def createMonitor():
return AccumulatingMonitorStrategy(
start_time=START_TIME,
instances=2,
txn_delta_k=ACC_MONITOR_TXN_DELTA_K,
timeout=ACC_MONITOR_TIMEOUT,
input_rate_reaction_half_time=ACC_MONITOR_INPUT_RATE_REACTION_HALF_TIME
)
def test_acc_monitor_detects_backup_slowdown(monitor: AccumulatingMonitorStrategy):
# Simulate txns receiving and ordering
triggered_time = simulate_ordering(monitor, 100.0, 0)
# Monitor should not be triggered before timeout
monitor.update_time(triggered_time + 0.8 * ACC_MONITOR_TIMEOUT)
assert not monitor.is_master_degraded()
assert not monitor.is_instance_degraded(1)
# Monitor should be triggered on backup after timeout
monitor.update_time(triggered_time + 1.2 * ACC_MONITOR_TIMEOUT)
assert not monitor.is_master_degraded()
assert monitor.is_instance_degraded(1)
def __init__(self, name: str, Delta: float, Lambda: float, Omega: float,
instances: Instances, nodestack,
blacklister: Blacklister, nodeInfo: Dict,
notifierEventTriggeringConfig: Dict,
pluginPaths: Iterable[str] = None,
notifierEventsEnabled: bool = True):
self.name = name
self.instances = instances
self.nodestack = nodestack
self.blacklister = blacklister
self.nodeInfo = nodeInfo
self.notifierEventTriggeringConfig = notifierEventTriggeringConfig
self.notifierEventsEnabled = notifierEventsEnabled
self.Delta = Delta
self.Lambda = Lambda
self.Omega = Omega
self.statsConsumers = self.getPluginsByType(pluginPaths,
PLUGIN_TYPE_STATS_CONSUMER)
self.config = getConfig()
# Number of ordered requests by each replica. The value at key `i` in
# the dict is a tuple of the number of ordered requests by replica and
# the time taken to order those requests by the replica of the `i`th
# protocol instance
self.numOrderedRequests = dict() # type: Dict[int, Tuple[int, int]]
# Dict(instance_id, throughput) of throughputs for replicas. Key is a instId and value is a instance of
# ThroughputMeasurement class and provide throughputs evaluating mechanism
self.throughputs = dict() # type: Dict[int, ThroughputMeasurement]
# Utility object for tracking requests order start and end
# TODO: Has very similar cleanup logic to propagator.Requests
self.requestTracker = RequestTimeTracker(instances.ids)
# Request latencies for the master protocol instances. Key of the
# dictionary is a tuple of client id and request id and the value is
# the time the master instance took for ordering it
self.masterReqLatencies = {} # type: Dict[Tuple[str, int], float]
# Indicates that request latency in previous snapshot of master req
# latencies was too high
self.masterReqLatencyTooHigh = False
# Request latency(time taken to be ordered) for the client. The value
# at key `i` in the dict is the LatencyMeasurement object which accumulate
# average latency and total request for each client.
self.clientAvgReqLatencies = dict() # type: Dict[int, LatencyMeasurement]
# TODO: Set this if this monitor belongs to a node which has primary
# of master. Will be used to set `totalRequests`
self.hasMasterPrimary = None
# Total requests that have been ordered since the node started
self.totalRequests = 0
self.started = datetime.utcnow().isoformat()
self.orderedRequestsInLast = []
# attention: handlers will work over unordered request only once
self.unordered_requests_handlers = [] # type: List[Callable]
# Monitoring suspicious spikes in cluster throughput
self.clusterThroughputSpikeMonitorData = {
'value': 0,
'cnt': 0,
'accum': []
}
psutil.cpu_percent(interval=None)
self.lastKnownTraffic = self.calculateTraffic()
self.totalViewChanges = 0
self._lastPostedViewChange = 0
HasActionQueue.__init__(self)
if self.config.SendMonitorStats:
self.startRepeating(self.sendPeriodicStats,
self.config.DashboardUpdateFreq)
self.startRepeating(
self.checkPerformance,
self.config.notifierEventTriggeringConfig['clusterThroughputSpike']['freq'])
self.startRepeating(self.check_unordered, self.config.UnorderedCheckFreq)
if 'disable_view_change' in self.config.unsafe:
self.isMasterDegraded = lambda: False
if 'disable_monitor' in self.config.unsafe:
self.requestOrdered = lambda *args, **kwargs: {}
self.sendPeriodicStats = lambda: None
self.checkPerformance = lambda: None
self.latency_avg_for_backup_cls = self.config.LatencyAveragingStrategyClass
self.latency_measurement_cls = self.config.LatencyMeasurementCls
self.throughput_avg_strategy_cls = self.config.throughput_averaging_strategy_class
self.acc_monitor = None
if self.config.ACC_MONITOR_ENABLED:
self.acc_monitor = AccumulatingMonitorStrategy(
start_time=time.perf_counter(),
instances=instances.ids,
txn_delta_k=self.config.ACC_MONITOR_TXN_DELTA_K,
timeout=self.config.ACC_MONITOR_TIMEOUT,
input_rate_reaction_half_time=self.config.ACC_MONITOR_INPUT_RATE_REACTION_HALF_TIME)
class Monitor(HasActionQueue, PluginLoaderHelper):
"""
Implementation of RBFT's monitoring mechanism.
The monitoring metrics are collected at the level of a node. Each node
monitors the performance of each instance. Throughput of requests and
latency per client request are measured.
"""
def __init__(self, name: str, Delta: float, Lambda: float, Omega: float,
instances: Instances, nodestack,
blacklister: Blacklister, nodeInfo: Dict,
notifierEventTriggeringConfig: Dict,
pluginPaths: Iterable[str] = None,
notifierEventsEnabled: bool = True):
self.name = name
self.instances = instances
self.nodestack = nodestack
self.blacklister = blacklister
self.nodeInfo = nodeInfo
self.notifierEventTriggeringConfig = notifierEventTriggeringConfig
self.notifierEventsEnabled = notifierEventsEnabled
self.Delta = Delta
self.Lambda = Lambda
self.Omega = Omega
self.statsConsumers = self.getPluginsByType(pluginPaths,
PLUGIN_TYPE_STATS_CONSUMER)
self.config = getConfig()
# Number of ordered requests by each replica. The value at key `i` in
# the dict is a tuple of the number of ordered requests by replica and
# the time taken to order those requests by the replica of the `i`th
# protocol instance
self.numOrderedRequests = dict() # type: Dict[int, Tuple[int, int]]
# Dict(instance_id, throughput) of throughputs for replicas. Key is a instId and value is a instance of
# ThroughputMeasurement class and provide throughputs evaluating mechanism
self.throughputs = dict() # type: Dict[int, ThroughputMeasurement]
# Utility object for tracking requests order start and end
# TODO: Has very similar cleanup logic to propagator.Requests
self.requestTracker = RequestTimeTracker(instances.ids)
# Request latencies for the master protocol instances. Key of the
# dictionary is a tuple of client id and request id and the value is
# the time the master instance took for ordering it
self.masterReqLatencies = {} # type: Dict[Tuple[str, int], float]
