def __init__(self, parent_pid, context, canary=False):
super(Worker, self).__init__()
self.context = context
self.ring = RedisRing(settings.REDIS_BACKENDS)
self.parent_pid = parent_pid
self.daemon = True
self.canary = canary
def __init__(self, parent_pid):
"""
Initialize the Analyzer
"""
super(Analyzer, self).__init__()
self.ring = RedisRing(settings.REDIS_BACKENDS)
self.daemon = True
self.parent_pid = parent_pid
self.current_pid = getpid()
self.anomalous_metrics = Manager().list()
self.exceptions_q = Queue()
self.anomaly_breakdown_q = Queue()
def run(self):
"""
Called when the process intializes.
"""
logger.info('started worker')
FULL_NAMESPACE = settings.FULL_NAMESPACE
MINI_NAMESPACE = settings.MINI_NAMESPACE
MAX_RESOLUTION = settings.MAX_RESOLUTION
self.conn = self.context.socket(zmq.PULL)
self.conn.connect(
'{0}:{0}'.format(settings.RELAY_HOST, settings.RELAY_PUBLISH_PORT))
self.poller = zmq.Poller()
self.poller.register(self.conn, zmq.POLLIN)
while 1:
sockets = dict(self.poller.poll())
if self.conn in sockets and sockets[self.conn] == zmq.POLLIN:
# Make sure Redis is up
try:
self.ring.check_connections()
except:
sleep(10)
self.ring = RedisRing(settings.REDIS_BACKENDS)
continue
try:
# Get a chunk from the queue with a 15 second timeout
chunk = self.q.get(True, 15)
now = time()
for metric in chunk:
# Check if we should skip it
if self.in_skip_list(metric[0]):
continue
# Bad data coming in
if metric[1][0] < now - MAX_RESOLUTION:
continue
for ns in [FULL_NAMESPACE, MINI_NAMESPACE]:
key = ''.join((ns, metric[0]))
self.ring.run('append', key, packb(metric[1]))
ukey = ''.join((ns,'unique_metrics.',metric[0]))
self.ring.run('sadd', ukey, key)
except Exception as e:
logger.error("worker error: " + str(e))
class Analyzer(Thread):
def __init__(self, parent_pid):
"""
Initialize the Analyzer
"""
super(Analyzer, self).__init__()
self.ring = RedisRing(settings.REDIS_BACKENDS)
self.daemon = True
self.parent_pid = parent_pid
self.current_pid = getpid()
self.anomalous_metrics = Manager().list()
self.exceptions_q = Queue()
self.anomaly_breakdown_q = Queue()
def check_if_parent_is_alive(self):
"""
Self explanatory
"""
try:
kill(self.current_pid, 0)
kill(self.parent_pid, 0)
except:
exit(0)
def spin_process(self, i, unique_metrics):
process_key = '.'.join(['skyline','analyzer', socket.gethostname(), str(i)])
alive_key = '.'.join([process_key, 'alive'])
self.ring.run('set', alive_key, 1)
self.ring.run('expire', alive_key, 30)
"""
Assign a bunch of metrics for a process to analyze.
