18

I want to monitor memory usage of a process, and I want this data to be logged. Does such a tool exist?

8

I have written a script to do exactly this. It basically samples ps at specific intervals, to build up a profile of a particular process. The process can be launched by the monitoring tool itself, or it can be an independent process (specified by pid or command pattern).

11

Occasionally when the need arises I just do:

$ top -d 1 -b |grep <process> >>somefile

It's not an elegant solution, but gets the job done if you want the quick crude value to verify your hypothesis.

  • I think it is elegant in it's simplicity. You may want to do grep --line-buffered <process> >>somefile to force grep to output each line without buffering – Ott Toomet Oct 7 '17 at 21:04
6

sar (System Activity Reporter) from the sysstat package is your friend in case like these.

Another way would be monitoring combined with historical data, e.g. Munin, pnp4nagios, rrdtools, ...

  • 1
    but can sar be focussed on just one process? mostly it seems to monitor the system as a whole – xenoterracide Jan 13 '11 at 15:38
  • 2
    The pidstat command also from the sysstat package provides a fairly nice interface for reporting statistics on single process. – Steven D Jan 13 '11 at 22:21
  • @xenoterracide Steven D had the answer. I wasn't aware of this command before. – Christian Jan 14 '11 at 7:10
4

Besides the aforementioned sar, I'd recommend atop. It saves a binary log that you can peruse afterwards, and besides memory saves a lot of other information.

3

You could try Valgrind.

Valgrind is an instrumentation framework for building dynamic analysis tools. There are Valgrind tools that can automatically detect many memory management and threading bugs, and profile your programs in detail. You can also use Valgrind to build new tools.

The Valgrind distribution currently includes six production-quality tools: a memory error detector, two thread error detectors, a cache and branch-prediction profiler, a call-graph generating cache and branch-prediction profiler, and a heap profiler.

  • Whilst this may theoretically answer the question, it would be preferable to include the essential parts of the answer here, and provide the link for reference. – saji89 Jan 3 '13 at 8:36
  • This document massif explain in detail. – Shawn Xie Feb 7 '13 at 7:23
0

I like Sridhar's simple answer but I rolled my own before I tried his:

import json, psutil, datetime, time

with open('log.txt', 'w') as f:
  while True:
    json.dump((datetime.datetime.now().isoformat(),
               psutil.Process(7274).memory_info()._asdict()), f)
    f.write('\n')
    f.flush()
    time.sleep(1)

It's basically only useful if you want structured output. Change 7274 as appropriate. Also Python 3.5.something broke _asdict(), so use Python 2.

Output file looks like:

["2019-03-19T11:21:53.784670", {"rss": 220389376, "vms": 538984448, "shared": 15724544, "text": 303104, "lib": 0, "data": 221364224, "dirty": 0}]
["2019-03-19T11:21:54.786136", {"rss": 220438528, "vms": 539119616, "shared": 15724544, "text": 303104, "lib": 0, "data": 221499392, "dirty": 0}]
["2019-03-19T11:21:55.787555", {"rss": 220495872, "vms": 539119616, "shared": 15724544, "text": 303104, "lib": 0, "data": 221499392, "dirty": 0}]
["2019-03-19T11:21:56.788754", {"rss": 220528640, "vms": 539119616, "shared": 15724544, "text": 303104, "lib": 0, "data": 221499392, "dirty": 0}]

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