# Indicates that request latency in previous snapshot of master req
# latencies was too high
self.masterReqLatencyTooHigh = False
# Request latency(time taken to be ordered) for the client. The value
# at key `i` in the dict is the LatencyMeasurement object which accumulate
# average latency and total request for each client.
self.clientAvgReqLatencies = dict() # type: Dict[int, LatencyMeasurement]
# TODO: Set this if this monitor belongs to a node which has primary
# of master. Will be used to set `totalRequests`
self.hasMasterPrimary = None
# Total requests that have been ordered since the node started
self.totalRequests = 0
self.started = datetime.utcnow().isoformat()
self.orderedRequestsInLast = []
# attention: handlers will work over unordered request only once
self.unordered_requests_handlers = [] # type: List[Callable]
# Monitoring suspicious spikes in cluster throughput
self.clusterThroughputSpikeMonitorData = {
'value': 0,
'cnt': 0,
'accum': []
}
psutil.cpu_percent(interval=None)
self.lastKnownTraffic = self.calculateTraffic()
self.totalViewChanges = 0
self._lastPostedViewChange = 0
HasActionQueue.__init__(self)
if self.config.SendMonitorStats:
self.startRepeating(self.sendPeriodicStats,
self.config.DashboardUpdateFreq)
self.startRepeating(
self.checkPerformance,
self.config.notifierEventTriggeringConfig['clusterThroughputSpike']['freq'])
self.startRepeating(self.check_unordered, self.config.UnorderedCheckFreq)
if 'disable_view_change' in self.config.unsafe:
self.isMasterDegraded = lambda: False
if 'disable_monitor' in self.config.unsafe:
self.requestOrdered = lambda *args, **kwargs: {}
self.sendPeriodicStats = lambda: None
self.checkPerformance = lambda: None
self.latency_avg_for_backup_cls = self.config.LatencyAveragingStrategyClass
self.latency_measurement_cls = self.config.LatencyMeasurementCls
self.throughput_avg_strategy_cls = self.config.throughput_averaging_strategy_class
self.acc_monitor = None
if self.config.ACC_MONITOR_ENABLED:
self.acc_monitor = AccumulatingMonitorStrategy(
start_time=time.perf_counter(),
instances=instances.ids,
txn_delta_k=self.config.ACC_MONITOR_TXN_DELTA_K,
timeout=self.config.ACC_MONITOR_TIMEOUT,
input_rate_reaction_half_time=self.config.ACC_MONITOR_INPUT_RATE_REACTION_HALF_TIME)
def __repr__(self):
return self.name
def metrics(self):
"""
Calculate and return the metrics.
"""
masterThrp, backupThrp = self.getThroughputs(self.instances.masterId)
r = self.instance_throughput_ratio(self.instances.masterId)
m = [
("{} Monitor metrics:".format(self), None),
("Delta", self.Delta),
("Lambda", self.Lambda),
("Omega", self.Omega),
("instances started", self.instances.started),
("ordered request counts",
{i: r[0] for i, r in self.numOrderedRequests.items()}),
("ordered request durations",
{i: r[1] for i, r in self.numOrderedRequests.items()}),
("master request latencies", self.masterReqLatencies),
("client avg request latencies", {i: self.getLatency(i)
for i in self.instances.ids}),
("throughput", {i: self.getThroughput(i)
for i in self.instances.ids}),
("master throughput", masterThrp),
("total requests", self.totalRequests),
("avg backup throughput", backupThrp),
("master throughput ratio", r)]
return m
@property
def prettymetrics(self) -> str:
"""
Pretty printing for metrics
"""
rendered = ["{}: {}".format(*m) for m in self.metrics()]
return "\n ".join(rendered)
def calculateTraffic(self):
currNetwork = psutil.net_io_counters()
currNetwork = currNetwork.bytes_sent + currNetwork.bytes_recv
currNetwork /= 1024
return currNetwork
@staticmethod
def create_throughput_measurement(config, start_ts=time.perf_counter()):
tm = config.throughput_measurement_class(
**config.throughput_measurement_params)
tm.init_time(start_ts)
return tm
def reset(self):
"""
Reset the monitor. Sets all monitored values to defaults.
"""
logger.debug("{}'s Monitor being reset".format(self))
instances_ids = self.instances.started.keys()
self.numOrderedRequests = {inst_id: (0, 0) for inst_id in instances_ids}
self.requestTracker.reset()
self.masterReqLatencies = {}
self.masterReqLatencyTooHigh = False
self.totalViewChanges += 1
self.lastKnownTraffic = self.calculateTraffic()
if self.acc_monitor:
self.acc_monitor.reset()
for i in instances_ids:
rm = self.create_throughput_measurement(self.config)
self.throughputs[i] = rm
lm = self.latency_measurement_cls(self.config)
self.clientAvgReqLatencies[i] = lm
def addInstance(self, inst_id):
"""
Add one protocol instance for monitoring.
"""
self.instances.add(inst_id)
self.requestTracker.add_instance(inst_id)
self.numOrderedRequests[inst_id] = (0, 0)
rm = self.create_throughput_measurement(self.config)
self.throughputs[inst_id] = rm
lm = self.latency_measurement_cls(self.config)
self.clientAvgReqLatencies[inst_id] = lm
if self.acc_monitor:
self.acc_monitor.add_instance(inst_id)
def removeInstance(self, inst_id):
if self.acc_monitor:
self.acc_monitor.remove_instance(inst_id)
if self.instances.count > 0:
self.instances.remove(inst_id)
self.requestTracker.remove_instance(inst_id)
self.numOrderedRequests.pop(inst_id, None)
self.clientAvgReqLatencies.pop(inst_id, None)
self.throughputs.pop(inst_id, None)
def requestOrdered(self, reqIdrs: List[str], instId: int,
requests, byMaster: bool = False) -> Dict:
"""
Measure the time taken for ordering of a request and return it. Monitor
might have been reset due to view change due to which this method
returns None
"""
now = time.perf_counter()
if self.acc_monitor:
self.acc_monitor.update_time(now)
durations = {}
for key in reqIdrs:
if key not in self.requestTracker:
logger.debug("Got untracked ordered request with digest {}".
format(key))
continue
if self.acc_monitor:
self.acc_monitor.request_ordered(key, instId)
if key in self.requestTracker.handled_unordered():
started = self.requestTracker.started(key)
logger.info('Consensus for ReqId: {} was achieved by {}:{} in {} seconds.'
