def inspect(self, metric_type, window):
"""Inspect a specific metric. Returns timeseries beteween now and
300 seconds before.
Args:
metric_type (str): Metric type.
window: Window (in seconds).
Returns:
list: List of timeseries.
"""
LOGGER.debug(
f'Inspecting metric "{metric_type}" in project "{self.project_id}"'
' ...')
metric = list(self.get(metric_type))[0]
LOGGER.info(metric)
metric_type = metric['type']
interval = types.TimeInterval()
now = time.time()
interval.end_time.seconds = int(now)
interval.end_time.nanos = int(
(now - interval.end_time.seconds) * 10**9)
interval.start_time.seconds = int(now - window)
interval.start_time.nanos = interval.end_time.nanos
results = list(
self.client.list_time_series(
self.project, 'metric.type = "%s"' % metric_type, interval,
enums.ListTimeSeriesRequest.TimeSeriesView.FULL))
return results
def inspect(self, metric_type, window, filters={}):
"""Inspect a specific metric. Returns timeseries beteween now and
300 seconds before.
Args:
metric_type (str): Metric type.
window: Window (in seconds).
filters (list): List of filters.
Returns:
list: List of timeseries.
"""
LOGGER.debug(
f'Inspecting metric "{metric_type}" in project "{self.project_id}"'
' ...'
)
metric = list(self.get(metric_type))[0]
LOGGER.info(metric)
metric_type = metric['type']
interval = types.TimeInterval()
now = time.time()
interval.end_time.seconds = int(now)
interval.end_time.nanos = int(
(now - interval.end_time.seconds) * 10**9)
interval.start_time.seconds = int(now - window)
interval.start_time.nanos = interval.end_time.nanos
query = f'metric.type = "{metric_type}"'
for filter_key, filter_value in filters.items():
query += f' {filter_key} = {filter_value}'
LOGGER.debug(f'Running query "{query}" ...')
results = list(
self.client.list_time_series(
self.project, query, interval,
enums.ListTimeSeriesRequest.TimeSeriesView.FULL))
return results
def _make_interval(end_time, start_time=None):
from google.cloud.monitoring_v3 import types
interval = types.TimeInterval()
interval.end_time.FromDatetime(end_time)
if start_time is not None:
interval.start_time.FromDatetime(start_time)
return interval
def inspect(self, metric_type, window, filters={}):
"""Inspect a specific metric. Returns timeseries beteween now and
300 seconds before.
Args:
metric_type (str): Metric type.
window: Window (in seconds).
filters (list): List of filters.
Returns:
list: List of timeseries.
"""
LOGGER.debug(
f'Inspecting metric "{metric_type}" in project "{self.project_id}"'
' ...')
metric = list(self.get(metric_type))[0]
LOGGER.info(metric)
metric_type = metric['type']
interval = types.TimeInterval()
now = time.time()
seconds = int(now)
nanos = int((now - seconds) * 10**9)
interval = TimeInterval({
"end_time": {
"seconds": seconds,
"nanos": nanos
},
"start_time": {
"seconds": (seconds - window),
"nanos": nanos
}
})
# TODO: Add custom aggregation filters
# aggregation = monitoring_v3.Aggregation({
# "alignment_period": {
# "seconds": 1200
# }, # 20 minutes
# "per_series_aligner":
# monitoring_v3.Aggregation.Aligner.ALIGN_MEAN,
# "cross_series_reducer":
# monitoring_v3.Aggregation.Reducer.REDUCE_MEAN,
# "group_by_fields": ["resource.zone"],
# })
query = f'metric.type = "{metric_type}"'
for filter_key, filter_value in filters.items():
query += f' {filter_key} = {filter_value}'
LOGGER.debug(f'Running query "{query}" ...')
results = self.client.list_time_series(
request={
"name": self.project,
"filter": query,
"interval": interval,
"view": ListTimeSeriesRequest.TimeSeriesView.FULL,
# "aggregation": aggregation # TODO: Uncomment this
})
return results
def _build_query_params(self, headers_only=False, page_size=None):
"""Return key-value pairs for the list_time_series API call.
:type headers_only: bool
:param headers_only:
Whether to omit the point data from the
:class:`~google.cloud.monitoring_v3.types.TimeSeries` objects.
:type page_size: int
:param page_size:
(Optional) The maximum number of points in each page of results
from this request. Non-positive values are ignored. Defaults
to a sensible value set by the API.
"""
params = {"name": self._project_path, "filter_": self.filter}
params["interval"] = types.TimeInterval()
params["interval"].end_time.FromDatetime(self._end_time)
if self._start_time:
params["interval"].start_time.FromDatetime(self._start_time)
if (
self._per_series_aligner
or self._alignment_period_seconds
or self._cross_series_reducer
or self._group_by_fields
):
params["aggregation"] = types.Aggregation(
per_series_aligner=self._per_series_aligner,
cross_series_reducer=self._cross_series_reducer,
group_by_fields=self._group_by_fields,
alignment_period={"seconds": self._alignment_period_seconds},
)
if headers_only:
params["view"] = enums.ListTimeSeriesRequest.TimeSeriesView.HEADERS
else:
params["view"] = enums.ListTimeSeriesRequest.TimeSeriesView.FULL
if page_size is not None:
params["page_size"] = page_size
return params
def _build_query_params(self, headers_only=False, page_size=None):
"""Return key-value pairs for the list_time_series API call.
:type headers_only: bool
:param headers_only:
Whether to omit the point data from the
:class:`~google.cloud.monitoring_v3.types.TimeSeries` objects.
:type page_size: int
:param page_size:
(Optional) A limit on the number of points to return per page.
"""
params = {'name': self._project_path, 'filter_': self.filter}
params['interval'] = types.TimeInterval()
params['interval'].end_time.FromDatetime(self._end_time)
if self._start_time:
params['interval'].start_time.FromDatetime(self._start_time)
if (self._per_series_aligner or self._alignment_period_seconds
or self._cross_series_reducer or self._group_by_fields):
params['aggregation'] = types.Aggregation(
per_series_aligner=self._per_series_aligner,
cross_series_reducer=self._cross_series_reducer,
group_by_fields=self._group_by_fields,
alignment_period={'seconds': self._alignment_period_seconds},
)
if headers_only:
params['view'] = enums.ListTimeSeriesRequest.TimeSeriesView.HEADERS
else:
params['view'] = enums.ListTimeSeriesRequest.TimeSeriesView.FULL
if page_size is not None:
params['page_size'] = page_size
return params
def P(timestamp, value):
interval = types.TimeInterval()
interval.start_time.FromJsonString(timestamp)
interval.end_time.FromJsonString(timestamp)
return types.Point(interval=interval, value={"double_value": value})