"""
processes = list(self.ring.run('zrange', settings.ANALYZER_PROCESS_KEY, 0, -1))
for key in processes:
value = self.ring.run('get', key)
if not value:
self.ring.run('zrem', settings.ANALYZER_PROCESS_KEY, 0, key)
# Add current process to index and determine position
if not self.ring.run('zscore', settings.ANALYZER_PROCESS_KEY, alive_key):
self.ring.run('zadd', settings.ANALYZER_PROCESS_KEY, time(), alive_key)
self.ring.run('expire', settings.ANALYZER_PROCESS_KEY, 60)
process_position = self.ring.run('zrank', settings.ANALYZER_PROCESS_KEY, alive_key) + 1
process_count = self.ring.run('zcard', settings.ANALYZER_PROCESS_KEY)
# If there are less processes then we know are going to be running assume
# the others will start
if process_count < settings.ANALYZER_PROCESSES:
process_count = settings.ANALYZER_PROCESSES
# Discover assigned metrics
keys_per_processor = int(ceil(float(len(unique_metrics)) / float(process_count)))
if process_position == process_count:
assigned_max = len(unique_metrics)
else:
assigned_max = process_position * keys_per_processor
assigned_min = assigned_max - keys_per_processor
assigned_keys = range(assigned_min, assigned_max)
# Compile assigned metrics
assigned_metrics = [unique_metrics[index] for index in assigned_keys]
# Check if this process is unnecessary
if len(assigned_metrics) == 0:
return
# Multi get series
raw_assigned = self.ring.run('mget', assigned_metrics)
# Make process-specific dicts
exceptions = defaultdict(int)
anomaly_breakdown = defaultdict(int)
# Distill timeseries strings into lists
for i, metric_name in enumerate(assigned_metrics):
self.check_if_parent_is_alive()
try:
raw_series = raw_assigned[i]
unpacker = Unpacker(use_list = False)
unpacker.feed(raw_series)
timeseries = list(unpacker)
anomalous, ensemble, datapoint = run_selected_algorithm(timeseries, metric_name)
# If it's anomalous, add it to list
if anomalous:
base_name = metric_name.replace(settings.FULL_NAMESPACE, '', 1)
metric = [datapoint, base_name]
self.anomalous_metrics.append(metric)
# Get the anomaly breakdown - who returned True?
for index, value in enumerate(ensemble):
if value:
algorithm = settings.ALGORITHMS[index]
anomaly_breakdown[algorithm] += 1
# It could have been deleted by the Roomba
except TypeError:
exceptions['DeletedByRoomba'] += 1
except TooShort:
exceptions['TooShort'] += 1
except Stale:
exceptions['Stale'] += 1
except Incomplete:
exceptions['Incomplete'] += 1
except Boring:
exceptions['Boring'] += 1
except:
exceptions['Other'] += 1
logger.info(traceback.format_exc())
# if anomalies detected Pack and Write anomoly data to Redis
if len(anomalous_metrics) > 0:
packed = Packer().pack(anomalous_metrics)
self.ring.run('set', process_key, packed)
# expire the key in 30s so anomalys don't show up for too long
self.ring.run('expire', process_key, 30)
self.ring.run('sadd', settings.ANALYZER_ANOMALY_KEY, process_key)
# expire the key in 60s so anomalys don't show up for too long
self.ring.run('expire', settings.ANALYZER_ANOMALY_KEY, 60)
# Collate process-specific dicts to main dicts
with self.lock:
for key, value in anomaly_breakdown.items():
if key not in self.anomaly_breakdown:
self.anomaly_breakdown[key] = value
else:
self.anomaly_breakdown[key] += value
for key, value in exceptions.items():
if key not in self.exceptions:
self.exceptions[key] = value
else:
self.exceptions[key] += value
for key, value in exceptions.items():
self.exceptions_q.put((key, value))
def run(self):
"""
Called when the process intializes.
"""
while 1:
now = time()
# Make sure Redis is up
try:
self.ring.check_connections()
except:
sleep(10)
self.ring = RedisRing(settings.REDIS_BACKENDS)
continue
# Discover unique metrics
unique_metrics = list(self.ring.run('smembers', settings.FULL_NAMESPACE + 'unique_metrics'))
if len(unique_metrics) == 0:
logger.info('no metrics in redis. try adding some - see README')
sleep(10)
continue
# Spawn processes
pids = []
for i in range(1, settings.ANALYZER_PROCESSES + 1):
if i > len(unique_metrics):
logger.info('WARNING: skyline is set for more cores than needed.')
