If your Linux server suddenly experiences a load surge and alarm text messages continue to flood into your mobile phone, how can you find the root cause of Linux performance problems in the shortest possible time? You may wish to refer to this blog post from the Netflix Performance Engineering Team to learn how they can quickly diagnose machine performance issues in one minute through ten commands.
By executing the following command, you can have a general understanding of the system resource usage within 1 minute.
Some of these commands require the sysstat package to be installed, and some are provided by the procps package. The output of these commands helps to quickly locate performance bottlenecks and check the utilization, saturation and error metrics of all resources (CPU, memory, disk IO, etc.), which is the so-called USE method.
Let’s introduce these commands one by one. For more parameters and instructions on these commands, please refer to the command manual.
uptime
$ uptime 23:51:26 up 21:31, 1 user, load average: 30.02, 26.43, 19.02
This command can quickly check the load status of the machine. In Linux systems, these data represent the number of processes waiting for CPU resources and blocked in uninterruptible IO processes (process status is D). This data can give us a macro understanding of system resource usage.
The output of thecommand indicates the average load conditions for 1 minute, 5 minutes, and 15 minutes respectively. Through these three data, you can understand whether the server load is becoming tight or easing in the area. If the 1-minute average load is very high and the 15-minute average load is very low, it means that the server is commanding a high load and you need to further investigate where the CPU resources are being consumed. On the other hand, if the 15-minute load average is high and the 1-minute load average is low, it is possible that the time when CPU resources are tight has passed.
The output in the above example shows that the average load in the last minute is very high and much higher than the load in the last 15 minutes. Therefore, we need to continue to investigate which processes in the current system consume a lot of resources. You can further investigate by using vmstat, mpstat and other commands that will be introduced below.
dmesg丨tail
$ dmesg | tail [1880957.563150] perl invoked oom-killer: gfp_mask=0x280da, order=0, oom_score_adj=0 [...] [1880957.563400] Out of memory: Kill process 18694 (perl) score 246 or sacrifice child [1880957.563408] Killed process 18694 (perl) total-vm:1972392kB, anon-rss:1953348kB, file-rss:0kB [2320864.954447] TCP: Possible SYN flooding on port 7001. Dropping request. Check SNMP counters.
This command will output the last 10 lines of the system log. In the output in the example, you can see a kernel oom kill and a TCP packet loss. These logs can help troubleshoot performance issues. Don't forget this step.
vmstat 1
$ vmstat 1 procs ---------memory---------- ---swap-- -----io---- -system-- ------cpu----- r b swpd free buff cache si so bi bo in cs us sy id wa st 34 0 0 200889792 73708 591828 0 0 0 5 6 10 96 1 3 0 0 32 0 0 200889920 73708 591860 0 0 0 592 13284 4282 98 1 1 0 0 32 0 0 200890112 73708 591860 0 0 0 0 9501 2154 99 1 0 0 0 32 0 0 200889568 73712 591856 0 0 0 48 11900 2459 99 0 0 0 0 32 0 0 200890208 73712 591860 0 0 0 0 15898 4840 98 1 1 0 0
vmstat(8) command, each line will output some core system indicators, which allow us to understand the system status in more detail. The following parameter 1 indicates that statistical information is output once per second. The header prompts the meaning of each column. These columns introduce some columns related to performance tuning:
The above CPU times allow us to quickly understand whether the CPU is busy. Generally, if the sum of user time and system time is very large, the CPU is busy executing instructions. If the IO wait time is long, the bottleneck of the system may be disk IO.
示例命令的输出可以看见,大量CPU时间消耗在用户态,也就是用户应用程序消耗了CPU时间。这不一定是性能问题,需要结合r队列,一起分析。
mpstat-P ALL 1
$ mpstat -P ALL 1 Linux 3.13.0-49-generic (titanclusters-xxxxx) 07/14/2015 _x86_64_ (32 CPU) 07:38:49 PM CPU %usr %nice %sys %iowait %irq %soft %steal %guest %gnice %idle 07:38:50 PM all 98.47 0.00 0.75 0.00 0.00 0.00 0.00 0.00 0.00 0.78 07:38:50 PM 0 96.04 0.00 2.97 0.00 0.00 0.00 0.00 0.00 0.00 0.99 07:38:50 PM 1 97.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 2.00 07:38:50 PM 2 98.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 07:38:50 PM 3 96.97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.03 [...]
