The watcher.datasource.monasca Module¶

class watcher.datasource.monasca.MonascaHelper(osc=None)[source]¶

Bases: watcher.datasource.base.DataSourceBase

check_availability()[source]¶

get_host_airflow(resource_id, period, aggregate, granularity=None)[source]¶

get_host_cpu_usage(resource_id, period, aggregate, granularity=None)[source]¶

get_host_inlet_temperature(resource_id, period, aggregate, granularity=None)[source]¶

get_host_memory_usage(resource_id, period, aggregate, granularity=None)[source]¶

get_host_outlet_temperature(resource_id, period, aggregate, granularity=None)[source]¶

get_host_power(resource_id, period, aggregate, granularity=None)[source]¶

get_instance_cpu_usage(resource_id, period, aggregate, granularity=None)[source]¶

get_instance_l3_cache_usage(resource_id, period, aggregate, granularity=None)[source]¶

get_instance_memory_usage(resource_id, period, aggregate, granularity=None)[source]¶

get_instance_ram_allocated(resource_id, period, aggregate, granularity=None)[source]¶

get_instance_root_disk_allocated(resource_id, period, aggregate, granularity=None)[source]¶

list_metrics()[source]¶

query_retry(f, *args, **kwargs)[source]¶

statistic_aggregation(resource_id=None, meter_name=None, period=300, granularity=300, dimensions=None, aggregation='avg', group_by='*')[source]¶

Representing a statistic aggregate by operators

Parameters:

resource_id – id of resource to list statistics for. This param isn’t used in Monasca datasource. meter_name – meter names of which we want the statistics. period – Sampling period: In seconds. If no period is given, only one aggregate statistic is returned. If given, a faceted result will be returned, divided into given periods. Periods with no data are ignored. granularity – frequency of marking metric point, in seconds. This param isn’t used in Ceilometer datasource. dimensions – dimensions (dict). aggregation – Should be either ‘avg’, ‘count’, ‘min’ or ‘max’. group_by – list of columns to group the metrics to be returned.

Returns:

A list of dict with each dict being a distinct result row

statistics_list(meter_name, dimensions, start_time=None, end_time=None, period=None)[source]¶

List of statistics.