.format(key, self.name, instId, now - started))
duration = self.requestTracker.order(instId, key, now)
self.throughputs[instId].add_request(now)
if byMaster:
# TODO for now, view_change procedure can take more that 15 minutes
# (5 minutes for catchup and 10 minutes for primary's answer).
# Therefore, view_change triggering by max latency is not indicative now.
# self.masterReqLatencies[key] = duration
self.orderedRequestsInLast.append(now)
if key in requests:
identifier = requests[key].request.identifier
self.clientAvgReqLatencies[instId].add_duration(identifier, duration)
durations[key] = duration
reqs, tm = self.numOrderedRequests[instId]
orderedNow = len(durations)
self.numOrderedRequests[instId] = (reqs + orderedNow,
tm + sum(durations.values()))
# TODO: Inefficient, as on every request a minimum of a large list is
# calculated
if min(r[0] for r in self.numOrderedRequests.values()) == (reqs + orderedNow):
# If these requests is ordered by the last instance then increment
# total requests, but why is this important, why cant is ordering
# by master not enough?
self.totalRequests += orderedNow
self.postOnReqOrdered()
if 0 == reqs:
self.postOnNodeStarted(self.started)
return durations
def requestUnOrdered(self, key: str):
"""
Record the time at which request ordering started.
"""
now = time.perf_counter()
if self.acc_monitor:
self.acc_monitor.update_time(now)
self.acc_monitor.request_received(key)
self.requestTracker.start(key, now)
def check_unordered(self):
now = time.perf_counter()
new_unordereds = [(req, now - started) for req, started in self.requestTracker.unhandled_unordered()
if now - started > self.config.UnorderedCheckFreq]
if len(new_unordereds) == 0:
return
for handler in self.unordered_requests_handlers:
handler(new_unordereds)
for unordered in new_unordereds:
self.requestTracker.handle(unordered[0])
logger.debug('Following requests were not ordered for more than {} seconds: {}'
.format(self.config.UnorderedCheckFreq, unordered[0]))
def isMasterDegraded(self):
"""
Return whether the master instance is slow.
"""
if self.acc_monitor:
self.acc_monitor.update_time(time.perf_counter())
return self.acc_monitor.is_master_degraded()
else:
return (self.instances.masterId is not None and
(self.isMasterThroughputTooLow() or
# TODO for now, view_change procedure can take more that 15 minutes
# (5 minutes for catchup and 10 minutes for primary's answer).
# Therefore, view_change triggering by max latency now is not indicative.
# self.isMasterReqLatencyTooHigh() or
self.isMasterAvgReqLatencyTooHigh()))
def areBackupsDegraded(self):
"""
Return slow instance.
"""
slow_instances = []
if self.acc_monitor:
for instance in self.instances.backupIds:
if self.acc_monitor.is_instance_degraded(instance):
slow_instances.append(instance)
else:
for instance in self.instances.backupIds:
if self.is_instance_throughput_too_low(instance) or \
self.is_instance_avg_req_latency_too_high(instance):
slow_instances.append(instance)
return slow_instances
def instance_throughput_ratio(self, inst_id):
"""
The relative throughput of an instance compared to the backup
instances.
"""
inst_thrp, otherThrp = self.getThroughputs(inst_id)
# Backup throughput may be 0 so moving ahead only if it is not 0
r = inst_thrp / otherThrp if otherThrp and inst_thrp is not None \
else None
return r
def isMasterThroughputTooLow(self):
"""
Return whether the throughput of the master instance is greater than the
acceptable threshold
"""
return self.is_instance_throughput_too_low(self.instances.masterId)
def is_instance_throughput_too_low(self, inst_id):
"""
Return whether the throughput of the master instance is greater than the
acceptable threshold
"""
logging = self.instances.masterId == inst_id
r = self.instance_throughput_ratio(inst_id)
if r is None:
if logging:
logger.debug("{} instance {} throughput is not "
"measurable.".format(self, inst_id))
return None
too_low = r < self.Delta
if logging and too_low:
logger.display("{}{} instance {} throughput ratio {} is lower than Delta {}.".
format(MONITORING_PREFIX, self, inst_id, r, self.Delta))
elif logging:
logger.trace("{} instance {} throughput ratio {} is acceptable.".
format(self, inst_id, r))
return too_low
def isMasterReqLatencyTooHigh(self):
"""
Return whether the request latency of the master instance is greater
than the acceptable threshold
"""
# TODO for now, view_change procedure can take more that 15 minutes
# (5 minutes for catchup and 10 minutes for primary's answer).
# Therefore, view_change triggering by max latency is not indicative now.
r = self.masterReqLatencyTooHigh or \
next(((key, lat) for key, lat in self.masterReqLatencies.items() if
lat > self.Lambda), None)
if r:
logger.display("{}{} found master's latency {} to be higher than the threshold for request {}.".
format(MONITORING_PREFIX, self, r[1], r[0]))
else:
logger.trace("{} found master's latency to be lower than the "
"threshold for all requests.".format(self))
return r
def isMasterAvgReqLatencyTooHigh(self):
"""
Return whether the average request latency of the master instance is
greater than the acceptable threshold
"""
return self.is_instance_avg_req_latency_too_high(self.instances.masterId)
def is_instance_avg_req_latency_too_high(self, inst_id):
"""
Return whether the average request latency of an instance is
greater than the acceptable threshold
"""
avg_lat, avg_lat_others = self.getLatencies()
if not avg_lat or not avg_lat_others:
return False
d = avg_lat - avg_lat_others
if d < self.Omega:
return False
if inst_id == self.instances.masterId:
logger.info("{}{} found difference between master's and "
"backups's avg latency {} to be higher than the "
"threshold".format(MONITORING_PREFIX, self, d))
logger.trace(
"{}'s master's avg request latency is {} and backup's "
"avg request latency is {}".format(self, avg_lat, avg_lat_others))
return True
def getThroughputs(self, desired_inst_id: int):
"""
Return a tuple of the throughput of the given instance and the average
throughput of the remaining instances.
:param instId: the id of the protocol instance
"""
instance_thrp = self.getThroughput(desired_inst_id)
totalReqs, totalTm = self.getInstanceMetrics(forAllExcept=desired_inst_id)
# Average backup replica's throughput
if len(self.throughputs) > 1:
thrs = []
for inst_id, thr_obj in self.throughputs.items():
if inst_id != desired_inst_id:
thr = self.getThroughput(inst_id)
if thr is not None:
thrs.append(thr)
if thrs:
other_thrp = self.throughput_avg_strategy_cls.get_avg(thrs)
else:
other_thrp = None
else:
other_thrp = None
if instance_thrp == 0:
if self.numOrderedRequests[desired_inst_id] == (0, 0):
avgReqsPerInst = (totalReqs or 0) / self.instances.count
if avgReqsPerInst <= 1:
# too early to tell if we need an instance change
instance_thrp = None
return instance_thrp, other_thrp
def getThroughput(self, instId: int) -> float:
"""
Return the throughput of the specified instance.
:param instId: the id of the protocol instance
"""
# We are using the instanceStarted time in the denominator instead of
# a time interval. This is alright for now as all the instances on a
# node are started at almost the same time.
if instId not in self.instances.ids:
return None
perf_time = time.perf_counter()
throughput = self.throughputs[instId].get_throughput(perf_time)
return throughput
def getInstanceMetrics(
self, forAllExcept: int) -> Tuple[Optional[int], Optional[float]]:
"""
Calculate and return the average throughput of all the instances except
the one specified as `forAllExcept`.
