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Start or attach to a process and monitor a customizable set of metrics (CPU, I/O, etc.). New metrics can be added by simply providing shell commands. The generated output uses a easily parsable tabular format, which can be used out of the box with tools like R.


Monitor the first 100 seconds of Google Chrome that from cold-start fires up and load a web site:

trace -d -mcpu_load_perc -mres_mem_kb -mread_b -mwrite_b -- run google-chrome

now using a simple R script it is possible to obtain a plot like this one:


Attach to a running instance of cp to monitor the amount of bytes read/written:

trace -d -mread_b -mwrite_b -- attach $(pidof cp)

Trace the RAM usage of an executable along with the system time:

trace -d -x 'time:date +%H:%M:%S ' -mres_mem_kb -- run ./something

Check the CPU load and disk writes of gzip compressing a 100M file:

trace -d -mwrite_b -mcpu_load_perc -- run gzip a-big-file | column -t

this for example could produce an output similar to:

ms    write_b    cpu_load_perc
1     69632      11.0
1024  20094976   56.5
2046  40226816   71.3
3068  60059648   79.0
4090  80150528   83.4
5113  100286464  86.3


wget -qO- | bash

Or manually put and wherever you want and symlink the former to just trace in one of your $PATH directories.

Or just run it from where it is with ./ The only requirement is that if you want to use the default metrics group, the file must be in the same directory as

(Same applies for


The full usage message is shown with the -h option.

trace [<options>] -- run <program> [<arguments>]
trace [<options>] -- attach <pid>
trace [<options>] -- list

<options> can be a combination of:

    -h                : show this message
    -d                : load the default group
    -g <group>        : group file to load
    -m <metric>       : metric to use
    -x <label>:<code> : custom shell snippet to execute in which the
                        variable $pid is defined to be the PID of the
                        process being traced; the first word of the argument
                        is the label and it will be shown as a column header
    -s <separator>    : column separator (defaults to tab)
    -i <interval>     : seconds between two consecutive measures (defaults to 1s)


The output produced is tab-separated values by default, though the field separator can be specified with the -s option. This format is particular suitable to be parsed by tools like R, for example using the read.table function:

trace <- read.table('trace.tsv',header=T)

For human consumption it is also possible to pipe the output through the column -t command to determine the proper length of the columns and thus get a prettified version of the table.

Note that when using the run command the program output is redirected to stderr so that measures are sent to stdout.


Groups are shell scripts that contain user defined functions (metrics) and can be loaded only when needed via the -g option. Most of the time the default group will be just enough hence there is a shortcut option -d that takes care of loading it.

For a list of all the available metrics in the included group files use the list command, for example to list the ones in the default group:

trace -d -- list

In case you need to write your own custom group file you can use the default group as a baseline. Of course you should avoid naming conflicts when dealing with multiple files.


Metrics are lightweight shell functions that dump precisely one value for the PID being traced in the current time instance, for example the CPU load. Metrics are specified with the -m option and each one eventually corresponds to a column in the output. -m must specify the name of the function to use and such function must be present in a previously included group file via the -g or -d options. The column label is the function name. For example:

trace -d -mread_b -- run dd if=my-file of=/dev/null

There is another kind of metrics (-x option) that allows to quickly specify a custom column without having to provide a whole custom group file. The accepted format is <label>:<code>. In this case the column label is the one provided. For example:

trace -x 'file_count:ls | wc -l' -- run ./something


Start or attach to a process and monitor a customizable set of metrics (CPU, I/O, etc.)







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