Optimizing Database Audit Tool Performance
By streamlining packet capture, cutting Goroutine count, employing Sync.Pool for object reuse, and filtering empty packets, the database audit tool’s CPU usage dropped from six cores to one, object allocation fell 90%, packet processing halved, and data loss was reduced 60%, achieving near‑zero loss with minimal performance impact.
Database security audit is crucial for detecting attacks and optimizing performance. This article details the optimization of a database audit tool, focusing on reducing CPU consumption and data loss during high QPS scenarios. The solution involves several key improvements:
1. Data Collection Optimization : The tool uses gopacket for packet capture, which was optimized to reduce CPU usage. Performance tests showed that the bottleneck was not in gopacket, allowing further optimizations.
2. Worker Scheduling : The number of Goroutines was reduced from 20 to 5, and the polling interval was adjusted from 1ms to 5ms to balance performance and data integrity.
3. Memory Management : Sync.Pool was implemented to reuse objects, reducing GC pressure and object allocation. This cut object allocation by 90%.
4. Packet Filtering : Empty packets were filtered out using pcap rules, reducing unnecessary processing. This decreased packet processing by 50%.
The result was a 60% reduction in data loss and a drop in CPU usage from 6 cores to 1 core. The tool now achieves near-zero data loss with minimal performance impact.
Meituan Technology Team
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