"""
m = [(reqs, tm) for i, (reqs, tm)
in self.numOrderedRequests.items()
if i != forAllExcept]
if m:
reqs, tm = zip(*m)
return sum(reqs), sum(tm)
else:
return None, None
def getLatencies(self, desired_inst_id=None):
if desired_inst_id is None:
desired_inst_id = self.instances.masterId
avg_lat = self.getLatency(desired_inst_id)
avg_lat_others_by_inst = []
for inst_id in self.instances.ids:
if desired_inst_id == inst_id:
continue
lat = self.getLatency(inst_id)
if lat:
avg_lat_others_by_inst.append(lat)
avg_lat_others = self.latency_avg_for_backup_cls.get_avg(avg_lat_others_by_inst)\
if avg_lat_others_by_inst else None
return avg_lat, avg_lat_others
def getLatency(self, instId: int) -> float:
"""
Return a dict with client identifier as a key and calculated latency as a value
"""
if len(self.clientAvgReqLatencies) == 0:
return 0.0
return self.clientAvgReqLatencies[instId].get_avg_latency()
def sendPeriodicStats(self):
thoughputData = self.sendThroughput()
self.clusterThroughputSpikeMonitorData['accum'].append(
thoughputData['throughput'])
self.sendLatencies()
self.sendKnownNodesInfo()
self.sendNodeInfo()
self.sendSystemPerfomanceInfo()
self.sendTotalRequests()
def checkPerformance(self):
self.sendClusterThroughputSpike()
def sendClusterThroughputSpike(self):
if self.instances.masterId is None:
return None
accum = 0
for val in self.clusterThroughputSpikeMonitorData['accum']:
accum += val
if len(self.clusterThroughputSpikeMonitorData['accum']):
accum /= len(self.clusterThroughputSpikeMonitorData['accum'])
self.clusterThroughputSpikeMonitorData['accum'] = []
return pluginManager.sendMessageUponSuspiciousSpike(
notifierPluginTriggerEvents['clusterThroughputSpike'],
self.clusterThroughputSpikeMonitorData,
accum,
self.notifierEventTriggeringConfig['clusterThroughputSpike'],
self.name,
self.notifierEventsEnabled
)
@property
def highResThroughput(self):
# TODO:KS Move these computations as well to plenum-stats project
return self.getThroughput(self.instances.masterId)
def sendThroughput(self):
logger.debug("{} sending throughput".format(self))
throughput = self.highResThroughput
utcTime = datetime.utcnow()
mtrStats = {
"throughput": throughput,
"timestamp": utcTime.isoformat(),
"nodeName": self.name,
# Multiply by 1000 for JavaScript date conversion
"time": time.mktime(utcTime.timetuple()) * 1000
}
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_THROUGHPUT, mtrStats)
return mtrStats
@property
def masterLatency(self):
master_latency, _ = self.getLatencies()
return master_latency
@property
def avgBackupLatency(self):
_, lat_backup = self.getLatencies()
return lat_backup
def sendLatencies(self):
logger.debug("{} sending latencies".format(self))
utcTime = datetime.utcnow()
# Multiply by 1000 to make it compatible to JavaScript Date()
jsTime = time.mktime(utcTime.timetuple()) * 1000
latencies = dict(
masterLatency=self.masterLatency,
averageBackupLatency=self.avgBackupLatency,
time=jsTime,
nodeName=self.name,
timestamp=utcTime.isoformat()
)
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_LATENCIES, latencies)
def sendKnownNodesInfo(self):
logger.debug("{} sending nodestack".format(self))
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_NODES, remotesInfo(
self.nodestack, self.blacklister))
def sendSystemPerfomanceInfo(self):
logger.debug("{} sending system performance".format(self))
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_SYSTEM_PERFORMANCE_INFO,
self.captureSystemPerformance())
def sendNodeInfo(self):
logger.debug("{} sending node info".format(self))
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_NODE_INFO, self.nodeInfo['data'])
def sendTotalRequests(self):
logger.debug("{} sending total requests".format(self))
totalRequests = dict(
totalRequests=self.totalRequests
)
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_TOTAL_REQUESTS, totalRequests)
def captureSystemPerformance(self):
logger.debug("{} capturing system performance".format(self))
timestamp = time.time()
cpu = psutil.cpu_percent(interval=None)
ram = psutil.virtual_memory()
curr_network = self.calculateTraffic()
network = curr_network - self.lastKnownTraffic
self.lastKnownTraffic = curr_network
cpu_data = {
'time': timestamp,
'value': cpu
}
ram_data = {
'time': timestamp,
'value': ram.percent
}
traffic_data = {
'time': timestamp,
'value': network
}
return {
'cpu': cpu_data,
'ram': ram_data,
'traffic': traffic_data
}
def postOnReqOrdered(self):
utcTime = datetime.utcnow()
# Multiply by 1000 to make it compatible to JavaScript Date()
jsTime = time.mktime(utcTime.timetuple()) * 1000
if self.totalViewChanges != self._lastPostedViewChange:
self._lastPostedViewChange = self.totalViewChanges
viewChange = dict(
time=jsTime,
viewChange=self._lastPostedViewChange
)
self._sendStatsDataIfRequired(EVENT_VIEW_CHANGE, viewChange)
reqOrderedEventDict = dict(self.metrics())
reqOrderedEventDict["created_at"] = utcTime.isoformat()
reqOrderedEventDict["nodeName"] = self.name
reqOrderedEventDict["time"] = jsTime
reqOrderedEventDict["hasMasterPrimary"] = "Y" if self.hasMasterPrimary else "N"
self._sendStatsDataIfRequired(EVENT_REQ_ORDERED, reqOrderedEventDict)
self._clearSnapshot()
def postOnNodeStarted(self, startedAt):
throughputData = {
"updateFrequency": self.config.DashboardUpdateFreq,
"graphDuration": self.config.ThroughputGraphDuration
}
startedAtData = {"startedAt": startedAt, "ctx": "DEMO"}
startedEventDict = {
"startedAtData": startedAtData,
"throughputConfig": throughputData
}
self._sendStatsDataIfRequired(EVENT_NODE_STARTED, startedEventDict)
def _clearSnapshot(self):
self.masterReqLatencyTooHigh = self.isMasterReqLatencyTooHigh()
self.masterReqLatencies = {}
def _sendStatsDataIfRequired(self, event, stats):
if self.config.SendMonitorStats:
for sc in self.statsConsumers:
sc.sendStats(event, stats)
@staticmethod
def mean(data):
return 0 if len(data) == 0 else mean(data)
def __init__(self, name: str, Delta: float, Lambda: float, Omega: float,
instances: Instances, nodestack,
blacklister: Blacklister, nodeInfo: Dict,
notifierEventTriggeringConfig: Dict,
pluginPaths: Iterable[str] = None,
notifierEventsEnabled: bool = True):
self.name = name
self.instances = instances
self.nodestack = nodestack
self.blacklister = blacklister
self.nodeInfo = nodeInfo
self.notifierEventTriggeringConfig = notifierEventTriggeringConfig
self.notifierEventsEnabled = notifierEventsEnabled
self.Delta = Delta
self.Lambda = Lambda
self.Omega = Omega
self.statsConsumers = self.getPluginsByType(pluginPaths,
PLUGIN_TYPE_STATS_CONSUMER)
self.config = getConfig()
# Number of ordered requests by each replica. The value at key `i` in
# the dict is a tuple of the number of ordered requests by replica and
# the time taken to order those requests by the replica of the `i`th
# protocol instance
self.numOrderedRequests = dict() # type: Dict[int, Tuple[int, int]]
# Dict(instance_id, throughput) of throughputs for replicas. Key is a instId and value is a instance of
# ThroughputMeasurement class and provide throughputs evaluating mechanism
self.throughputs = dict() # type: Dict[int, ThroughputMeasurement]
# Utility object for tracking requests order start and end
# TODO: Has very similar cleanup logic to propagator.Requests
self.requestTracker = RequestTimeTracker(instances.ids)
# Request latencies for the master protocol instances. Key of the
# dictionary is a tuple of client id and request id and the value is
# the time the master instance took for ordering it
self.masterReqLatencies = {} # type: Dict[Tuple[str, int], float]
