250 lines
9.1 KiB
Python
250 lines
9.1 KiB
Python
# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import datetime
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import logging
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from django.utils import timezone
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from django.utils.translation import ugettext_lazy as _
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import pytz
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from horizon.utils import units
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from openstack_dashboard import api
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LOG = logging.getLogger(__name__)
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METER_API_MAPPINGS = {
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"instance": 'nova',
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"cpu": 'nova',
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"cpu_util": 'nova',
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"disk_read_requests": 'nova',
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"disk_write_requests": 'nova',
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"disk_read_bytes": 'nova',
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"disk_write_bytes": 'nova',
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"image": 'glance',
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"image_size": 'glance'
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}
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def calc_period(date_from, date_to, number_of_samples=400):
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if date_from and date_to:
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if date_to < date_from:
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# TODO(lsmola) propagate the Value error through Horizon
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# handler to the client with verbose message.
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raise ValueError(_("To date to must be greater than From date."))
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delta = date_to - date_from
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delta_in_seconds = delta.days * 24 * 3600 + delta.seconds
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period = delta_in_seconds / number_of_samples
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else:
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# If some date is missing, just set static window to one day.
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period = 3600 * 24
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return period
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def calc_date_args(date_from, date_to, date_options):
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# TODO(lsmola) all timestamps should probably work with
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# current timezone. And also show the current timezone in chart.
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if date_options == "other":
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try:
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if date_from:
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date_from = pytz.utc.localize(
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datetime.datetime.strptime(str(date_from), "%Y-%m-%d"))
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else:
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# TODO(lsmola) there should be probably the date
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# of the first sample as default, so it correctly
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# counts the time window. Though I need ordering
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# and limit of samples to obtain that.
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pass
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if date_to:
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date_to = pytz.utc.localize(
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datetime.datetime.strptime(str(date_to), "%Y-%m-%d"))
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# It returns the beginning of the day, I want the end of
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# the day, so I add one day without a second.
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date_to = (date_to + datetime.timedelta(days=1) -
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datetime.timedelta(seconds=1))
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else:
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date_to = timezone.now()
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except Exception:
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raise ValueError(_("The dates haven't been recognized"))
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else:
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try:
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date_to = timezone.now()
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date_from = date_to - datetime.timedelta(days=float(date_options))
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except Exception:
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raise ValueError(_("The time delta must be a number representing "
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"the time span in days"))
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return date_from, date_to
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def get_resource_name(request, resource_id, resource_name, meter_name):
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resource = None
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try:
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if resource_name == "resource_id":
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meter_name = 'instance' if "instance" in meter_name else meter_name
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api_type = METER_API_MAPPINGS.get(meter_name, '')
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if api_type == 'nova':
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resource = api.nova.server_get(request, resource_id)
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elif api_type == 'glance':
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resource = api.glance.image_get(request, resource_id)
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except Exception:
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LOG.info(_("Failed to get the resource name: %s"), resource_id,
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exc_info=True)
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return resource.name if resource else resource_id
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def series_for_meter(request, aggregates, group_by, meter_id,
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meter_name, stats_name, unit, label=None):
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"""Construct datapoint series for a meter from resource aggregates."""
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series = []
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for resource in aggregates:
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if resource.get_meter(meter_name):
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if label:
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name = label
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else:
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resource_name = ('id' if group_by == "project"
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else 'resource_id')
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resource_id = getattr(resource, resource_name)
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name = get_resource_name(request, resource_id,
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resource_name, meter_name)
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point = {'unit': unit,
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'name': name,
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'meter': meter_id,
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'data': []}
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for statistic in resource.get_meter(meter_name):
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date = statistic.duration_end[:19]
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value = float(getattr(statistic, stats_name))
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point['data'].append({'x': date, 'y': value})
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series.append(point)
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return series
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def normalize_series_by_unit(series):
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"""Transform series' values into a more human readable form:
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1) Determine the data point with the maximum value
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2) Decide the unit appropriate for this value (normalize it)
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3) Convert other values to this new unit, if necessary
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"""
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if not series:
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return series
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source_unit = target_unit = series[0]['unit']
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if not units.is_supported(source_unit):
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return series
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# Find the data point with the largest value and normalize it to
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# determine its unit - that will be the new unit
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maximum = max([d['y'] for point in series for d in point['data']])
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unit = units.normalize(maximum, source_unit)[1]
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# If unit needs to be changed, set the new unit for all data points
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# and convert all values to that unit
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if units.is_larger(unit, target_unit):
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target_unit = unit
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for i, point in enumerate(series[:]):
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if point['unit'] != target_unit:
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series[i]['unit'] = target_unit
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for j, d in enumerate(point['data'][:]):
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series[i]['data'][j]['y'] = units.convert(
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d['y'], source_unit, target_unit, fmt=True)[0]
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return series
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def get_unit(meter, request):
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sample_list = api.ceilometer.sample_list(request, meter, limit=1)
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unit = ""
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if sample_list:
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unit = sample_list[0].counter_unit
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return unit
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class ProjectAggregatesQuery(object):
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def __init__(self, request, date_from, date_to,
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period=None, additional_query=None):
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additional_query = additional_query or []
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if not period:
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period = calc_period(date_from, date_to)
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if date_from:
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additional_query.append({'field': 'timestamp',
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'op': 'ge',
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'value': date_from})
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if date_to:
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additional_query.append({'field': 'timestamp',
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'op': 'le',
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'value': date_to})
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self.request = request
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self.period = period
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self.additional_query = additional_query
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tenants, more = api.keystone.tenant_list(request,
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domain=None,
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paginate=False)
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self.queries = {}
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for tenant in tenants:
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tenant_query = [{
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"field": "project_id",
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"op": "eq",
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"value": tenant.id}]
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self.queries[tenant.name] = tenant_query
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def query(self, meter):
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unit = get_unit(meter, self.request)
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ceilometer_usage = api.ceilometer.CeilometerUsage(self.request)
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resources = ceilometer_usage.resource_aggregates_with_statistics(
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self.queries, [meter], period=self.period,
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stats_attr=None,
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additional_query=self.additional_query)
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return resources, unit
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class MeterQuery(ProjectAggregatesQuery):
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def __init__(self, *args, **kwargs):
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# pop filterfunc and add it later to self.
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filterfunc = kwargs.pop('filterfunc', None)
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super(MeterQuery, self).__init__(*args, **kwargs)
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self.filterfunc = filterfunc
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# Resetting the tenant based filter set in base class
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self.queries = None
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def query(self, meter):
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def filter_by_meter_name(resource):
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"""Function for filtering of the list of resources.
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Will pick the right resources according to currently selected
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meter.
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"""
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for link in resource.links:
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if link['rel'] == meter:
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# If resource has the currently chosen meter.
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return True
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return False
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unit = get_unit(meter, self.request)
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ceilometer_usage = api.ceilometer.CeilometerUsage(self.request)
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resources = ceilometer_usage.resources_with_statistics(
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self.queries, [meter],
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period=self.period,
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stats_attr=None,
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additional_query=self.additional_query,
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filter_func=filter_by_meter_name)
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return resources, unit
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