Allow for global datasources preference from config

Allows to define a global preference for metric datasources with the
ability for strategy specific overrides. In addition, strategies which
do not require datasources have the config options removed this is
done to prevent confusion.

Some documentation that details the inner workings of selecting
datasources is updated.

Imports for some files in watcher/common have been changed to resolve
circular dependencies and now match the overall method to import
configuration.

Addtional datasources will be retrieved by the manager if the
datasource throws an error.

Implements: blueprint global-datasource-preference
Change-Id: I6fc455b288e338c20d2c4cfec5a0c95350bebc36
This commit is contained in:
Dantali0n
2019-03-21 15:17:44 +01:00
parent 92c94f61ca
commit bd8636f3f0
30 changed files with 234 additions and 126 deletions

100
watcher/datasources/base.py Normal file
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# -*- encoding: utf-8 -*-
# Copyright 2017 NEC Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import abc
class DataSourceBase(object):
METRIC_MAP = dict(host_cpu_usage=None,
host_memory_usage=None,
host_outlet_temp=None,
host_inlet_temp=None,
host_airflow=None,
host_power=None,
instance_cpu_usage=None,
instance_ram_usage=None,
instance_ram_allocated=None,
instance_l3_cache_usage=None,
instance_root_disk_size=None,
)
@abc.abstractmethod
def statistic_aggregation(self, resource_id=None, meter_name=None,
period=300, granularity=300, dimensions=None,
aggregation='avg', group_by='*'):
pass
@abc.abstractmethod
def list_metrics(self):
pass
@abc.abstractmethod
def check_availability(self):
pass
@abc.abstractmethod
def get_host_cpu_usage(self, resource_id, period, aggregate,
granularity=None):
pass
@abc.abstractmethod
def get_host_memory_usage(self, resource_id, period, aggregate,
granularity=None):
pass
@abc.abstractmethod
def get_host_outlet_temp(self, resource_id, period, aggregate,
granularity=None):
pass
@abc.abstractmethod
def get_host_inlet_temp(self, resource_id, period, aggregate,
granularity=None):
pass
@abc.abstractmethod
def get_host_airflow(self, resource_id, period, aggregate,
granularity=None):
pass
@abc.abstractmethod
def get_host_power(self, resource_id, period, aggregate, granularity=None):
pass
@abc.abstractmethod
def get_instance_cpu_usage(self, resource_id, period, aggregate,
granularity=None):
pass
@abc.abstractmethod
def get_instance_ram_usage(self, resource_id, period, aggregate,
granularity=None):
pass
@abc.abstractmethod
def get_instance_ram_allocated(self, resource_id, period, aggregate,
granularity=None):
pass
@abc.abstractmethod
def get_instance_l3_cache_usage(self, resource_id, period, aggregate,
granularity=None):
pass
@abc.abstractmethod
def get_instance_root_disk_size(self, resource_id, period, aggregate,
granularity=None):
pass