nagplug

Nagios guidelines-compliant monitoring plugin creation library (Shinken, Icinga, Centreon)


Keywords
nagios, plugin, shinken, icinga, centreon, monitoring
License
MIT
Install
pip install nagplug==1.1

Documentation

Nagplug Build Status GitHub release PyPI License: MIT

A library to easily write Monitoring Plugins compliant with the monitoring plugins guidelines using python.

This library was designed to be similar to Perl Monitoring::Plugin library.

Plugin Documentation

You can access embedded plugin documentation using pydoc

$ pydoc nagplug

Also, the example.py file gives a pretty good example of a simple plugin.

The nagplug library manages almost all the life of the plugin program, from argument parsing to timeouts, exception handling, output formatting.

Using the library

First, create an instance of a Plugin

>>> from nagplug import Plugin, OK, WARNING, CRITICAL, UNKNOWN
>>> plugin = Plugin()

Then, you can add some arguments to parse from the command-line. (Note that unless you use add_stdargs=False when calling Plugin(), some default standard arguments will be added (--hostname, --timeout, --verbose and --version). --help is added by the underlying argparse module.)

>>> plugin.add_arg('--max', required=True, type=int) # doctest: +ELLIPSIS
_StoreAction(...)
>>> plugin.add_arg('--value', required=True, type=int) # doctest: +ELLIPSIS
_StoreAction(...)
>>> args = plugin.parse_args('--max 3 --value 6'.split())
>>> print(args.max)
3
>>> print(args.value)
6

Any argument you can pass to argparse.ArgumentParser.add_argument can also be passed to nagplug.Plugin.add_arg. See the argparse documentation to see how it works and all the nice things you can do.

If you need to do advanced parsing, you can access the internal parser using the parser attribute of the plugin.

>>> # if you want to add subparsers, for example.
>>> sp = plugin.parser.add_subparsers()

For safety reasons, you might want your test to stop after a certain amount of time, considering that it failed. By default it will use the value of args.timeout set by the --timeout argument.

>>> print(args.timeout)
30
>>> plugin.set_timeout()

Now let's say that you want to check if value is inferior to max, returning an OK status if it's the case and critical if its is not. You do the check, then add the result to the plugin. At anytime, you can get the current plugin status via the get_code() method.

>>> if args.value <= args.max:
...     plugin.add_result(OK, 'All Good !')
... else:
...     plugin.add_result(CRITICAL, 'Dammit !')
>>> plugin.get_code() == CRITICAL
True
>>> plugin.get_message()
'Dammit !'

You can add any number of results, the plugin will return the worst recorded status:

>>> plugin.add_result(OK, 'But... Other test worked !')
>>> plugin.get_code() == CRITICAL
True

When you're done, exit the plugin and return the final result by calling the finish method:

>>> plugin.finish() # doctest: +SKIP

Checking values against Thresholds

Thresholds are useful for the user to express more complex value ranges from the command line. The syntax is described in the threshold format specification.

The check_threshold function makes it easy to check values against thresholds. It returns the code corresponding to the worst threshold matched.

>>> from nagplug import Threshold
>>> warn_t = Threshold(':90')
>>> crit_t = Threshold(':95')
>>> plugin.check_threshold(56, warning=warn_t, critical=crit_t) == OK
True
>>> plugin.check_threshold(93, warning=warn_t, critical=crit_t) == WARNING
True
>>> plugin.check_threshold(97, warning=warn_t, critical=crit_t) == CRITICAL
True

Perfdata and Extended Data

Some monitoring systems can also do graphing. These system use the performance data emitted by your plugin.

The add_perfdata method will make sure everything is well-formatted. You must give at least a label and a value, but you can also add an unit of measurement, minimum and maximum bounds, and thresholds.

>>> plugin.add_perfdata('percent_used', 20, uom='%', minimum=0, maximum=100)
>>> plugin.add_perfdata('age_of_the_captain', 87)
>>> print(plugin.get_perfdata())
'percent_used'=20%;;;0;100 'age_of_the_captain'=87;;;;

Extended data can help you by having more details in your output, while keeping the main status line short and clear.

>>> plugin.add_extdata('This will be logged in the output')
>>> plugin.add_extdata('This will also be logged')
>>> print(plugin.get_extdata())
This will be logged in the output
This will also be logged