break
p = Process(target=self.spin_process, args=(i, unique_metrics))
pids.append(p)
p.start()
# Send wait signal to zombie processes
for p in pids:
p.join()
# Grab data from the queue and populate dictionaries
exceptions = dict()
anomaly_breakdown = dict()
while 1:
try:
key, value = self.anomaly_breakdown_q.get_nowait()
if key not in anomaly_breakdown.keys():
anomaly_breakdown[key] = value
else:
anomaly_breakdown[key] += value
except Empty:
break
while 1:
try:
key, value = self.exceptions_q.get_nowait()
if key not in exceptions.keys():
exceptions[key] = value
else:
exceptions[key] += value
except Empty:
break
# Send alerts
if settings.ENABLE_ALERTS:
for alert in settings.ALERTS:
for metric in self.anomalous_metrics:
if alert[0] in metric[1]:
cache_key = 'last_alert.%s.%s' % (alert[1], metric[1])
try:
last_alert = self.ring.run('get', cache_key)
if not last_alert:
self.ring.run('setex', cache_key, alert[2], packb(metric[0]))
trigger_alert(alert, metric)
except Exception as e:
logger.error("couldn't send alert: %s" % e)
# Log progress
logger.info('seconds to run :: %.2f' % (time() - now))
logger.info('total metrics :: %d' % len(unique_metrics))
logger.info('total analyzed :: %d' % (len(unique_metrics) - sum(exceptions.values())))
logger.info('total anomalies :: %d' % len(self.anomalous_metrics))
logger.info('exception stats :: %s' % exceptions)
logger.info('anomaly breakdown :: %s' % anomaly_breakdown)
# Log to Graphite
if settings.GRAPHITE_HOST != '':
host = settings.GRAPHITE_HOST.replace('http://', '')
system('echo skyline.analyzer.run_time %.2f %s | nc -w 3 %s 2003' % ((time() - now), now, host))
system('echo skyline.analyzer.total_analyzed %d %s | nc -w 3 %s 2003' % ((len(unique_metrics) - sum(exceptions.values())), now, host))
# Check canary metric
raw_series = self.ring.run('get', settings.FULL_NAMESPACE + settings.CANARY_METRIC)
if raw_series is not None:
unpacker = Unpacker(use_list = False)
unpacker.feed(raw_series)
timeseries = list(unpacker)
time_human = (timeseries[-1][0] - timeseries[0][0]) / 3600
projected = 24 * (time() - now) / time_human
logger.info('canary duration :: %.2f' % time_human)
if settings.GRAPHITE_HOST != '':
host = settings.GRAPHITE_HOST.replace('http://', '')
system('echo skyline.analyzer.duration %.2f %s | nc -w 3 %s 2003' % (time_human, now, host))
system('echo skyline.analyzer.projected %.2f %s | nc -w 3 %s 2003' % (projected, now, host))
# Reset counters
self.anomalous_metrics[:] = []
# Sleep if it went too fast
if time() - now < 5:
logger.info('sleeping due to low run time...')
sleep(10)
def run(self):
"""
Called when the process intializes.
"""
while 1:
now = time()
# Make sure Redis is up
try:
self.ring.check_connections()
except:
sleep(10)
self.ring = RedisRing(settings.REDIS_BACKENDS)
continue
# Discover unique metrics
unique_metrics = list(self.ring.run('smembers', settings.FULL_NAMESPACE + 'unique_metrics'))
if len(unique_metrics) == 0:
logger.info('no metrics in redis. try adding some - see README')
sleep(10)
continue
# Spawn processes
pids = []
for i in range(1, settings.ANALYZER_PROCESSES + 1):
if i > len(unique_metrics):
logger.info('WARNING: skyline is set for more cores than needed.')
