they significantly impact the user experience. The system continuously monitors for crash conditions, collects data in advance, and has pre-prepared response protocols that cushion the impact of crashes and enable faster recovery, maintaining availability while improving stability.
Data Source
AI summary
Methods for improving operation of a user device executing an application. The methods include collecting a first set of data corresponding to a run time environment of the application, collecting a second set of data corresponding to a crash of the application, identifying a cause of the crash based on the first set of data and a second set of data and determining the cause of the crash is associated with an application feature corresponding to a feature flag.