# Indicates that request latency in previous snapshot of master req
# latencies was too high
self.masterReqLatencyTooHigh = False
# Request latency(time taken to be ordered) for the client. The value
# at key `i` in the dict is the LatencyMeasurement object which accumulate
# average latency and total request for each client.
self.clientAvgReqLatencies = dict() # type: Dict[int, LatencyMeasurement]
# TODO: Set this if this monitor belongs to a node which has primary
# of master. Will be used to set `totalRequests`
self.hasMasterPrimary = None
# Total requests that have been ordered since the node started
self.totalRequests = 0
self.started = datetime.utcnow().isoformat()
# attention: handlers will work over unordered request only once
self.unordered_requests_handlers = [] # type: List[Callable]
# Monitoring suspicious spikes in cluster throughput
self.clusterThroughputSpikeMonitorData = {
'value': 0,
'cnt': 0,
'accum': []
}
psutil.cpu_percent(interval=None)
self.lastKnownTraffic = self.calculateTraffic()
self.totalViewChanges = 0
self._lastPostedViewChange = 0
HasActionQueue.__init__(self)
if self.config.SendMonitorStats:
self.startRepeating(self.sendPeriodicStats,
self.config.DashboardUpdateFreq)
self.startRepeating(
self.checkPerformance,
self.config.notifierEventTriggeringConfig['clusterThroughputSpike']['freq'])
self.startRepeating(self.check_unordered, self.config.UnorderedCheckFreq)
if 'disable_view_change' in self.config.unsafe:
self.isMasterDegraded = lambda: False
if 'disable_monitor' in self.config.unsafe:
self.requestOrdered = lambda *args, **kwargs: {}
self.sendPeriodicStats = lambda: None
self.checkPerformance = lambda: None
self.latency_avg_for_backup_cls = self.config.LatencyAveragingStrategyClass
self.latency_measurement_cls = self.config.LatencyMeasurementCls
self.throughput_avg_strategy_cls = self.config.throughput_averaging_strategy_class
self.acc_monitor = None
if self.config.ACC_MONITOR_ENABLED:
self.acc_monitor = AccumulatingMonitorStrategy(
start_time=time.perf_counter(),
instances=instances.ids,
txn_delta_k=self.config.ACC_MONITOR_TXN_DELTA_K,
timeout=self.config.ACC_MONITOR_TIMEOUT,
input_rate_reaction_half_time=self.config.ACC_MONITOR_INPUT_RATE_REACTION_HALF_TIME)
class Monitor(HasActionQueue, PluginLoaderHelper):
"""
Implementation of RBFT's monitoring mechanism.
The monitoring metrics are collected at the level of a node. Each node
monitors the performance of each instance. Throughput of requests and
latency per client request are measured.
"""
def __init__(self, name: str, Delta: float, Lambda: float, Omega: float,
instances: Instances, nodestack,
blacklister: Blacklister, nodeInfo: Dict,
notifierEventTriggeringConfig: Dict,
pluginPaths: Iterable[str] = None,
notifierEventsEnabled: bool = True):
self.name = name
self.instances = instances
self.nodestack = nodestack
self.blacklister = blacklister
self.nodeInfo = nodeInfo
self.notifierEventTriggeringConfig = notifierEventTriggeringConfig
self.notifierEventsEnabled = notifierEventsEnabled
self.Delta = Delta
self.Lambda = Lambda
self.Omega = Omega
self.statsConsumers = self.getPluginsByType(pluginPaths,
PLUGIN_TYPE_STATS_CONSUMER)
self.config = getConfig()
# Number of ordered requests by each replica. The value at key `i` in
# the dict is a tuple of the number of ordered requests by replica and
# the time taken to order those requests by the replica of the `i`th
# protocol instance
self.numOrderedRequests = dict() # type: Dict[int, Tuple[int, int]]
# Dict(instance_id, throughput) of throughputs for replicas. Key is a instId and value is a instance of
# ThroughputMeasurement class and provide throughputs evaluating mechanism
self.throughputs = dict() # type: Dict[int, ThroughputMeasurement]
# Utility object for tracking requests order start and end
# TODO: Has very similar cleanup logic to propagator.Requests
self.requestTracker = RequestTimeTracker(instances.ids)
# Request latencies for the master protocol instances. Key of the
# dictionary is a tuple of client id and request id and the value is
# the time the master instance took for ordering it
self.masterReqLatencies = {} # type: Dict[Tuple[str, int], float]
# Indicates that request latency in previous snapshot of master req
# latencies was too high
self.masterReqLatencyTooHigh = False
# Request latency(time taken to be ordered) for the client. The value
# at key `i` in the dict is the LatencyMeasurement object which accumulate
# average latency and total request for each client.
self.clientAvgReqLatencies = dict() # type: Dict[int, LatencyMeasurement]
# TODO: Set this if this monitor belongs to a node which has primary
# of master. Will be used to set `totalRequests`
self.hasMasterPrimary = None
# Total requests that have been ordered since the node started
self.totalRequests = 0
self.started = datetime.utcnow().isoformat()
# attention: handlers will work over unordered request only once
self.unordered_requests_handlers = [] # type: List[Callable]
# Monitoring suspicious spikes in cluster throughput
self.clusterThroughputSpikeMonitorData = {
'value': 0,
'cnt': 0,
'accum': []
}
psutil.cpu_percent(interval=None)
self.lastKnownTraffic = self.calculateTraffic()
self.totalViewChanges = 0
self._lastPostedViewChange = 0
HasActionQueue.__init__(self)
if self.config.SendMonitorStats:
self.startRepeating(self.sendPeriodicStats,
self.config.DashboardUpdateFreq)
self.startRepeating(
self.checkPerformance,
self.config.notifierEventTriggeringConfig['clusterThroughputSpike']['freq'])
self.startRepeating(self.check_unordered, self.config.UnorderedCheckFreq)
if 'disable_view_change' in self.config.unsafe:
self.isMasterDegraded = lambda: False
if 'disable_monitor' in self.config.unsafe:
self.requestOrdered = lambda *args, **kwargs: {}
self.sendPeriodicStats = lambda: None
self.checkPerformance = lambda: None
self.latency_avg_for_backup_cls = self.config.LatencyAveragingStrategyClass
self.latency_measurement_cls = self.config.LatencyMeasurementCls
self.throughput_avg_strategy_cls = self.config.throughput_averaging_strategy_class
self.acc_monitor = None
if self.config.ACC_MONITOR_ENABLED:
self.acc_monitor = AccumulatingMonitorStrategy(
start_time=time.perf_counter(),
instances=instances.ids,
txn_delta_k=self.config.ACC_MONITOR_TXN_DELTA_K,
timeout=self.config.ACC_MONITOR_TIMEOUT,
input_rate_reaction_half_time=self.config.ACC_MONITOR_INPUT_RATE_REACTION_HALF_TIME)
def __repr__(self):
return self.name
def metrics(self):
"""
Calculate and return the metrics.
