Diagnostic Data Package Assembly for Error Recovery
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Solution Overview
Problem
Current computing systems face challenges in quickly diagnosing and resolving user-reported issues due to insufficient information, leading to trial and error processes between users and support personnel, and often require cumbersome administrative intervention.
Innovation Solution
A computing system that receives a diagnostic data package from a client, runs a problem-specific analyzer to generate additional data, identifies the root cause of the issue, and determines if the recovery action can be performed by an end user or an administrative user, with controlled communication to ensure appropriate intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If general log information is collected every time a user encounters an error condition, then more diagnostic data is available, but the volume of information increases making it harder to quickly identify root causes
Solution Approach 1:
The system extracts and collects only the specific diagnostic data relevant to the encountered error condition rather than collecting all general log information. The diagnostic data package is selectively assembled from logs and other sources based on the specific error type, reducing information volume while maintaining diagnostic effectiveness.
Solution Approach 2:
The system prepares and transmits the diagnostic data package automatically when an error is detected, before support personnel need to analyze the issue. This preliminary action includes running problem-specific analyzers and assembling relevant data, so that when support receives the issue, the information is already organized and ready for rapid analysis.
2Loss of information
If support engineers ask users to download and run data collection tools, then comprehensive data can be collected, but the time required for data collection increases significantly
Solution Approach 1:
The data collection process is performed automatically in advance when the error occurs, before support engagement begins. The system runs problem-specific analyzers and assembles the diagnostic data package immediately, eliminating the need for users to manually install and execute tools later.
Solution Approach 2:
The system performs self-diagnosis by automatically detecting the error condition, running appropriate analyzers, and assembling the diagnostic data package without requiring user intervention. This self-service approach replaces the manual process where users must download and execute data collection tools requested by support engineers.
3Ease of operation
If users navigate through help or troubleshooting flows to address problems themselves, then some issues can be resolved independently, but the time and effort required increases before any solution can be found
Solution Approach 1:
The system provides automated feedback by analyzing the diagnostic data and generating a response that identifies the root cause and suggests recovery actions. This automated feedback loop eliminates the need for users to manually navigate troubleshooting flows, as the system itself performs the diagnosis and communicates the solution path.
4Reliability
If administrative users are involved in remediating errors, then issues requiring system-level changes can be fixed, but the process becomes cumbersome and confusing for end users
Solution Approach 1:
The system acts as an intermediary between the end user and the administrative user. It collects the user's error report, runs diagnostic analyses, determines the root cause, identifies whether administrative intervention is needed, and communicates the appropriate recovery actions. This intermediary function shields end users from the complexity of administrative processes while ensuring reliable error resolution.
Data Source
AI summary
A computing system in a server environment receives a diagnostic data package, corresponding to a problem, from a client computing system and runs a problem-specific analyzer to generate additional problem-specific data. A root cause for the problem is identified along with a recovery action, based on the diagnostic data package and the additional problem-specific data. The recovery action indicates whether it can be performed by an end user or an administrative user. Communication with the end user and administrative user is controlled based on the recovery action.