Ganglia监控系统是UC Berkeley开源的一个项目，设计初衷就是要做好分布式集群的监控，监控层面包括资源层面和业务层面，资源层面包括cpu、memory、disk、IO、网络负载等，至于业务层面由于用户可以很方便的增加自定义的metric，因此可以用于做诸如服务性能、负载、出错率等的监控，例如某web服务的QPS、Http status错误率。此外，如果和Nagios集成起来还可以在某指标超过一定阈值时触发相应的报警。
Ganglia相比zabbix的优势在于客户端收集agent（gmond）所带来的系统开销非常低，不会影响相关服务的性能。
ganglia主要有几个模块：
关于ganglia的安装本文不做过多介绍，传送门：http://www.it165.net/admin/html/201302/770.html
本文主要介绍一下如何开发自定义的metric，方便监控自己关心的指标。
主要有几大类的方法：
1. 直接使用gmetric
安装gmond的机器，会同时安装上/usr/bin/gmetric，该命令是将一个metric的name
value等信息进行广播的工具，例如
/usr/bin/gmetric -c /etc/ganglia/gmond.conf --name=test --type=int32 --units=sec --value=2
具体gmetric的选项见：http://manpages.ubuntu.com/manpages/hardy/man1/gmetric.1.html
2. 使用基于gmetric的第三方工具此外，除了直接命令行使用gmetric外，还可以使用常见语言的binding，例如go、Java、python等，github上都有相关的binding可以使用，只需要import进来即可。 go语言 https://github.com/ganglia/ganglia_contrib/tree/master/ganglia-go
ruby https://github.com/igrigorik/gmetric/blob/master/lib/gmetric.rb
Java https://github.com/ganglia/ganglia_contrib/tree/master/gmetric-java
Python https://github.com/ganglia/ganglia_contrib/tree/master/gmetric-python
本文以ganglia-logtailer举例： https://github.com/ganglia/ganglia_contrib/tree/master/ganglia-logtailer
该工具基于logtail(debain)/logcheck(centos) package, 实现对日志的定时tail，然后通过指定classname来使用相应的类进行日志的分析，
根据自己关注的字段统计出自定义metric，并由gmetric广播出来。
例如我们根据自己服务的nginx日志格式，修改NginxLogtailer.py如下：
# -*- coding: utf-8 -*-
###
### This plugin for logtailer will crunch nginx logs and produce these metrics:
### * hits per second
### * GETs per second
### * average query processing time
### * ninetieth percentile query processing time
### * number of HTTP 200, 300, 400, and 500 responses per second
###
### Note that this plugin depends on a certain nginx log format, documented in
## __init__.
import time
import threading
import re
# local dependencies
from ganglia_logtailer_helper import GangliaMetricObject
from ganglia_logtailer_helper import LogtailerParsingException, LogtailerStateException
class NginxLogtailer(object):
# only used in daemon mode
period = 30
def __init__(self):
'''This function should initialize any data structures or variables
needed for the internal state of the line parser.'''
self.reset_state()
self.lock = threading.RLock()
# this is what will match the nginx lines
#log_format ganglia-logtailer
# '$host '
# '$server_addr '
# '$remote_addr '
# '- '
# '"$time_iso8601" '
# '$status '
# '$body_bytes_sent '
# '$request_time '
# '"$http_referer" '
# '"$request" '
# '"$http_user_agent" '
# '$pid';
# NOTE: nginx 0.7 doesn't support $time_iso8601, use $time_local
# instead
# original apache log format string:
# %v %A %a %u %{%Y-%m-%dT%H:%M:%S}t %c %s %>s %B %D \"%{Referer}i\" \"%r\" \"%{User-Agent}i\" %P
# host.com 127.0.0.1 127.0.0.1 - "2008-05-08T07:34:44" - 200 200 371 103918 - "-" "GET /path HTTP/1.0" "-" 23794
# match keys: server_name, local_ip, remote_ip, date, status, size,
# req_time, referrer, request, user_agent, pid
self.reg = re.compile('^(?P<remote_ip>[^ ]+) (?P<server_name>[^ ]+) (?P<hit>[^ ]+) \[(?P<date>[^\]]+)\] "(?P<request>[^"]+)" (?P<status>[^ ]+) (?P<size>[^ ]+) "(?P<referrer>[^"]+)" "(?P<user_agent>[^"]+)" "(?P<forward_to>[^"]+)" "(?P<req_time>[^"]+)"')
# assume we're in daemon mode unless set_check_duration gets called
self.dur_override = False
# example function for parse line
# takes one argument (text) line to be parsed
# returns nothing
def parse_line(self, line):
'''This function should digest the contents of one line at a time,
updating the internal state variables.'''
