2024-09-01
vmstat
displays various system statistics, categorized into many key areas. Understanding these categories is essential to effectively using the command. A typical output looks like this (the exact columns may vary slightly depending on your system):
procs -----------memory---------- ---swap-- -----io---- -system-- ------cpu-----
r b swpd free buff cache si so bi bo in cs us sy id wa st
0 0 0 1017364 12368 167332 0 0 2 4 156 270 1 0 99 0 0
Let’s break down some of the most important columns:
The simplest way to use vmstat
is to run it without any arguments:
vmstat
This will display a single line of statistics representing the current system state. To get a more detailed view, specify an interval and count:
vmstat 2 5
This command will display statistics every 2 seconds for 5 iterations (10 seconds total). This allows you to observe trends in system performance over time.
Let’s say you suspect your database server is experiencing performance issues. You can use vmstat
to monitor resource utilization for a longer period:
vmstat 5 30
This command outputs statistics every 5 seconds over a 150-second period. Look at the wa
(I/O wait) and b
(blocked processes) values – high values indicate I/O bottlenecks which might point to database performance issues.
Suppose you want to analyze the system’s response to a resource-intensive operation. You can run vmstat
before, during, and after the operation to compare the values:
vmstat 1 3
(collect baseline data)vmstat 1 10
(Monitor resource use during the task)vmstat 1 3
(Check for recovery)By comparing the vmstat
outputs from these three stages, you can pinpoint the impact of your task on CPU usage, memory usage, I/O, and other metrics.
While vmstat
displays a wealth of information, you can focus on specific metrics using the -s
option (for summary statistics):
vmstat -s
This shows cumulative statistics since boot, useful for long-term analysis.
By mastering vmstat
, you gain a powerful tool for understanding and optimizing your Linux system’s performance. Remember that interpreting the output requires context and understanding of your specific workload. Continuous monitoring and analysis are key to identifying and resolving performance bottlenecks effectively.