该命令可以显示每个CPU的占用情况,如果有一个CPU占用率特别高,那么有可能是一个单线程应用程序引起的。
pidstat 1
$ pidstat 1 Linux 3.13.0-49-generic (titanclusters-xxxxx) 07/14/2015 _x86_64_ (32 CPU) 07:41:02 PM UID PID %usr %system %guest %CPU CPU Command 07:41:03 PM 0 9 0.00 0.94 0.00 0.94 1 rcuos/0 07:41:03 PM 0 4214 5.66 5.66 0.00 11.32 15 mesos-slave 07:41:03 PM 0 4354 0.94 0.94 0.00 1.89 8 java 07:41:03 PM 0 6521 1596.23 1.89 0.00 1598.11 27 java 07:41:03 PM 0 6564 1571.70 7.55 0.00 1579.25 28 java 07:41:03 PM 60004 60154 0.94 4.72 0.00 5.66 9 pidstat 07:41:03 PM UID PID %usr %system %guest %CPU CPU Command 07:41:04 PM 0 4214 6.00 2.00 0.00 8.00 15 mesos-slave 07:41:04 PM 0 6521 1590.00 1.00 0.00 1591.00 27 java07:41:04 PM 0 6564 1573.00 10.00 0.00 1583.00 28 java 07:41:04 PM 108 6718 1.00 0.00 0.00 1.00 0 snmp-pass 07:41:04 PM 60004 60154 1.00 4.00 0.00 5.00 9 pidstat
pidstat命令输出进程的CPU占用率,该命令会持续输出,并且不会覆盖之前的数据,可以方便观察系统动态。如上的输出,可以看见两个JAVA进程占用了将近1600%的CPU时间,既消耗了大约16个CPU核心的运算资源。
iostat-xz 1
$ iostat -xz 1 Linux 3.13.0-49-generic (titanclusters-xxxxx) 07/14/2015 _x86_64_ (32 CPU) avg-cpu: %user %nice %system %iowait %steal %idle 73.96 0.00 3.73 0.03 0.06 22.21 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await r_await w_await svctm %util xvda 0.00 0.23 0.21 0.18 4.52 2.08 34.37 0.00 9.98 13.80 5.42 2.44 0.09 xvdb 0.01 0.00 1.02 8.94 127.97 598.53 145.79 0.00 0.43 1.78 0.28 0.25 0.25 xvdc 0.01 0.00 1.02 8.86 127.79 595.94 146.50 0.00 0.45 1.82 0.30 0.27 0.26 dm-0 0.00 0.00 0.69 2.32 10.47 31.69 28.01 0.01 3.23 0.71 3.98 0.13 0.04 dm-1 0.00 0.00 0.00 0.94 0.01 3.78 8.00 0.33 345.84 0.04 346.81 0.01 0.00 dm-2 0.00 0.00 0.09 0.07 1.35 0.36 22.50 0.00 2.55 0.23 5.62 1.78 0.03 [...]
iostat命令主要用于查看机器磁盘IO情况。该命令输出的列,主要含义是:
如果显示的是逻辑设备的数据,那么设备利用率不代表后端实际的硬件设备已经饱和。值得注意的是,即使IO性能不理想,也不一定意味这应用程序性能会不好,可以利用诸如预读取、写缓存等策略提升应用性能。
free -m
$ free -m total used free shared buffers cached Mem: 245998 24545 221453 83 59 541 -/+ buffers/cache: 23944 222053 Swap: 0 0 0
free命令可以查看系统内存的使用情况,-m参数表示按照兆字节展示。最后两列分别表示用于IO缓存的内存数,和用于文件系统页缓存的内存数。需要注意的是,第二行-/+ buffers/cache,看上去缓存占用了大量内存空间。这是Linux系统的内存使用策略,尽可能的利用内存,如果应用程序需要内存,这部分内存会立即被回收并分配给应用程序。因此,这部分内存一般也被当成是可用内存。
如果可用内存非常少,系统可能会动用交换区(如果配置了的话),这样会增加IO开销(可以在iostat命令中提现),降低系统性能。
sar -n DEV 1
