def parse_metric_data(metric):
try:
dimensions_ = metric.get('dimensions', {})
dimensions = utils.extract_member_dict(dimensions_)
except KeyError:
err = "Unsuitable Dimensions Value - %s" % str(dimensions_)
raise InvalidParameterValue(err)
self.check_dimensions(dimensions)
metric_name = metric.get('metric_name')
unit = metric.get('unit', 'None')
value = metric.get('value')
req_timestamp = metric.get('timestamp')
timestamp = req_timestamp if req_timestamp \
else utils.strtime(utils.utcnow())
timebound = (datetime.datetime.utcnow() -
datetime.timedelta(
seconds=FLAGS.get('statistics_ttl')))
if utils.parse_strtime(timestamp) < timebound:
err = "Stale metric data - %s" % timestamp
raise InvalidParameterValue(err)
self.check_metric_name(metric_name)
self.check_unit(unit)
return metric_name, dimensions, value, unit, timestamp
def describe_alarms_for_metric(self, context, namespace, metric_name,
dimensions=None, period=None,
statistic=None, unit=None, project_id=None):
if not (project_id and context.is_admin):
project_id = context.project_id
ret_dict = {}
ret_alarms = []
dimensions = utils.extract_member_dict(dimensions)
self.check_dimensions(dimensions)
self.check_metric_name(metric_name)
self.check_namespace(namespace)
self.check_statistic(statistic)
self.check_unit(unit)
alarms = self.monitor_api.describe_alarms_for_metric(
project_id=project_id, namespace=namespace,
metric_name=metric_name, dimensions=dimensions, period=period,
statistic=statistic, unit=unit
)
for k, v in alarms:
ret_alarms.append(to_alarm(v))
ret_dict['describe_alarms_for_metric_result'] = {'metric_alarms':
ret_alarms}
return ret_dict
def list_metrics(self, context, next_token=None, dimensions=None,
metric_name=None, namespace=None, project_id=None):
"""
Returns a list of valid metrics stored for the Synaps account owner.
Returned metrics can be used with get_metric_statics to obtain
statistical data for a given metric.
"""
def to_aws_metric(metric):
k, v = metric
return {
'dimensions': utils.dict_to_aws(v['dimensions']),
'metric_name': v['name'],
'namespace': v['namespace']
}
if not (project_id and context.is_admin):
project_id = context.project_id
dimensions = utils.extract_member_dict(dimensions)
self._check_dimension_filter(dimensions)
self.check_metric_name(metric_name)
self.check_namespace(namespace)
self.check_next_token(next_token)
metrics, next_token = self.monitor_api.list_metrics(project_id,
next_token, dimensions, metric_name, namespace)
metrics = map(to_aws_metric, metrics)
list_metrics_result = {'Metrics': metrics}
if next_token:
list_metrics_result['NextToken'] = next_token
return {'ListMetricsResult': list_metrics_result}
def describe_alarms_for_metric(self, context, namespace, metric_name,
dimensions=None, period=None,
statistic=None, unit=None, project_id=None):
if not (project_id and context.is_admin):
project_id = context.project_id
ret_dict = {}
ret_alarms = []
dimensions = utils.extract_member_dict(dimensions)
self.check_dimensions(dimensions)
self.check_metric_name(metric_name)
self.check_namespace(namespace)
self.check_statistic(statistic)
self.check_unit(unit)
alarms = self.monitor_api.describe_alarms_for_metric(
project_id=project_id, namespace=namespace,
metric_name=metric_name, dimensions=dimensions, period=period,
statistic=statistic, unit=unit
)
for k, v in alarms:
ret_alarms.append(to_alarm(v))
ret_dict['describe_alarms_for_metric_result'] = {'metric_alarms':
ret_alarms}
return ret_dict
def put_metric_alarm(self, context, alarm_name, comparison_operator,
evaluation_periods, metric_name, namespace, period,
statistic, threshold, alarm_actions=[],
insufficient_data_actions=[], ok_actions=[],
actions_enabled=True, alarm_description="",
dimensions={}, unit="", project_id=None):
"""
Create or updates an alarm and associates it with the specified
SPCS Synaps metric.
When this operation creates an alarm, the alarm state is immediately
set to INSUFFICIENT_DATA. The alarm is evaluated and its StateVale is
set appropriately.
"""
if not (project_id and context.is_admin):
project_id = context.project_id
d = utils.extract_member_dict(dimensions)
alarm_actions = utils.extract_member_list(alarm_actions)
insufficient_data_actions = \
utils.extract_member_list(insufficient_data_actions)
ok_actions = utils.extract_member_list(ok_actions)
self.check_alarm_description(alarm_description)
self.check_alarm_name(alarm_name)
self.check_comparison_operator(comparison_operator)
self.check_dimensions(dimensions)
self.check_metric_name(metric_name)
self.check_namespace(namespace)
self.check_statistic(statistic)
self.check_unit(unit)
self._validate_period(period)
self._validate_evaluation_periods(evaluation_periods)
self.validate_put_metric_alarm(period, evaluation_periods)
metricalarm = monitor.MetricAlarm(
alarm_name=alarm_name,
comparison_operator=comparison_operator,
evaluation_periods=evaluation_periods,
metric_name=metric_name,
namespace=namespace,
period=period,
statistic=statistic,
threshold=threshold,
actions_enabled=actions_enabled,
alarm_actions=alarm_actions,
alarm_description=alarm_description,
dimensions=d,
insufficient_data_actions=insufficient_data_actions,
ok_actions=ok_actions,
unit=unit
)
self.monitor_api.put_metric_alarm(project_id, metricalarm)
return {}
def get_metric_statistics(self, context, end_time, metric_name,
namespace, period, start_time, statistics,
unit=None, dimensions=None, project_id=None):
"""
Gets statistics for the specified metric.
