tahoe-lafs/src/allmydata/stats.py

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stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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import os
import pickle
import pprint
import sys
import time
from collections import deque
from twisted.internet import reactor, defer
from twisted.application import service
from twisted.application.internet import TimerService
from zope.interface import implements
import foolscap
from foolscap.eventual import eventually
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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from foolscap.logging.gatherer import get_local_ip_for
from twisted.internet.error import ConnectionDone, ConnectionLost
from foolscap import DeadReferenceError
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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from allmydata.util import log
from allmydata.interfaces import RIStatsProvider, RIStatsGatherer, IStatsProducer
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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class LoadMonitor(service.MultiService):
implements(IStatsProducer)
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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loop_interval = 1
num_samples = 60
def __init__(self, provider, warn_if_delay_exceeds=1):
service.MultiService.__init__(self)
self.provider = provider
self.warn_if_delay_exceeds = warn_if_delay_exceeds
self.started = False
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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self.last = None
self.stats = deque()
self.timer = None
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def startService(self):
if not self.started:
self.started = True
self.timer = reactor.callLater(self.loop_interval, self.loop)
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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service.MultiService.startService(self)
def stopService(self):
self.started = False
if self.timer:
self.timer.cancel()
self.timer = None
return service.MultiService.stopService(self)
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def loop(self):
self.timer = None
if not self.started:
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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return
now = time.time()
if self.last is not None:
delay = now - self.last - self.loop_interval
if delay > self.warn_if_delay_exceeds:
log.msg(format='excessive reactor delay (%ss)', args=(delay,),
level=log.UNUSUAL)
self.stats.append(delay)
while len(self.stats) > self.num_samples:
self.stats.popleft()
self.last = now
self.timer = reactor.callLater(self.loop_interval, self.loop)
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def get_stats(self):
if self.stats:
avg = sum(self.stats) / len(self.stats)
m_x = max(self.stats)
else:
avg = m_x = 0
return { 'load_monitor.avg_load': avg,
'load_monitor.max_load': m_x, }
class CPUUsageMonitor(service.MultiService):
implements(IStatsProducer)
MINUTES = 15
def __init__(self):
service.MultiService.__init__(self)
# we don't use time.clock() here, because the constructor is run by
# the twistd parent process (as it loads the .tac file), whereas the
# rest of the program will be run by the child process, after twistd
# forks. Instead, set self.initial_cpu as soon as the reactor starts
# up.
self.initial_cpu = 0.0 # just in case
eventually(self._set_initial_cpu)
self.samples = []
# we provide 1min, 5min, and 15min moving averages
TimerService(60, self.check).setServiceParent(self)
def _set_initial_cpu(self):
self.initial_cpu = time.clock()
def check(self):
now_wall = time.time()
now_cpu = time.clock()
self.samples.append( (now_wall, now_cpu) )
while len(self.samples) > self.MINUTES+1:
self.samples.pop(0)
def _average_N_minutes(self, size):
if len(self.samples) < size+1:
return None
first = -size-1
elapsed_wall = self.samples[-1][0] - self.samples[first][0]
elapsed_cpu = self.samples[-1][1] - self.samples[first][1]
fraction = elapsed_cpu / elapsed_wall
return fraction
def get_stats(self):
s = {}
avg = self._average_N_minutes(1)
if avg is not None:
s["cpu_monitor.1min_avg"] = avg
avg = self._average_N_minutes(5)
if avg is not None:
s["cpu_monitor.5min_avg"] = avg
avg = self._average_N_minutes(15)
if avg is not None:
s["cpu_monitor.15min_avg"] = avg
now_cpu = time.clock()
s["cpu_monitor.total"] = now_cpu - self.initial_cpu
return s
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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class StatsProvider(foolscap.Referenceable, service.MultiService):
implements(RIStatsProvider)