"""
masterThrp, backupThrp = self.getThroughputs(self.instances.masterId)
r = self.instance_throughput_ratio(self.instances.masterId)
m = [
("{} Monitor metrics:".format(self), None),
("Delta", self.Delta),
("Lambda", self.Lambda),
("Omega", self.Omega),
("instances started", self.instances.started),
("ordered request counts",
{i: r[0] for i, r in self.numOrderedRequests.items()}),
("ordered request durations",
{i: r[1] for i, r in self.numOrderedRequests.items()}),
("master request latencies", self.masterReqLatencies),
("client avg request latencies", {i: self.getLatency(i)
for i in self.instances.ids}),
("throughput", {i: self.getThroughput(i)
for i in self.instances.ids}),
("master throughput", masterThrp),
("total requests", self.totalRequests),
("avg backup throughput", backupThrp),
("master throughput ratio", r)]
return m
@property
def prettymetrics(self) -> str:
"""
Pretty printing for metrics
"""
rendered = ["{}: {}".format(*m) for m in self.metrics()]
return "\n ".join(rendered)
def calculateTraffic(self):
currNetwork = psutil.net_io_counters()
currNetwork = currNetwork.bytes_sent + currNetwork.bytes_recv
currNetwork /= 1024
return currNetwork
@staticmethod
def create_throughput_measurement(config, start_ts=None):
if start_ts is None:
start_ts = time.perf_counter()
tm = config.throughput_measurement_class(
**config.throughput_measurement_params)
tm.init_time(start_ts)
logger.trace("Creating throughput measurement class {} with parameters {} in start time {}"
.format(str(config.throughput_measurement_class), str(config.throughput_measurement_params), start_ts))
return tm
def reset(self):
"""
Reset the monitor. Sets all monitored values to defaults.
"""
logger.debug("{}'s Monitor being reset".format(self))
instances_ids = self.instances.started.keys()
self.numOrderedRequests = {inst_id: (0, 0) for inst_id in instances_ids}
self.requestTracker.reset()
self.masterReqLatencies = {}
self.masterReqLatencyTooHigh = False
self.totalViewChanges += 1
self.lastKnownTraffic = self.calculateTraffic()
if self.acc_monitor:
self.acc_monitor.reset()
for i in instances_ids:
rm = self.create_throughput_measurement(self.config)
self.throughputs[i] = rm
lm = self.latency_measurement_cls(self.config)
self.clientAvgReqLatencies[i] = lm
def addInstance(self, inst_id):
"""
Add one protocol instance for monitoring.
"""
self.instances.add(inst_id)
self.requestTracker.add_instance(inst_id)
self.numOrderedRequests[inst_id] = (0, 0)
rm = self.create_throughput_measurement(self.config)
self.throughputs[inst_id] = rm
lm = self.latency_measurement_cls(self.config)
self.clientAvgReqLatencies[inst_id] = lm
if self.acc_monitor:
self.acc_monitor.add_instance(inst_id)
def removeInstance(self, inst_id):
if self.acc_monitor:
self.acc_monitor.remove_instance(inst_id)
if self.instances.count > 0:
self.instances.remove(inst_id)
self.requestTracker.remove_instance(inst_id)
self.numOrderedRequests.pop(inst_id, None)
self.clientAvgReqLatencies.pop(inst_id, None)
self.throughputs.pop(inst_id, None)
def requestOrdered(self, reqIdrs: List[str], instId: int,
requests, byMaster: bool = False) -> Dict:
"""
Measure the time taken for ordering of a request and return it. Monitor
might have been reset due to view change due to which this method
returns None
"""
now = time.perf_counter()
if self.acc_monitor:
self.acc_monitor.update_time(now)
durations = {}
for key in reqIdrs:
if key not in self.requestTracker:
logger.debug("Got untracked ordered request with digest {}".
format(key))
continue
if self.acc_monitor:
self.acc_monitor.request_ordered(key, instId)
if key in self.requestTracker.handled_unordered():
started = self.requestTracker.started(key)
logger.info('Consensus for ReqId: {} was achieved by {}:{} in {} seconds.'
.format(key, self.name, instId, now - started))
duration = self.requestTracker.order(instId, key, now)
self.throughputs[instId].add_request(now)
if key in requests:
identifier = requests[key].request.identifier
self.clientAvgReqLatencies[instId].add_duration(identifier, duration)
durations[key] = duration
reqs, tm = self.numOrderedRequests[instId]
orderedNow = len(durations)
self.numOrderedRequests[instId] = (reqs + orderedNow,
tm + sum(durations.values()))
# TODO: Inefficient, as on every request a minimum of a large list is
# calculated
if min(r[0] for r in self.numOrderedRequests.values()) == (reqs + orderedNow):
# If these requests is ordered by the last instance then increment
# total requests, but why is this important, why cant is ordering
# by master not enough?
self.totalRequests += orderedNow
self.postOnReqOrdered()
if 0 == reqs:
self.postOnNodeStarted(self.started)
return durations
def requestUnOrdered(self, key: str):
"""
Record the time at which request ordering started.
"""
now = time.perf_counter()
if self.acc_monitor:
self.acc_monitor.update_time(now)
self.acc_monitor.request_received(key)
self.requestTracker.start(key, now)
def check_unordered(self):
now = time.perf_counter()
new_unordereds = [(req, now - started) for req, started in self.requestTracker.unhandled_unordered()
if now - started > self.config.UnorderedCheckFreq]
if len(new_unordereds) == 0:
return
for handler in self.unordered_requests_handlers:
handler(new_unordereds)
for unordered in new_unordereds:
self.requestTracker.handle(unordered[0])
logger.debug('Following requests were not ordered for more than {} seconds: {}'
.format(self.config.UnorderedCheckFreq, unordered[0]))
def isMasterDegraded(self):
"""
Return whether the master instance is slow.
"""
if self.acc_monitor:
self.acc_monitor.update_time(time.perf_counter())
return self.acc_monitor.is_master_degraded()
else:
return (self.instances.masterId is not None and
(self.isMasterThroughputTooLow() or
# TODO for now, view_change procedure can take more that 15 minutes
# (5 minutes for catchup and 10 minutes for primary's answer).
# Therefore, view_change triggering by max latency now is not indicative.
# self.isMasterReqLatencyTooHigh() or
self.isMasterAvgReqLatencyTooHigh()))
def areBackupsDegraded(self):
"""
Return slow instance.