"""
def stat_to_datapoint(stat):
"""
단위 변경 및 형식 변경
"""
timestamp, values = stat
ret = {}
ret['Timestamp'] = timestamp
for statistic, value in values.iteritems():
if statistic == "SampleCount":
ret['Unit'] = "Count"
ret[statistic] = value
else:
ret['Unit'] = (unit if unit != 'None' else None)
ret[statistic] = utils.to_unit(value, unit)
return ret
if not (project_id and context.is_admin):
project_id = context.project_id
end_time = utils.parse_strtime(end_time)
start_time = utils.parse_strtime(start_time)
dimensions = utils.extract_member_dict(dimensions)
statistics = utils.extract_member_list(statistics)
self.check_dimensions(dimensions)
self.check_metric_name(metric_name)
self.check_namespace(namespace)
self.check_statistics(statistics)
self.check_unit(unit)
self._validate_period(period)
self.validate_get_metric_statistics(start_time, end_time, period)
stats, unit = self.monitor_api.get_metric_statistics(
project_id, end_time,
metric_name, namespace,
period, start_time,
statistics, unit,
dimensions)
datapoints = map(stat_to_datapoint, stats)
label = metric_name
return {'GetMetricStatisticsResult': {'Datapoints': datapoints,
'Label': label}}
def parse_metric_data(metric):
try:
dimensions_ = metric.get('dimensions', {})
dimensions = utils.extract_member_dict(dimensions_)
except KeyError:
err = "Unsuitable Dimensions Value - %s" % str(dimensions_)
raise InvalidParameterValue(err)
metric_name = metric.get('metric_name')
unit = metric.get('unit', 'None')
value = metric.get('value')
req_timestamp = metric.get('timestamp')
timestamp = req_timestamp if req_timestamp \
else utils.strtime(utils.utcnow())
self.check_metric_name(metric_name)
self.check_unit(unit)
return metric_name, dimensions, value, unit, timestamp
def list_metrics(self, context, next_token=None, dimensions=None,
metric_name=None, namespace=None, project_id=None):
"""
Returns a list of valid metrics stored for the Synaps account owner.
Returned metrics can be used with get_metric_statics to obtain
statistical data for a given metric.
"""
def to_aws_metric(metric):
k, v = metric
return {
'dimensions': utils.dict_to_aws(v['dimensions']),
'metric_name': v['name'],
'namespace': v['namespace']
}
if not (project_id and context.is_admin):
project_id = context.project_id
dimensions = utils.extract_member_dict(dimensions)
self.check_dimensions(dimensions)
self.check_metric_name(metric_name)
self.check_namespace(namespace)
self.check_next_token(next_token)
metrics = self.monitor_api.list_metrics(project_id, next_token,
dimensions, metric_name,
namespace)
ret_list = []
for i, (k, v) in enumerate(metrics):
if i >= 500:
ret_next_token = k
break
ret_list.append(to_aws_metric((k, v)))
else:
ret_next_token = None
metrics = map(to_aws_metric, metrics)
list_metrics_result = {'Metrics': ret_list}
if ret_next_token:
list_metrics_result['NextToken'] = str(ret_next_token)
return {'ListMetricsResult': list_metrics_result}
def put_metric_alarm(self, context, alarm_name, comparison_operator,
evaluation_periods, metric_name, namespace, period,
statistic, threshold, alarm_actions=[],
insufficient_data_actions=[], ok_actions=[],
actions_enabled=True, alarm_description="",
dimensions={}, unit="", project_id=None):
"""
Create or updates an alarm and associates it with the specified
SPCS Synaps metric.
When this operation creates an alarm, the alarm state is immediately
set to INSUFFICIENT_DATA. The alarm is evaluated and its StateVale is
set appropriately.
"""
if not (project_id and context.is_admin):
project_id = context.project_id
d = utils.extract_member_dict(dimensions)
alarm_actions = utils.extract_member_list(alarm_actions)
insufficient_data_actions = \
utils.extract_member_list(insufficient_data_actions)
ok_actions = utils.extract_member_list(ok_actions)
self.check_alarm_description(alarm_description)
self.check_alarm_name(alarm_name)
self._check_admin_alarm([alarm_name], context.is_admin)
self.check_comparison_operator(comparison_operator)
self.check_dimensions(dimensions)
self.check_metric_name(metric_name)
self.check_namespace(namespace)
self.check_statistic(statistic)
self.check_unit(unit)
self._validate_period(period)
self._validate_evaluation_periods(evaluation_periods)
self.validate_put_metric_alarm(period, evaluation_periods)
self._validate_instanceaction(ok_actions, project_id, context)
self._validate_instanceaction(insufficient_data_actions, project_id,
context)
self._validate_instanceaction(alarm_actions, project_id, context)
try:
metricalarm = monitor.MetricAlarm(
alarm_name=alarm_name,
comparison_operator=comparison_operator,
evaluation_periods=evaluation_periods,
metric_name=metric_name,
namespace=namespace,
period=period,
statistic=statistic,
threshold=threshold,
actions_enabled=actions_enabled,
alarm_actions=alarm_actions,
alarm_description=alarm_description,
dimensions=d,
insufficient_data_actions=insufficient_data_actions,
ok_actions=ok_actions,
unit=unit
)
except AssertionError as e:
LOG.exception(e)
err = "Unsuitable MetricAlarm Value(%s)" % str(e)
raise InvalidParameterValue(err)
self.monitor_api.put_metric_alarm(context, project_id, metricalarm)
return {}
