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|
"""
diskprediction with local predictor
"""
import json
import datetime
import _strptime
from threading import Event
import time
from mgr_module import MgrModule, CommandResult
# Importing scipy early appears to avoid a future deadlock when
# we try to do
#
# from .predictor import get_diskfailurepredictor_path
#
# in a command thread. See https://tracker.ceph.com/issues/42764
import scipy
TIME_FORMAT = '%Y%m%d-%H%M%S'
TIME_DAYS = 24*60*60
TIME_WEEK = TIME_DAYS * 7
class Module(MgrModule):
MODULE_OPTIONS = [
{
'name': 'sleep_interval',
'default': str(600),
},
{
'name': 'predict_interval',
'default': str(86400),
},
{
'name': 'predictor_model',
'default': 'prophetstor',
},
]
COMMANDS = []
def __init__(self, *args, **kwargs):
super(Module, self).__init__(*args, **kwargs)
# options
for opt in self.MODULE_OPTIONS:
setattr(self, opt['name'], opt['default'])
# other
self._run = True
self._event = Event()
def config_notify(self):
for opt in self.MODULE_OPTIONS:
setattr(self,
opt['name'],
self.get_module_option(opt['name']))
self.log.debug(' %s = %s', opt['name'], getattr(self, opt['name']))
if self.get_ceph_option('device_failure_prediction_mode') == 'local':
self._event.set()
def refresh_config(self):
for opt in self.MODULE_OPTIONS:
setattr(self,
opt['name'],
self.get_module_option(opt['name']))
self.log.debug(' %s = %s', opt['name'], getattr(self, opt['name']))
def handle_command(self, _, cmd):
self.log.debug('handle_command cmd: %s', cmd)
raise NotImplementedError(cmd['prefix'])
def self_test(self):
self.log.debug('self_test enter')
ret, out, err = self.predict_all_devices()
assert ret == 0
return 0, 'self test succeed', ''
def serve(self):
self.log.info('Starting diskprediction local module')
self.config_notify()
last_predicted = None
ls = self.get_store('last_predicted')
if ls:
try:
last_predicted = datetime.datetime.strptime(ls, TIME_FORMAT)
except ValueError:
pass
self.log.debug('Last predicted %s', last_predicted)
while self._run:
self.refresh_config()
mode = self.get_ceph_option('device_failure_prediction_mode')
if mode == 'local':
now = datetime.datetime.utcnow()
if not last_predicted:
next_predicted = now
else:
predicted_frequency = int(self.predict_interval) or 86400
seconds = (last_predicted - datetime.datetime.utcfromtimestamp(0)).total_seconds()
seconds -= seconds % predicted_frequency
seconds += predicted_frequency
next_predicted = datetime.datetime.utcfromtimestamp(seconds)
if last_predicted:
self.log.debug('Last scrape %s, next scrape due %s',
last_predicted.strftime(TIME_FORMAT),
next_predicted.strftime(TIME_FORMAT))
else:
self.log.debug('Last scrape never, next scrape due %s',
next_predicted.strftime(TIME_FORMAT))
if now >= next_predicted:
self.predict_all_devices()
last_predicted = now
self.set_store('last_predicted', last_predicted.strftime(TIME_FORMAT))
sleep_interval = int(self.sleep_interval) or 60
self.log.debug('Sleeping for %d seconds', sleep_interval)
self._event.wait(sleep_interval)
self._event.clear()
def shutdown(self):
self.log.info('Stopping')
self._run = False
self._event.set()
@staticmethod
def _convert_timestamp(predicted_timestamp, life_expectancy_day):
"""
:param predicted_timestamp: unit is nanoseconds
:param life_expectancy_day: unit is seconds
:return:
date format '%Y-%m-%d' ex. 2018-01-01
"""
return datetime.datetime.fromtimestamp(
predicted_timestamp / (1000 ** 3) + life_expectancy_day).strftime('%Y-%m-%d')
def _predict_life_expentancy(self, devid):
predicted_result = ''
health_data = {}
predict_datas = []
try:
r, outb, outs = self.remote('devicehealth', 'show_device_metrics', devid=devid, sample='')
if r != 0:
self.log.error('failed to get device %s health', devid)
health_data = {}
else:
health_data = json.loads(outb)
except Exception as e:
self.log.error('failed to get device %s health data due to %s', devid, str(e))
# initialize appropriate disk failure predictor model
from .predictor import get_diskfailurepredictor_path
if self.predictor_model == 'prophetstor':
from .predictor import PSDiskFailurePredictor
obj_predictor = PSDiskFailurePredictor()
ret = obj_predictor.initialize("{}/models/{}".format(get_diskfailurepredictor_path(), self.predictor_model))
if ret is not None:
self.log.error('Error initializing predictor')
return predicted_result
elif self.predictor_model == 'redhat':
from .predictor import RHDiskFailurePredictor
obj_predictor = RHDiskFailurePredictor()
ret = obj_predictor.initialize("{}/models/{}".format(get_diskfailurepredictor_path(), self.predictor_model))
if ret is not None:
self.log.error('Error initializing predictor')
return predicted_result
else:
self.log.error('invalid value received for MODULE_OPTIONS.predictor_model')
return predicted_result
if len(health_data) >= 6:
o_keys = sorted(health_data.keys(), reverse=True)
for o_key in o_keys:
# get values for current day (?)
dev_smart = {}
s_val = health_data[o_key]
# add all smart attributes
ata_smart = s_val.get('ata_smart_attributes', {})
for attr in ata_smart.get('table', []):
# get raw smart values
if attr.get('raw', {}).get('string') is not None:
if str(attr.get('raw', {}).get('string', '0')).isdigit():
dev_smart['smart_%s_raw' % attr.get('id')] = \
int(attr.get('raw', {}).get('string', '0'))
else:
if str(attr.get('raw', {}).get('string', '0')).split(' ')[0].isdigit():
dev_smart['smart_%s_raw' % attr.get('id')] = \
int(attr.get('raw', {}).get('string',
'0').split(' ')[0])
else:
dev_smart['smart_%s_raw' % attr.get('id')] = \
attr.get('raw', {}).get('value', 0)
# get normalized smart values
if attr.get('value') is not None:
dev_smart['smart_%s_normalized' % attr.get('id')] = \
attr.get('value')
# add power on hours manually if not available in smart attributes
if s_val.get('power_on_time', {}).get('hours') is not None:
dev_smart['smart_9_raw'] = int(s_val['power_on_time']['hours'])
# add device capacity
if s_val.get('user_capacity') is not None:
if s_val.get('user_capacity').get('bytes') is not None:
dev_smart['user_capacity'] = s_val.get('user_capacity').get('bytes')
else:
self.log.debug('user_capacity not found in smart attributes list')
# add device model
if s_val.get('model_name') is not None:
dev_smart['model_name'] = s_val.get('model_name')
# add vendor
if s_val.get('vendor') is not None:
dev_smart['vendor'] = s_val.get('vendor')
# if smart data was found, then add that to list
if dev_smart:
predict_datas.append(dev_smart)
if len(predict_datas) >= 12:
break
else:
self.log.error('unable to predict device due to health data records less than 6 days')
if len(predict_datas) >= 6:
predicted_result = obj_predictor.predict(predict_datas)
return predicted_result
def predict_life_expectancy(self, devid):
result = self._predict_life_expentancy(devid)
if result.lower() == 'good':
return 0, '>6w', ''
elif result.lower() == 'warning':
return 0, '>=2w and <=6w', ''
elif result.lower() == 'bad':
return 0, '<2w', ''
else:
return 0, 'unknown', ''
def _reset_device_life_expectancy(self, device_id):
result = CommandResult('')
self.send_command(result, 'mon', '', json.dumps({
'prefix': 'device rm-life-expectancy',
'devid': device_id
}), '')
ret, _, outs = result.wait()
if ret != 0:
self.log.error(
'failed to reset device life expectancy, %s' % outs)
return ret
def _set_device_life_expectancy(self, device_id, from_date, to_date=None):
result = CommandResult('')
if to_date is None:
self.send_command(result, 'mon', '', json.dumps({
'prefix': 'device set-life-expectancy',
'devid': device_id,
'from': from_date
}), '')
else:
self.send_command(result, 'mon', '', json.dumps({
'prefix': 'device set-life-expectancy',
'devid': device_id,
'from': from_date,
'to': to_date
}), '')
ret, _, outs = result.wait()
if ret != 0:
self.log.error(
'failed to set device life expectancy, %s' % outs)
return ret
def predict_all_devices(self):
self.log.debug('predict_all_devices')
devices = self.get('devices').get('devices', [])
for devInfo in devices:
if not devInfo.get('daemons'):
continue
if not devInfo.get('devid'):
continue
self.log.debug('%s' % devInfo)
result = self._predict_life_expentancy(devInfo['devid'])
if result == 'unknown':
self._reset_device_life_expectancy(devInfo['devid'])
continue
predicted = int(time.time() * (1000 ** 3))
if result.lower() == 'good':
life_expectancy_day_min = (TIME_WEEK * 6) + TIME_DAYS
life_expectancy_day_max = None
elif result.lower() == 'warning':
life_expectancy_day_min = (TIME_WEEK * 2)
life_expectancy_day_max = (TIME_WEEK * 6)
elif result.lower() == 'bad':
life_expectancy_day_min = 0
life_expectancy_day_max = (TIME_WEEK * 2) - TIME_DAYS
else:
predicted = None
life_expectancy_day_min = None
life_expectancy_day_max = None
if predicted and devInfo['devid'] and life_expectancy_day_min:
from_date = None
to_date = None
try:
if life_expectancy_day_min:
from_date = self._convert_timestamp(predicted, life_expectancy_day_min)
if life_expectancy_day_max:
to_date = self._convert_timestamp(predicted, life_expectancy_day_max)
self._set_device_life_expectancy(devInfo['devid'], from_date, to_date)
self._logger.info(
'succeed to set device {} life expectancy from: {}, to: {}'.format(
devInfo['devid'], from_date, to_date))
except Exception as e:
self._logger.error(
'failed to set device {} life expectancy from: {}, to: {}, {}'.format(
devInfo['devid'], from_date, to_date, str(e)))
else:
self._reset_device_life_expectancy(devInfo['devid'])
return 0, 'succeed to predicted all devices', ''
|
