class Analyzer(Thread):
def __init__(self, parent_pid, storage):
"""
Initialize the Analyzer
"""
super(Analyzer, self).__init__()
self.redis_conn = StrictRedis(unix_socket_path = settings.REDIS_SOCKET_PATH)
self.daemon = True
self.parent_pid = parent_pid
self.current_pid = getpid()
self.lock = Lock()
self.exceptions = Manager().dict()
self.anomaly_breakdown = Manager().dict()
self.anomalous_metrics = Manager().list()
self.storage = storage
self.alerter = Alerter(storage)
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):
"""
Assign a bunch of metrics for a process to analyze.
"""
# Discover assigned metrics
keys_per_processor = int(ceil(float(len(unique_metrics)) / float(settings.ANALYZER_PROCESSES)))
if i == settings.ANALYZER_PROCESSES:
assigned_max = len(unique_metrics)
else:
assigned_max = i * 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.redis_conn.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, ts = run_selected_algorithm(timeseries)
# If it's anomalous, add it to list
if anomalous:
base_name = metric_name.replace(settings.FULL_NAMESPACE, '', 1)
metric = [datapoint, base_name, ts]
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 AttributeError:
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())
# 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
def send_mail(self, alert, metric):
"""
Send an alert email to the appropriate recipient
"""
msg = MIMEMultipart('alternative')
msg['Subject'] = '[skyline alert] ' + metric[1]
msg['From'] = settings.ALERT_SENDER
msg['To'] = alert[1]
link = '%s/render/?width=588&height=308&target=%s' % (settings.GRAPHITE_HOST, metric[1])
body = 'Anomalous value: %s <br> Next alert in: %s seconds <a href="%s"><img src="%s"/></a>' % (metric[0], alert[2], link, link)
msg.attach(MIMEText(body, 'html'))
s = SMTP('127.0.0.1')
s.sendmail(settings.ALERT_SENDER, alert[1], msg.as_string())
s.quit()
def run(self):
"""
Called when the process intializes.
"""
while 1:
now = time()
# Make sure Redis is up
try:
self.redis_conn.ping()
except:
logger.error('skyline can\'t connect to redis at socket path %s' % settings.REDIS_SOCKET_PATH)
sleep(10)
self.redis_conn = StrictRedis(unix_socket_path = settings.REDIS_SOCKET_PATH)
continue
# Discover unique metrics
unique_metrics = list(self.redis_conn.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()
# Send alerts
#if settings.ENABLE_ALERTS:
# for alert in settings.ALERTS:
# for metric in self.anomalous_metrics:
# if alert[0] in metric[1]:
# try:
# last_alert = self.redis_conn.get('last_alert.' + metric[1])
# if not last_alert:
# self.redis_conn.setex('last_alert.' + metric[1], alert[2], packb(metric[0]))
# self.send_mail(alert, metric)
# except Exception as e:
# logger.error("couldn't send alert: %s" % e)
# Write anomalous_metrics to static webapp directory
filename = path.abspath(path.join(path.dirname( __file__ ), '..', settings.ANOMALY_DUMP))
with open(filename, 'w') as fh:
# Make it JSONP with a handle_data() function
anomalous_metrics = list(self.anomalous_metrics)
anomalous_metrics.sort(key=operator.itemgetter(1))
fh.write('handle_data(%s)' % anomalous_metrics)
# process anomalous metrics
for metric in self.anomalous_metrics:
try:
last_save_key = 'last_save.%s.%s' % (metric[1], metric[2])
last_save = self.redis_conn.get(last_save_key)
if not last_save:
self.redis_conn.setex(last_save_key,
settings.SKIP_FREQUENCY, packb(metric[0]))
self.storage.save(metric)
if settings.ENABLE_ALERTS:
last_alert_key = 'last_alert.' + metric[1]
last_alert = self.redis_conn.get(last_alert_key)
if not last_alert:
self.redis_conn.setex(last_alert_key,
settings.SKIP_FREQUENCY, packb(metric[0]))
self.alerter.add(metric)
except Exception as e:
logger.error("Failed processing anomaly, pid: %s, metric: %s, error: %s",
getpid(), metric[1], e)
# send ready alerts
if settings.ENABLE_ALERTS:
try:
self.alerter.send_alerts()
except Exception as e:
logger.error("Failed sending alerts, error: %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(self.exceptions.values())))
logger.info('total anomalies :: %d' % len(self.anomalous_metrics))
logger.info('exception stats :: %s' % self.exceptions)
logger.info('anomaly breakdown :: %s' % self.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(self.exceptions.values())), now, host))
# Check canary metric
raw_series = self.redis_conn.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[:] = []
self.exceptions = Manager().dict()
self.anomaly_breakdown = Manager().dict()
# Sleep if it went too fast
if time() - now < 5:
logger.info('sleeping due to low run time...')
sleep(10)
class Analyzer(Thread):
def __init__(self, parent_pid, storage):
"""
Initialize the Analyzer
"""
super(Analyzer, self).__init__()
self.redis_conn = StrictRedis(
unix_socket_path=settings.REDIS_SOCKET_PATH)
self.daemon = True
self.parent_pid = parent_pid
self.current_pid = getpid()
self.lock = Lock()
self.exceptions = Manager().dict()
self.anomaly_breakdown = Manager().dict()
self.anomalous_metrics = Manager().list()
self.storage = storage
self.alerter = Alerter(storage)
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):
"""
Assign a bunch of metrics for a process to analyze.
