cpu飙高排查思路

### CPU Usage Spike Troubleshooting Methods When encountering a situation where CPU usage spikes, several systematic approaches can be employed to diagnose and resolve the issue. The methodologies encompass monitoring tools utilization, log analysis, performance counters review, and specific commands execution depending on the environment. For environments using certain network testing utilities, one might use `generic_send_tcp` with parameters such as `<Target IP> <Target Port>` alongside scripts like `spike_script`, which could help simulate traffic or test responses that may lead to understanding what triggers high CPU conditions[^1]. However, this approach is more about generating load rather than directly diagnosing issues unless used in controlled scenarios for benchmarking or stress-testing applications suspected of causing spikes. In database-related contexts, analyzing bottlenecks involves examining operations' timing within systems. Tools designed specifically for database management provide insights into how long queries take, helping identify inefficient processes consuming excessive resources over time[^3]. Commands issued in High Availability Disaster Recovery (HADR) setups offer insight into system configurations but are not direct means for troubleshooting CPU spikes. Commands related to HADR setup focus on ensuring replication between primary and secondary servers through socket buffer sizes adjustment and disk settings configuration[^2], which indirectly contribute by optimizing overall server efficiency potentially reducing unnecessary loads leading to CPU peaks. To effectively troubleshoot CPU spikes: - Utilize operating system built-in monitors or third-party software capable of providing real-time statistics. - Review application logs along with any available stack traces during periods when CPUs were overloaded. - Examine process lists identifying resource-intensive tasks running at times corresponding to increased activity levels. - Adjust scheduling policies if preemptive multitasking causes context switching overhead contributing significantly towards higher consumption rates. ```bash top -b -n 1 | head -n 12 ``` This command provides an overview of current top processes sorted by their CPU usage percentage allowing administrators to pinpoint problematic services quickly.