"""
slow_instances = []
if self.acc_monitor:
for instance in self.instances.backupIds:
if self.acc_monitor.is_instance_degraded(instance):
slow_instances.append(instance)
else:
for instance in self.instances.backupIds:
if self.is_instance_throughput_too_low(instance):
slow_instances.append(instance)
return slow_instances
def instance_throughput_ratio(self, inst_id):
"""
The relative throughput of an instance compared to the backup
instances.
"""
inst_thrp, otherThrp = self.getThroughputs(inst_id)
# Backup throughput may be 0 so moving ahead only if it is not 0
r = inst_thrp / otherThrp if otherThrp and inst_thrp is not None \
else None
return r
def isMasterThroughputTooLow(self):
"""
Return whether the throughput of the master instance is greater than the
acceptable threshold
"""
return self.is_instance_throughput_too_low(self.instances.masterId)
def is_instance_throughput_too_low(self, inst_id):
"""
Return whether the throughput of the master instance is greater than the
acceptable threshold
"""
r = self.instance_throughput_ratio(inst_id)
if r is None:
logger.debug("{} instance {} throughput is not "
"measurable.".format(self, inst_id))
return None
too_low = r < self.Delta
if too_low:
logger.display("{}{} instance {} throughput ratio {} is lower than Delta {}.".
format(MONITORING_PREFIX, self, inst_id, r, self.Delta))
else:
logger.trace("{} instance {} throughput ratio {} is acceptable.".
format(self, inst_id, r))
return too_low
def isMasterReqLatencyTooHigh(self):
"""
Return whether the request latency of the master instance is greater
than the acceptable threshold
"""
# TODO for now, view_change procedure can take more that 15 minutes
# (5 minutes for catchup and 10 minutes for primary's answer).
# Therefore, view_change triggering by max latency is not indicative now.
r = self.masterReqLatencyTooHigh or \
next(((key, lat) for key, lat in self.masterReqLatencies.items() if
lat > self.Lambda), None)
if r:
logger.display("{}{} found master's latency {} to be higher than the threshold for request {}.".
format(MONITORING_PREFIX, self, r[1], r[0]))
else:
logger.trace("{} found master's latency to be lower than the "
"threshold for all requests.".format(self))
return r
def isMasterAvgReqLatencyTooHigh(self):
"""
Return whether the average request latency of the master instance is
greater than the acceptable threshold
"""
return self.is_instance_avg_req_latency_too_high(self.instances.masterId)
def is_instance_avg_req_latency_too_high(self, inst_id):
"""
Return whether the average request latency of an instance is
greater than the acceptable threshold
"""
avg_lat, avg_lat_others = self.getLatencies()
if not avg_lat or not avg_lat_others:
return False
d = avg_lat - avg_lat_others
if d < self.Omega:
return False
if inst_id == self.instances.masterId:
logger.info("{}{} found difference between master's and "
"backups's avg latency {} to be higher than the "
"threshold".format(MONITORING_PREFIX, self, d))
logger.trace(
"{}'s master's avg request latency is {} and backup's "
"avg request latency is {}".format(self, avg_lat, avg_lat_others))
return True
def getThroughputs(self, desired_inst_id: int):
"""
Return a tuple of the throughput of the given instance and the average
throughput of the remaining instances.
:param instId: the id of the protocol instance
"""
instance_thrp = self.getThroughput(desired_inst_id)
totalReqs, totalTm = self.getInstanceMetrics(forAllExcept=desired_inst_id)
# Average backup replica's throughput
if len(self.throughputs) > 1:
thrs = []
for inst_id, thr_obj in self.throughputs.items():
if inst_id == desired_inst_id:
continue
thr = self.getThroughput(inst_id)
if thr is not None:
thrs.append(thr)
if thrs:
other_thrp = self.throughput_avg_strategy_cls.get_avg(thrs)
else:
other_thrp = None
else:
other_thrp = None
if instance_thrp == 0:
if self.numOrderedRequests[desired_inst_id] == (0, 0):
avgReqsPerInst = (totalReqs or 0) / self.instances.count
if avgReqsPerInst <= 1:
# too early to tell if we need an instance change
instance_thrp = None
return instance_thrp, other_thrp
def getThroughput(self, instId: int) -> float:
"""
Return the throughput of the specified instance.
:param instId: the id of the protocol instance
"""
# We are using the instanceStarted time in the denominator instead of
# a time interval. This is alright for now as all the instances on a
# node are started at almost the same time.
if instId not in self.instances.ids:
return None
perf_time = time.perf_counter()
throughput = self.throughputs[instId].get_throughput(perf_time)
return throughput
def getInstanceMetrics(
self, forAllExcept: int) -> Tuple[Optional[int], Optional[float]]:
"""
Calculate and return the average throughput of all the instances except
the one specified as `forAllExcept`.
"""
m = [(reqs, tm) for i, (reqs, tm)
in self.numOrderedRequests.items()
if i != forAllExcept]
if m:
reqs, tm = zip(*m)
return sum(reqs), sum(tm)
else:
return None, None
def getLatencies(self, desired_inst_id=None):
if desired_inst_id is None:
desired_inst_id = self.instances.masterId
avg_lat = self.getLatency(desired_inst_id)
avg_lat_others_by_inst = []
for inst_id in self.instances.ids:
if desired_inst_id == inst_id:
continue
lat = self.getLatency(inst_id)
if lat:
avg_lat_others_by_inst.append(lat)
avg_lat_others = self.latency_avg_for_backup_cls.get_avg(avg_lat_others_by_inst)\
if avg_lat_others_by_inst else None
return avg_lat, avg_lat_others
def getLatency(self, instId: int) -> float:
"""
Return a dict with client identifier as a key and calculated latency as a value
"""
if len(self.clientAvgReqLatencies) == 0:
return 0.0
return self.clientAvgReqLatencies[instId].get_avg_latency()
def sendPeriodicStats(self):
thoughputData = self.sendThroughput()
self.clusterThroughputSpikeMonitorData['accum'].append(
thoughputData['throughput'])
self.sendLatencies()
self.sendKnownNodesInfo()
self.sendNodeInfo()
self.sendSystemPerfomanceInfo()
self.sendTotalRequests()
def checkPerformance(self):
self.sendClusterThroughputSpike()
def sendClusterThroughputSpike(self):
if self.instances.masterId is None:
return None
accum = 0
for val in self.clusterThroughputSpikeMonitorData['accum']:
accum += val
if len(self.clusterThroughputSpikeMonitorData['accum']):
accum /= len(self.clusterThroughputSpikeMonitorData['accum'])
self.clusterThroughputSpikeMonitorData['accum'] = []
return pluginManager.sendMessageUponSuspiciousSpike(
notifierPluginTriggerEvents['clusterThroughputSpike'],
self.clusterThroughputSpikeMonitorData,