"""
# Discover assigned metrics
keys_per_processor = int(
ceil(
float(len(unique_metrics)) /
float(settings.ANALYZER_PROCESSES)))
if i == settings.ANALYZER_PROCESSES:
assigned_max = len(unique_metrics)
else:
assigned_max = i * 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.redis_conn.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, ts = run_selected_algorithm(
timeseries)
# If it's anomalous, add it to list
if anomalous:
base_name = metric_name.replace(settings.FULL_NAMESPACE,
'', 1)
metric = [datapoint, base_name, ts]
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 AttributeError:
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())
# 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
def send_mail(self, alert, metric):
"""
Send an alert email to the appropriate recipient
"""
msg = MIMEMultipart('alternative')
msg['Subject'] = '[skyline alert] ' + metric[1]
msg['From'] = settings.ALERT_SENDER
msg['To'] = alert[1]
link = '%s/render/?width=588&height=308&target=%s' % (
settings.GRAPHITE_HOST, metric[1])
body = 'Anomalous value: %s <br> Next alert in: %s seconds <a href="%s"><img src="%s"/></a>' % (
metric[0], alert[2], link, link)
msg.attach(MIMEText(body, 'html'))
s = SMTP('127.0.0.1')
s.sendmail(settings.ALERT_SENDER, alert[1], msg.as_string())
s.quit()
def run(self):
"""
Called when the process intializes.
"""
while 1:
now = time()
# Make sure Redis is up
try:
self.redis_conn.ping()
except:
logger.error(
'skyline can\'t connect to redis at socket path %s' %
settings.REDIS_SOCKET_PATH)
sleep(10)
self.redis_conn = StrictRedis(
unix_socket_path=settings.REDIS_SOCKET_PATH)
continue
# Discover unique metrics
unique_metrics = list(
self.redis_conn.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()
# Send alerts
#if settings.ENABLE_ALERTS:
# for alert in settings.ALERTS:
# for metric in self.anomalous_metrics:
# if alert[0] in metric[1]:
# try:
# last_alert = self.redis_conn.get('last_alert.' + metric[1])
# if not last_alert:
# self.redis_conn.setex('last_alert.' + metric[1], alert[2], packb(metric[0]))
# self.send_mail(alert, metric)
# except Exception as e:
# logger.error("couldn't send alert: %s" % e)
# Write anomalous_metrics to static webapp directory
filename = path.abspath(
path.join(path.dirname(__file__), '..', settings.ANOMALY_DUMP))
with open(filename, 'w') as fh:
# Make it JSONP with a handle_data() function
anomalous_metrics = list(self.anomalous_metrics)
anomalous_metrics.sort(key=operator.itemgetter(1))
fh.write('handle_data(%s)' % anomalous_metrics)
# process anomalous metrics
for metric in self.anomalous_metrics:
try:
last_save_key = 'last_save.%s.%s' % (metric[1], metric[2])
last_save = self.redis_conn.get(last_save_key)
if not last_save:
self.redis_conn.setex(last_save_key,
settings.SKIP_FREQUENCY,
packb(metric[0]))
self.storage.save(metric)
if settings.ENABLE_ALERTS:
last_alert_key = 'last_alert.' + metric[1]
last_alert = self.redis_conn.get(last_alert_key)
if not last_alert:
self.redis_conn.setex(last_alert_key,
settings.SKIP_FREQUENCY,
packb(metric[0]))
self.alerter.add(metric)
except Exception as e:
logger.error(
"Failed processing anomaly, pid: %s, metric: %s, error: %s",
getpid(), metric[1], e)
# send ready alerts
if settings.ENABLE_ALERTS:
try:
self.alerter.send_alerts()
except Exception as e:
logger.error("Failed sending alerts, error: %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(self.exceptions.values())))
logger.info('total anomalies :: %d' %
len(self.anomalous_metrics))
logger.info('exception stats :: %s' % self.exceptions)
logger.info('anomaly breakdown :: %s' % self.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(self.exceptions.values())),
now, host))
# Check canary metric
raw_series = self.redis_conn.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[:] = []
self.exceptions = Manager().dict()
self.anomaly_breakdown = Manager().dict()
# Sleep if it went too fast
if time() - now < 5:
logger.info('sleeping due to low run time...')
sleep(10)