$ sar -n DEV 1 Linux 3.13.0-49-generic (titanclusters-xxxxx) 07/14/2015 _x86_64_ (32 CPU) 12:16:48 AM IFACE rxpck/s txpck/s rxkB/s txkB/s rxcmp/s txcmp/s rxmcst/s %ifutil 12:16:49 AM eth0 18763.00 5032.00 20686.42 478.30 0.00 0.00 0.00 0.00 12:16:49 AM lo 14.00 14.00 1.36 1.36 0.00 0.00 0.00 0.00 12:16:49 AM docker0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 12:16:49 AM IFACE rxpck/s txpck/s rxkB/s txkB/s rxcmp/s txcmp/s rxmcst/s %ifutil 12:16:50 AM eth0 19763.00 5101.00 21999.10 482.56 0.00 0.00 0.00 0.00 12:16:50 AM lo 20.00 20.00 3.25 3.25 0.00 0.00 0.00 0.00 12:16:50 AM docker0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
sar命令在这里可以查看网络设备的吞吐率。在排查性能问题时,可以通过网络设备的吞吐量,判断网络设备是否已经饱和。如示例输出中,eth0网卡设备,吞吐率大概在22 Mbytes/s,既176 Mbits/sec,没有达到1Gbit/sec的硬件上限。
sar -n TCP,ETCP 1
$ sar -n TCP,ETCP 1 Linux 3.13.0-49-generic (titanclusters-xxxxx) 07/14/2015 _x86_64_ (32 CPU) 12:17:19 AM active/s passive/s iseg/s oseg/s 12:17:20 AM 1.00 0.00 10233.00 18846.00 12:17:19 AM atmptf/s estres/s retrans/s isegerr/s orsts/s 12:17:20 AM 0.00 0.00 0.00 0.00 0.00 12:17:20 AM active/s passive/s iseg/s oseg/s 12:17:21 AM 1.00 0.00 8359.00 6039.00 12:17:20 AM atmptf/s estres/s retrans/s isegerr/s orsts/s 12:17:21 AM 0.00 0.00 0.00 0.00 0.00
sar命令在这里用于查看TCP连接状态,其中包括:
TCP连接数可以用来判断性能问题是否由于建立了过多的连接,进一步可以判断是主动发起的连接,还是被动接受的连接。TCP重传可能是因为网络环境恶劣,或者服务器压力过大导致丢包。
top
$ top top - 00:15:40 up 21:56, 1 user, load average: 31.09, 29.87, 29.92 Tasks: 871 total, 1 running, 868 sleeping, 0 stopped, 2 zombie %Cpu(s): 96.8 us, 0.4 sy, 0.0 ni, 2.7 id, 0.1 wa, 0.0 hi, 0.0 si, 0.0 st KiB Mem: 25190241+total, 24921688 used, 22698073+free, 60448 buffers KiB Swap: 0 total, 0 used, 0 free. 554208 cached Mem PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 20248 root 20 0 0.227t 0.012t 18748 S 3090 5.2 29812:58 java 4213 root 20 0 2722544 64640 44232 S 23.5 0.0 233:35.37 mesos-slave 66128 titancl+ 20 0 24344 2332 1172 R 1.0 0.0 0:00.07 top 5235 root 20 0 38.227g 547004 49996 S 0.7 0.2 2:02.74 java 4299 root 20 0 20.015g 2.682g 16836 S 0.3 1.1 33:14.42 java 1 root 20 0 33620 2920 1496 S 0.0 0.0 0:03.82 init 2 root 20 0 0 0 0 S 0.0 0.0 0:00.02 kthreadd 3 root 20 0 0 0 0 S 0.0 0.0 0:05.35 ksoftirqd/0 5 root 0 -20 0 0 0 S 0.0 0.0 0:00.00 kworker/0:0H 6 root 20 0 0 0 0 S 0.0 0.0 0:06.94 kworker/u256:0 8 root 20 0 0 0 0 S 0.0 0.0 2:38.05 rcu_sched
top命令包含了前面好几个命令的检查的内容。比如系统负载情况(uptime)、系统内存使用情况(free)、系统CPU使用情况(vmstat)等。因此通过这个命令,可以相对全面的查看系统负载的来源。同时,top命令支持排序,可以按照不同的列排序,方便查找出诸如内存占用最多的进程、CPU占用率最高的进程等。
但是,top命令相对于前面一些命令,输出是一个瞬间值,如果不持续盯着,可能会错过一些线索。这时可能需要暂停top命令刷新,来记录和比对数据。
总 结
排查Linux服务器性能问题还有很多工具,上面介绍的一些命令,可以帮助我们快速的定位问题。例如前面的示例输出,多个证据证明有JAVA进程占用了大量CPU资源,之后的性能调优就可以针对应用程序进行。
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