def mql_thresholds_single(project, quota_metric, threshold):
"""Returns all quota limit, usage, consumption percentage values.
Args:
project: obj, representing project details.
quota_metric: str, metric that is of interest.
threshold: int, the threshold to use for fetching the values.
Returns:
generator object, which will yield the results as a dict.
"""
mql = _MQL + _MQL_THRESHOLDS
mql %= (project.id, quota_metric, project.id, quota_metric, threshold)
results = monitoring_lib.query_timeseries_mql(project.id, mql)
rate_mql = _MQL_RATE + _MQL_THRESHOLDS
rate_mql %= (project.id, quota_metric, project.id, quota_metric, threshold)
rate_results = monitoring_lib.query_timeseries_mql(project.id, rate_mql)
# Since this returns both quota and limit, metric_type is empty.
return _results_as_json(project,
'',
itertools.chain.from_iterable(
(results, rate_results)),
data_op='to_alerts_dict',
additional_values={'threshold': threshold})
def mql_all(project):
"""Returns all quota limit, usage, consumption percentage values.
Args:
project: obj, representing project details.
Returns:
generator object, which will yield the results as a dict.
"""
mql = _MQL_ALL % (project.id, project.id)
results = monitoring_lib.query_timeseries_mql(project.id, mql)
rate_mql = _MQL_RATE_ALL % (project.id, project.id)
rate_results = monitoring_lib.query_timeseries_mql(project.id, rate_mql)
# Since this returns both quota and limit, metric_type is empty.
return _results_as_json(
project, '', itertools.chain.from_iterable((results, rate_results)))
def usage_mql_all(project):
"""Query and return quota metric usage details using MQL.
Args:
project: obj, representing project details.
Returns:
generator object, which will yield the results as a dict.
"""
mql = _USAGE_MQL_ALL % ', '.join(_USAGE_GROUP_BY_FIELDS)
results = monitoring_lib.query_timeseries_mql(project.id, mql)
return _results_as_json(project, _USAGE_METRIC_TYPE, results)
def limit_mql(project, quota_metric):
"""Query and return quota metric limit details using MQL.
Args:
project: obj, representing project details.
quota_metric: str, metric that is of interest.
Returns:
generator object, which will yield the results as a dict.
"""
mql = _LIMIT_MQL % (quota_metric, ', '.join(_LIMIT_GROUP_BY_FIELDS))
results = monitoring_lib.query_timeseries_mql(project.id, mql)
return _results_as_json(project, _LIMIT_METRIC_TYPE, results)