magnum/magnum/drivers/mesos_ubuntu_v1/monitor.py

72 lines
2.6 KiB
Python

# 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.
from oslo_serialization import jsonutils
from magnum.common import urlfetch
from magnum.conductor import monitors
class MesosMonitor(monitors.MonitorBase):
def __init__(self, context, cluster):
super(MesosMonitor, self).__init__(context, cluster)
self.data = {}
@property
def metrics_spec(self):
return {
'memory_util': {
'unit': '%',
'func': 'compute_memory_util',
},
'cpu_util': {
'unit': '%',
'func': 'compute_cpu_util',
},
}
def _build_url(self, url, protocol='http', port='80', path='/'):
return protocol + '://' + url + ':' + port + path
def _is_leader(self, state):
return state['leader'] == state['pid']
def pull_data(self):
self.data['mem_total'] = 0
self.data['mem_used'] = 0
self.data['cpu_total'] = 0
self.data['cpu_used'] = 0
for master_addr in self.cluster.master_addresses:
mesos_master_url = self._build_url(master_addr, port='5050',
path='/state')
master = jsonutils.loads(urlfetch.get(mesos_master_url))
if self._is_leader(master):
for slave in master['slaves']:
self.data['mem_total'] += slave['resources']['mem']
self.data['mem_used'] += slave['used_resources']['mem']
self.data['cpu_total'] += slave['resources']['cpus']
self.data['cpu_used'] += slave['used_resources']['cpus']
break
def compute_memory_util(self):
if self.data['mem_total'] == 0 or self.data['mem_used'] == 0:
return 0
else:
return self.data['mem_used'] * 100 / self.data['mem_total']
def compute_cpu_util(self):
if self.data['cpu_total'] == 0 or self.data['cpu_used'] == 0:
return 0
else:
return self.data['cpu_used'] * 100 / self.data['cpu_total']