def __init__(self, node, gatherer_furl):
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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service.MultiService.__init__(self)
self.node = node
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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self.gatherer_furl = gatherer_furl
self.counters = {}
self.stats_producers = []
self.load_monitor = LoadMonitor(self)
self.load_monitor.setServiceParent(self)
self.register_producer(self.load_monitor)
self.cpu_monitor = CPUUsageMonitor()
self.cpu_monitor.setServiceParent(self)
self.register_producer(self.cpu_monitor)
def startService(self):
if self.node:
d = self.node.when_tub_ready()
def connect(junk):
nickname = self.node.get_config('nickname')
self.node.tub.connectTo(self.gatherer_furl, self._connected, nickname)
d.addCallback(connect)
service.MultiService.startService(self)
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def count(self, name, delta=1):
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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val = self.counters.setdefault(name, 0)
self.counters[name] = val + delta
def register_producer(self, stats_producer):
self.stats_producers.append(IStatsProducer(stats_producer))
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def get_stats(self):
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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stats = {}
for sp in self.stats_producers:
stats.update(sp.get_stats())
ret = { 'counters': self.counters, 'stats': stats }
log.msg(format='get_stats() -> %(stats)s', stats=ret, level=log.NOISY)
return ret
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def remote_get_stats(self):
return self.get_stats()
def _connected(self, gatherer, nickname):
gatherer.callRemoteOnly('provide', self, nickname or '')
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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class StatsGatherer(foolscap.Referenceable, service.MultiService):
implements(RIStatsGatherer)
poll_interval = 60
def __init__(self, tub, basedir):
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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service.MultiService.__init__(self)
self.tub = tub
self.basedir = basedir
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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self.clients = {}
self.nicknames = {}
def startService(self):
# the Tub must have a location set on it by now
service.MultiService.startService(self)
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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self.timer = TimerService(self.poll_interval, self.poll)
self.timer.setServiceParent(self)
self.registerGatherer()
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def get_furl(self):
return self.my_furl
def registerGatherer(self):
furl_file = os.path.join(self.basedir, "stats_gatherer.furl")
self.my_furl = self.tub.registerReference(self, furlFile=furl_file)
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def get_tubid(self, rref):
return foolscap.SturdyRef(rref.tracker.getURL()).getTubRef().getTubID()
def remote_provide(self, provider, nickname):
tubid = self.get_tubid(provider)
if tubid == '<unauth>':
print "WARNING: failed to get tubid for %s (%s)" % (provider, nickname)
# don't add to clients to poll (polluting data) don't care about disconnect
return
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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self.clients[tubid] = provider
self.nicknames[tubid] = nickname
def poll(self):
for tubid,client in self.clients.items():
nickname = self.nicknames.get(tubid)
d = client.callRemote('get_stats')
d.addCallbacks(self.got_stats, self.lost_client,
callbackArgs=(tubid, nickname),
errbackArgs=(tubid,))
d.addErrback(self.log_client_error, tubid)
def lost_client(self, f, tubid):
# this is called lazily, when a get_stats request fails
del self.clients[tubid]
del self.nicknames[tubid]
f.trap(DeadReferenceError, ConnectionDone, ConnectionLost)
def log_client_error(self, f, tubid):
log.msg("StatsGatherer: error in get_stats(), peerid=%s" % tubid,
level=log.UNUSUAL, failure=f)
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def got_stats(self, stats, tubid, nickname):
raise NotImplementedError()
class StdOutStatsGatherer(StatsGatherer):
verbose = True
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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def remote_provide(self, provider, nickname):
tubid = self.get_tubid(provider)
if self.verbose:
print 'connect "%s" [%s]' % (nickname, tubid)