self.lock.acquire()
try:
regMatch = self.reg.match(line)
if regMatch:
linebits = regMatch.groupdict()
if '-' == linebits['request'] or 'file2get' in linebits['request']:
self.lock.release()
return
self.num_hits+=1
# capture GETs
if( 'GET' in linebits['request'] ):
self.num_gets+=1
# capture HTTP response code
rescode = float(linebits['status'])
if( (rescode >= 200) and (rescode < 300) ):
self.num_two+=1
elif( (rescode >= 300) and (rescode < 400) ):
self.num_three+=1
elif( (rescode >= 400) and (rescode < 500) ):
self.num_four+=1
elif( (rescode >= 500) and (rescode < 600) ):
self.num_five+=1
# capture request duration
dur = float(linebits['req_time'])
self.req_time += dur
# store for 90th % calculation
self.ninetieth.append(dur)
else:
raise LogtailerParsingException, "regmatch failed to match"
except Exception, e:
self.lock.release()
raise LogtailerParsingException, "regmatch or contents failed with %s" % e
self.lock.release()
# example function for deep copy
# takes no arguments
# returns one object
def deep_copy(self):
'''This function should return a copy of the data structure used to
maintain state. This copy should different from the object that is
currently being modified so that the other thread can deal with it
without fear of it changing out from under it. The format of this
object is internal to the plugin.'''
myret = dict( num_hits=self.num_hits,
num_gets=self.num_gets,
req_time=self.req_time,
num_two=self.num_two,
num_three=self.num_three,
num_four=self.num_four,
num_five=self.num_five,
ninetieth=self.ninetieth
)
return myret
# example function for reset_state
# takes no arguments
# returns nothing
def reset_state(self):
'''This function resets the internal data structure to 0 (saving
whatever state it needs). This function should be called
immediately after deep copy with a lock in place so the internal
data structures can't be modified in between the two calls. If the
time between calls to get_state is necessary to calculate metrics,
reset_state should store now() each time it's called, and get_state
will use the time since that now() to do its calculations'''
self.num_hits = 0
self.num_gets = 0
self.req_time = 0
self.num_two = 0
self.num_three = 0
self.num_four = 0
self.num_five = 0
self.ninetieth = list()
self.last_reset_time = time.time()
# example for keeping track of runtimes
# takes no arguments
# returns float number of seconds for this run
def set_check_duration(self, dur):
'''This function only used if logtailer is in cron mode. If it is
invoked, get_check_duration should use this value instead of calculating
it.'''
self.duration = dur
self.dur_override = True
def get_check_duration(self):
'''This function should return the time since the last check. If called
from cron mode, this must be set using set_check_duration(). If in
daemon mode, it should be calculated internally.'''
if( self.dur_override ):
duration = self.duration
else:
cur_time = time.time()
duration = cur_time - self.last_reset_time
# the duration should be within 10% of period
acceptable_duration_min = self.period - (self.period / 10.0)
acceptable_duration_max = self.period + (self.period / 10.0)
if (duration < acceptable_duration_min or duration > acceptable_duration_max):
raise LogtailerStateException, "time calculation problem - duration (%s) > 10%% away from period (%s)" % (duration, self.period)
return duration
# example function for get_state
# takes no arguments
# returns a dictionary of (metric => metric_object) pairs
def get_state(self):
'''This function should acquire a lock, call deep copy, get the
current time if necessary, call reset_state, then do its
calculations. It should return a list of metric objects.'''
