Dynamic Trace Filtering for Debugging Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional distributed storage systems face challenges in managing and filtering large volumes of trace data, leading to inefficiencies in debugging and data preservation, as they lack dynamic trace filtering capabilities, resulting in the discard of critical information and increased storage needs.
Innovation Solution
A dynamic trace filtering system that filters and preserves critical trace information in real-time within a distributed storage system by using a trace filter system to identify and store relevant trace chunks based on predefined keys, allowing for on-demand preservation and recycling of trace data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If dynamic trace filtering is implemented, then storage requirements are reduced and debugging efficiency is enhanced, but device complexity increases
Solution Approach 1:
A trace filter system is introduced as an intermediary component between the trace buffer and the storage system. This filter receives trace chunks from the trace buffer, evaluates them against predefined keys, and selectively passes relevant traces to storage while discarding irrelevant ones. The intermediary approach resolves the contradiction by centralizing filtering logic in a dedicated system that reduces storage requirements and improves debugging efficiency without requiring complex modifications to the entire distributed storage system.
Solution Approach 2:
The patent extracts only the essential trace information by filtering out irrelevant trace data before storage. The trace filter system identifies and extracts trace chunks that match predefined keys, separating critical debugging information from redundant data. This extraction principle reduces storage requirements and enhances debugging efficiency by ensuring only relevant traces are preserved, while the filtering mechanism itself is implemented as a manageable component rather than a system-wide complexity.
2Reliability
If trace data is stored without filtering, then all trace information is preserved, but storage requirements increase and critical information may be discarded
Solution Approach 1:
The trace filter system performs preliminary filtering action on trace data before it is stored in the trace buffer. By evaluating trace chunks against predefined keys in advance, the system ensures that only relevant traces are preserved, preventing storage of unnecessary data while maintaining reliability of critical information. This preliminary action resolves the contradiction by establishing filtering criteria before storage occurs, ensuring data preservation reliability without requiring excessive storage capacity.
Solution Approach 2:
The patent applies local quality by treating different trace data differently based on its relevance. The trace filter system evaluates each trace chunk individually against predefined keys, applying selective preservation only to traces that match the criteria. This localized filtering approach ensures that critical information is preserved while unnecessary data is discarded, resolving the contradiction between data preservation reliability and storage requirements by applying quality differentiation at the trace level rather than uniformly across all data.
Data Source
AI summary
An apparatus comprises at least one processing device that includes a processor coupled to a memory. The processing device is configured to receive, by a trace filter system, a trace chunk from a trace buffer associated with a processor core in a processing device, where the trace buffer is comprised of a plurality of trace chunks, to filter, by the trace filter system, the trace chunk, and to store the filtered trace chunk in the trace buffer.