accum,
self.notifierEventTriggeringConfig['clusterThroughputSpike'],
self.name,
self.notifierEventsEnabled
)
@property
def highResThroughput(self):
# TODO:KS Move these computations as well to plenum-stats project
return self.getThroughput(self.instances.masterId)
def sendThroughput(self):
logger.debug("{} sending throughput".format(self))
throughput = self.highResThroughput
utcTime = datetime.utcnow()
mtrStats = {
"throughput": throughput,
"timestamp": utcTime.isoformat(),
"nodeName": self.name,
# Multiply by 1000 for JavaScript date conversion
"time": time.mktime(utcTime.timetuple()) * 1000
}
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_THROUGHPUT, mtrStats)
return mtrStats
@property
def masterLatency(self):
master_latency, _ = self.getLatencies()
return master_latency
@property
def avgBackupLatency(self):
_, lat_backup = self.getLatencies()
return lat_backup
def sendLatencies(self):
logger.debug("{} sending latencies".format(self))
utcTime = datetime.utcnow()
# Multiply by 1000 to make it compatible to JavaScript Date()
jsTime = time.mktime(utcTime.timetuple()) * 1000
latencies = dict(
masterLatency=self.masterLatency,
averageBackupLatency=self.avgBackupLatency,
time=jsTime,
nodeName=self.name,
timestamp=utcTime.isoformat()
)
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_LATENCIES, latencies)
def sendKnownNodesInfo(self):
logger.debug("{} sending nodestack".format(self))
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_NODES, remotesInfo(
self.nodestack, self.blacklister))
def sendSystemPerfomanceInfo(self):
logger.debug("{} sending system performance".format(self))
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_SYSTEM_PERFORMANCE_INFO,
self.captureSystemPerformance())
def sendNodeInfo(self):
logger.debug("{} sending node info".format(self))
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_NODE_INFO, self.nodeInfo['data'])
def sendTotalRequests(self):
logger.debug("{} sending total requests".format(self))
totalRequests = dict(
totalRequests=self.totalRequests
)
self._sendStatsDataIfRequired(
EVENT_PERIODIC_STATS_TOTAL_REQUESTS, totalRequests)
def captureSystemPerformance(self):
logger.debug("{} capturing system performance".format(self))
timestamp = time.time()
cpu = psutil.cpu_percent(interval=None)
ram = psutil.virtual_memory()
curr_network = self.calculateTraffic()
network = curr_network - self.lastKnownTraffic
self.lastKnownTraffic = curr_network
cpu_data = {
'time': timestamp,
'value': cpu
}
ram_data = {
'time': timestamp,
'value': ram.percent
}
traffic_data = {
'time': timestamp,
'value': network
}
return {
'cpu': cpu_data,
'ram': ram_data,
'traffic': traffic_data
}
def postOnReqOrdered(self):
utcTime = datetime.utcnow()
# Multiply by 1000 to make it compatible to JavaScript Date()
jsTime = time.mktime(utcTime.timetuple()) * 1000
if self.totalViewChanges != self._lastPostedViewChange:
self._lastPostedViewChange = self.totalViewChanges
viewChange = dict(
time=jsTime,
viewChange=self._lastPostedViewChange
)
self._sendStatsDataIfRequired(EVENT_VIEW_CHANGE, viewChange)
reqOrderedEventDict = dict(self.metrics())
reqOrderedEventDict["created_at"] = utcTime.isoformat()
reqOrderedEventDict["nodeName"] = self.name
reqOrderedEventDict["time"] = jsTime
reqOrderedEventDict["hasMasterPrimary"] = "Y" if self.hasMasterPrimary else "N"
self._sendStatsDataIfRequired(EVENT_REQ_ORDERED, reqOrderedEventDict)
self._clearSnapshot()
def postOnNodeStarted(self, startedAt):
throughputData = {
"updateFrequency": self.config.DashboardUpdateFreq,
"graphDuration": self.config.ThroughputGraphDuration
}
startedAtData = {"startedAt": startedAt, "ctx": "DEMO"}
startedEventDict = {
"startedAtData": startedAtData,
"throughputConfig": throughputData
}
self._sendStatsDataIfRequired(EVENT_NODE_STARTED, startedEventDict)
def _clearSnapshot(self):
self.masterReqLatencyTooHigh = self.isMasterReqLatencyTooHigh()
self.masterReqLatencies = {}
def _sendStatsDataIfRequired(self, event, stats):
if self.config.SendMonitorStats:
for sc in self.statsConsumers:
sc.sendStats(event, stats)
@staticmethod
def mean(data):
return 0 if len(data) == 0 else mean(data)
def test_acc_monitor_works_even_with_one_instance(monitor: AccumulatingMonitorStrategy):
monitor.remove_instance(1)
start_time = 100.0
monitor.update_time(start_time)
monitor.request_received('A')
monitor.update_time(start_time + 1.2 * ACC_MONITOR_TIMEOUT)
assert not monitor.is_master_degraded()
monitor.request_ordered('A', 0)
monitor.update_time(start_time + 2.4 * ACC_MONITOR_TIMEOUT)
assert not monitor.is_master_degraded()
def test_acc_monitor_behaves_as_expected(monitor: AccumulatingMonitorStrategy):
# Simulate txns receiving and ordering
triggered_time = simulate_ordering(monitor, 100.0, 1)
# Monitor should not be triggered before timeout
monitor.update_time(triggered_time + 0.8 * ACC_MONITOR_TIMEOUT)
assert not monitor.is_master_degraded()
assert not monitor.is_instance_degraded(1)
# Monitor should be triggered on master after timeout
monitor.update_time(triggered_time + 1.2 * ACC_MONITOR_TIMEOUT)
assert monitor.is_master_degraded()
assert not monitor.is_instance_degraded(1)
# Monitor should not be triggered after reset
monitor.reset()
assert not monitor.is_master_degraded()
assert not monitor.is_instance_degraded(1)
# Give monitor chance to observe txn statistics
reset_time = triggered_time + 2.4 * ACC_MONITOR_TIMEOUT
monitor.update_time(reset_time)
# Monitor should not be triggered if nothing is ordered
monitor.update_time(reset_time + 1.2 * ACC_MONITOR_TIMEOUT)
assert not monitor.is_master_degraded()
assert not monitor.is_instance_degraded(1)
def test_acc_monitor_isnt_alerted_when_created(monitor: AccumulatingMonitorStrategy):
assert not monitor.is_master_degraded()
assert not monitor.is_instance_degraded(1)
def test_acc_monitor_handles_adding_instances(monitor: AccumulatingMonitorStrategy):
monitor.add_instance(2)
triggered_time = simulate_ordering(monitor, 100.0, 2)
# Monitor should not be triggered before timeout
monitor.update_time(triggered_time + 0.8 * ACC_MONITOR_TIMEOUT)
assert not monitor.is_master_degraded()
assert not monitor.is_instance_degraded(1)
assert not monitor.is_instance_degraded(2)
# Monitor should be triggered after timeout
monitor.update_time(triggered_time + 1.2 * ACC_MONITOR_TIMEOUT)
assert monitor.is_master_degraded()
assert monitor.is_instance_degraded(1) # TODO: Monitor behaves like this now, but is it okay?
assert not monitor.is_instance_degraded(2)