# get the data to work with
self.lock.acquire()
try:
mydata = self.deep_copy()
check_time = self.get_check_duration()
self.reset_state()
self.lock.release()
except LogtailerStateException, e:
# if something went wrong with deep_copy or the duration, reset and continue
self.reset_state()
self.lock.release()
raise e
# crunch data to how you want to report it
hits_per_second = mydata['num_hits'] / check_time
gets_per_second = mydata['num_gets'] / check_time
if (mydata['num_hits'] != 0):
avg_req_time = mydata['req_time'] / mydata['num_hits']
else:
avg_req_time = 0
two_per_second = mydata['num_two'] / check_time
three_per_second = mydata['num_three'] / check_time
four_per_second = mydata['num_four'] / check_time
five_per_second = mydata['num_five'] / check_time
# calculate 90th % request time
ninetieth_list = mydata['ninetieth']
ninetieth_list.sort()
num_entries = len(ninetieth_list)
if (num_entries != 0 ):
ninetieth_element = ninetieth_list[int(num_entries * 0.9)]
else:
ninetieth_element = 0
# package up the data you want to submit
hps_metric = GangliaMetricObject('nginx_hits', hits_per_second, units='hps')
gps_metric = GangliaMetricObject('nginx_gets', gets_per_second, units='hps')
avgdur_metric = GangliaMetricObject('nginx_avg_dur', avg_req_time, units='sec')
ninetieth_metric = GangliaMetricObject('nginx_90th_dur', ninetieth_element, units='sec')
twops_metric = GangliaMetricObject('nginx_200', two_per_second, units='hps')
threeps_metric = GangliaMetricObject('nginx_300', three_per_second, units='hps')
fourps_metric = GangliaMetricObject('nginx_400', four_per_second, units='hps')
fiveps_metric = GangliaMetricObject('nginx_500', five_per_second, units='hps')
# return a list of metric objects
return [ hps_metric, gps_metric, avgdur_metric, ninetieth_metric, twops_metric, threeps_metric, fourps_metric, fiveps_metric, ]在被监控机器上部署ganglia-logtailer后，使用如下命令建立crond任务
*/1 * * * * root /usr/local/bin/ganglia-logtailer --classname NginxLogtailer --log_file /usr/local/nginx-video/logs/access.log --mode cron --gmetric_options ‘-C test_cluster -g nginx_status‘
reload crond service,过一分钟后，在ganglia web上即可看到相应的metric信息：
关于ganglia-logtailer的部署方法，详见：https://github.com/ganglia/ganglia_contrib/tree/master/ganglia-logtailer
3. 用支持的语言编写自己的module，本文以Python为例
ganglia支持用户编写自己的Python
module，以下为github上简要介绍：
Writing a Python module is very simple. You just need to write it following a template and put the resulting Python
module (.py) in /usr/lib(64)/ganglia/python_modules.
A corresponding Python Configuration (.pyconf) file needs to reside in /etc/ganglia/conf.d/.
例如，编写一个检查机器温度的示例Python文件
acpi_file = "/proc/acpi/thermal_zone/THRM/temperature"
def temp_handler(name):
try:
f = open(acpi_file, 'r')
except IOError:
return 0
for l in f:
line = l.split()
return int(line[1])
def metric_init(params):
global descriptors, acpi_file
if 'acpi_file' in params:
acpi_file = params['acpi_file']
d1 = {'name': 'temp',
'call_back': temp_handler,
'time_max': 90,
'value_type': 'uint',
'units': 'C',
'slope': 'both',
'format': '%u',
'description': 'Temperature of host',
'groups': 'health'}
descriptors = [d1]
return descriptors
def metric_cleanup():
'''Clean up the metric module.'''
pass
#This code is for debugging and unit testing
if __name__ == '__main__':
metric_init({})
for d in descriptors:
v = d['call_back'](d['name'])
print 'value for %s is %u' % (d['name'], v)
modules {
module {
name = "temp"
language = "python"
# The following params are examples only
# They are not actually used by the temp module
param RandomMax {
value = 600
}
param ConstantValue {
value = 112
}
}
}
collection_group {
collect_every = 10
time_threshold = 50
metric {
name = "temp"
title = "Temperature"
value_threshold = 70
}
}有了这两个文件，这个module就算添加成功了。
更多的用户贡献的module，请查看 https://github.com/ganglia/gmond_python_modules
其中包括elasticsearch、filecheck、nginx_status、MySQL等常见服务的监控metric对应的module，非常有用，只需要稍作修改，即可满足自己的需求。
如有问题，欢迎留言讨论。
版权声明：本文为博主原创文章，未经博主允许不得转载。
原文地址：http://blog.csdn.net/jiaowopan/article/details/46882911