provider.notifyOnDisconnect(self.announce_lost_client, tubid)
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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StatsGatherer.remote_provide(self, provider, nickname)
def announce_lost_client(self, tubid):
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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print 'disconnect "%s" [%s]:' % (self.nicknames[tubid], tubid)
def got_stats(self, stats, tubid, nickname):
print '"%s" [%s]:' % (nickname, tubid)
pprint.pprint(stats)
class PickleStatsGatherer(StdOutStatsGatherer):
# inherit from StdOutStatsGatherer for connect/disconnect notifications
def __init__(self, tub, basedir=".", verbose=True):
self.verbose = verbose
StatsGatherer.__init__(self, tub, basedir)
self.picklefile = os.path.join(basedir, "stats.pickle")
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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if os.path.exists(self.picklefile):
f = open(self.picklefile, 'rb')
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
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self.gathered_stats = pickle.load(f)
f.close()
else:
self.gathered_stats = {}
def got_stats(self, stats, tubid, nickname):
s = self.gathered_stats.setdefault(tubid, {})
s['timestamp'] = time.time()
s['nickname'] = nickname
s['stats'] = stats
self.dump_pickle()
def dump_pickle(self):
tmp = "%s.tmp" % (self.picklefile,)
f = open(tmp, 'wb')
pickle.dump(self.gathered_stats, f)
f.close()
if os.path.exists(self.picklefile):
os.unlink(self.picklefile)
os.rename(tmp, self.picklefile)
class GathererApp(object):
def __init__(self):
d = self.setup_tub()
d.addCallback(self._tub_ready)
def setup_tub(self):
self._tub = foolscap.Tub(certFile="stats_gatherer.pem")
self._tub.setOption("logLocalFailures", True)
self._tub.setOption("logRemoteFailures", True)
self._tub.startService()
portnumfile = "portnum"
try:
portnum = int(open(portnumfile, "r").read())
except (EnvironmentError, ValueError):
portnum = 0
self._tub.listenOn("tcp:%d" % portnum)
d = defer.maybeDeferred(get_local_ip_for)
d.addCallback(self._set_location)
d.addCallback(lambda res: self._tub)
return d
def _set_location(self, local_address):
if local_address is None:
local_addresses = ["127.0.0.1"]
else:
local_addresses = [local_address, "127.0.0.1"]
l = self._tub.getListeners()[0]
portnum = l.getPortnum()
portnumfile = "portnum"
open(portnumfile, "w").write("%d\n" % portnum)
local_addresses = [ "%s:%d" % (addr, portnum,)
for addr in local_addresses ]
assert len(local_addresses) >= 1
location = ",".join(local_addresses)
self._tub.setLocation(location)
def _tub_ready(self, tub):
sg = PickleStatsGatherer(tub, ".")
stats: add a simple stats gathering system We have a desire to collect runtime statistics from multiple nodes primarily for server monitoring purposes. This implements a simple implementation of such a system, as a skeleton to build more sophistication upon. Each client now looks for a 'stats_gatherer.furl' config file. If it has been configured to use a stats gatherer, then it instantiates internally a StatsProvider. This is a central place for code which wishes to offer stats up for monitoring to report them to, either by calling stats_provider.count('stat.name', value) to increment a counter, or by registering a class as a stats producer with sp.register_producer(obj). The StatsProvider connects to the StatsGatherer server and provides its provider upon startup. The StatsGatherer is then responsible for polling the attached providers periodically to retrieve the data provided. The provider queries each registered producer when the gatherer queries the provider. Both the internal 'counters' and the queried 'stats' are then reported to the gatherer. This provides a simple gatherer app, (c.f. make stats-gatherer-run) which prints its furl and listens for incoming connections. Once a minute, the gatherer polls all connected providers, and writes the retrieved data into a pickle file. Also included is a munin plugin which knows how to read the gatherer's stats.pickle and output data munin can interpret. this plugin, tahoe-stats.py can be symlinked as multiple different names within munin's 'plugins' directory, and inspects argv to determine which data to display, doing a lookup in a table within that file. It looks in the environment for 'statsfile' to determine the path to the gatherer's stats.pickle. An example plugins-conf.d file is provided.
2008-01-31 03:11:07 +00:00
sg.setServiceParent(tub)
sg.verbose = True
print '\nStatsGatherer: %s\n' % (sg.get_furl(),)
def main(argv):
ga = GathererApp()
reactor.run()
if __name__ == '__main__':
main(sys.argv)