break
p = Process(target=self.spin_process, args=(i, unique_metrics))
pids.append(p)
p.start()
# Send wait signal to zombie processes
for p in pids:
p.join()
# Grab data from the queue and populate dictionaries
exceptions = dict()
anomaly_breakdown = dict()
while 1:
try:
key, value = self.anomaly_breakdown_q.get_nowait()
if key not in anomaly_breakdown.keys():
anomaly_breakdown[key] = value
else:
anomaly_breakdown[key] += value
except Empty:
break
while 1:
try:
key, value = self.exceptions_q.get_nowait()
if key not in exceptions.keys():
exceptions[key] = value
else:
exceptions[key] += value
except Empty:
break
# Send alerts
if settings.ENABLE_ALERTS:
for alert in settings.ALERTS:
for metric in self.anomalous_metrics:
if alert[0] in metric[1]:
cache_key = 'last_alert.%s.%s' % (alert[1], metric[1])
try:
last_alert = self.ring.run('get', cache_key)
if not last_alert:
self.ring.run('setex', cache_key, alert[2], packb(metric[0]))
trigger_alert(alert, metric)
except Exception as e:
logger.error("couldn't send alert: %s" % e)
# Log progress
logger.info('seconds to run :: %.2f' % (time() - now))
logger.info('total metrics :: %d' % len(unique_metrics))
logger.info('total analyzed :: %d' % (len(unique_metrics) - sum(exceptions.values())))
logger.info('total anomalies :: %d' % len(self.anomalous_metrics))
logger.info('exception stats :: %s' % exceptions)
logger.info('anomaly breakdown :: %s' % anomaly_breakdown)
# Log to Graphite
if settings.GRAPHITE_HOST != '':
host = settings.GRAPHITE_HOST.replace('http://', '')
system('echo skyline.analyzer.run_time %.2f %s | nc -w 3 %s 2003' % ((time() - now), now, host))
system('echo skyline.analyzer.total_analyzed %d %s | nc -w 3 %s 2003' % ((len(unique_metrics) - sum(exceptions.values())), now, host))
# Check canary metric
raw_series = self.ring.run('get', settings.FULL_NAMESPACE + settings.CANARY_METRIC)
if raw_series is not None:
unpacker = Unpacker(use_list = False)
unpacker.feed(raw_series)
timeseries = list(unpacker)
time_human = (timeseries[-1][0] - timeseries[0][0]) / 3600
projected = 24 * (time() - now) / time_human
logger.info('canary duration :: %.2f' % time_human)
if settings.GRAPHITE_HOST != '':
host = settings.GRAPHITE_HOST.replace('http://', '')
system('echo skyline.analyzer.duration %.2f %s | nc -w 3 %s 2003' % (time_human, now, host))
system('echo skyline.analyzer.projected %.2f %s | nc -w 3 %s 2003' % (projected, now, host))
# Reset counters
self.anomalous_metrics[:] = []
# Sleep if it went too fast
if time() - now < 5:
logger.info('sleeping due to low run time...')
sleep(10)
class Worker(Process):
"""
The worker processes chunks from the queue and appends
the latest datapoints to their respective timesteps in Redis.
"""
def __init__(self, parent_pid, context, canary=False):
super(Worker, self).__init__()
self.context = context
self.ring = RedisRing(settings.REDIS_BACKENDS)
self.parent_pid = parent_pid
self.daemon = True
self.canary = canary
def check_if_parent_is_alive(self):
"""
Self explanatory.
"""
try:
kill(self.parent_pid, 0)
except:
exit(0)
def in_skip_list(self, metric_name):
"""
Check if the metric is in SKIP_LIST.
"""
for to_skip in settings.SKIP_LIST:
if to_skip in metric_name:
return True
return False
def run(self):
"""
Called when the process intializes.
"""
logger.info('started worker')
FULL_NAMESPACE = settings.FULL_NAMESPACE
MINI_NAMESPACE = settings.MINI_NAMESPACE
MAX_RESOLUTION = settings.MAX_RESOLUTION
self.conn = self.context.socket(zmq.PULL)
self.conn.connect(
'{0}:{0}'.format(settings.RELAY_HOST, settings.RELAY_PUBLISH_PORT))
self.poller = zmq.Poller()
self.poller.register(self.conn, zmq.POLLIN)
while 1:
sockets = dict(self.poller.poll())
if self.conn in sockets and sockets[self.conn] == zmq.POLLIN:
# Make sure Redis is up
try:
self.ring.check_connections()
except:
sleep(10)
self.ring = RedisRing(settings.REDIS_BACKENDS)
continue
try:
# Get a chunk from the queue with a 15 second timeout
chunk = self.q.get(True, 15)
now = time()
for metric in chunk:
# Check if we should skip it
if self.in_skip_list(metric[0]):
continue
# Bad data coming in
if metric[1][0] < now - MAX_RESOLUTION:
continue
for ns in [FULL_NAMESPACE, MINI_NAMESPACE]:
key = ''.join((ns, metric[0]))
self.ring.run('append', key, packb(metric[1]))
ukey = ''.join((ns,'unique_metrics.',metric[0]))
self.ring.run('sadd', ukey, key)
except Exception as e:
logger.error("worker error: " + str(e))
