Event Triggered Data Collection Profiles
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Solution Overview
Problem
Existing data collection systems in data storage systems are often manually triggered, leading to untimely data collection and potential loss of valuable diagnostic information, especially when constraints such as size and system reboots are involved, making it difficult to store and impacting system performance.
Innovation Solution
Implementing a profile-based data collection method that automatically collects customized diagnostic data in response to predefined events, using predefined profiles that specify the data to be collected, including log files, system configuration, and runtime data, and execute specific commands to ensure timely and efficient data gathering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data collection is used, then system performance impact is reduced, but data collection timeliness deteriorates and diagnostic information may be lost
Solution Approach 1:
The system performs preliminary configuration of data collection profiles and event mappings before events occur. When events happen, the pre-configured profiles enable immediate automated data collection without requiring manual intervention, thus improving timeliness while the system is optimized to minimize performance impact during collection
Solution Approach 2:
The system enables self-service automated data collection that triggers automatically in response to events without manual intervention. The event monitoring component detects events and automatically initiates data collection based on configured profiles, eliminating the need for manual triggering while maintaining system optimization
2Loss of information
If comprehensive diagnostic data is collected, then diagnostic information completeness is improved, but data storage requirements increase and storage issues arise
Solution Approach 1:
The system applies local quality by collecting different amounts and types of data based on the specific event type. Each profile is customized to collect only the relevant diagnostic information needed for that particular event, avoiding collection of unnecessary data. This ensures diagnostic completeness for each event while minimizing overall storage requirements through event-specific data selection
3Loss of time
If automated data collection is implemented, then data collection timeliness is improved, but system complexity increases
Solution Approach 1:
The system segments the data collection functionality into distinct modular components: event monitoring component, profile configuration component, and data collection component. Each component has a specific responsibility and can be independently configured and managed. This modular segmentation enables automated timely data collection while keeping system complexity manageable through clear separation of concerns
Data Source
AI summary
Described are techniques for processing event occurrence. A first notification may be received regarding a first occurrence of a first event. Responsive to receiving the first notification, first processing may be performed that includes mapping the first event to a first profile, and performing second processing using the first profile to collect first data regarding the first occurrence of the first event.