-"""
-Copyright (c) 2015 SONATA-NFV
-ALL RIGHTS RESERVED.
-
-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.
-
-Neither the name of the SONATA-NFV [, ANY ADDITIONAL AFFILIATION]
-nor the names of its contributors may be used to endorse or promote
-products derived from this software without specific prior written
-permission.
-
-This work has been performed in the framework of the SONATA project,
-funded by the European Commission under Grant number 671517 through
-the Horizon 2020 and 5G-PPP programmes. The authors would like to
-acknowledge the contributions of their colleagues of the SONATA
-partner consortium (www.sonata-nfv.eu).
-"""
-
+# Copyright (c) 2015 SONATA-NFV and Paderborn University
+# ALL RIGHTS RESERVED.
+#
+# 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.
+#
+# Neither the name of the SONATA-NFV, Paderborn University
+# nor the names of its contributors may be used to endorse or promote
+# products derived from this software without specific prior written
+# permission.
+#
+# This work has been performed in the framework of the SONATA project,
+# funded by the European Commission under Grant number 671517 through
+# the Horizon 2020 and 5G-PPP programmes. The authors would like to
+# acknowledge the contributions of their colleagues of the SONATA
+# partner consortium (www.sonata-nfv.eu).
import time
import os
import unittest
from emuvim.dcemulator.resourcemodel.upb.simple import UpbSimpleCloudDcRM, UpbOverprovisioningCloudDcRM, UpbDummyRM
-
class testResourceModel(SimpleTestTopology):
"""
Test the general resource model API and functionality.
class DummyContainer(object):
def __init__(self):
- self.cpu_period = -1
- self.cpu_quota = -1
- self.mem_limit = -1
- self.memswap_limit = -1
+ # take defaukt values from son-emu
+ self.resources = dict(
+ cpu_period=-1,
+ cpu_quota=-1,
+ mem_limit=-1,
+ memswap_limit=-1
+ )
+ # self.cpu_period = self.resources['cpu_period']
+ # self.cpu_quota = self.resources['cpu_quota']
+ # self.mem_limit = self.resources['mem_limit']
+ # self.memswap_limit = self.resources['memswap_limit']
def updateCpuLimit(self, cpu_period, cpu_quota):
- self.cpu_period = cpu_period
- self.cpu_quota = cpu_quota
+ self.resources['cpu_period'] = cpu_period
+ self.resources['cpu_quota'] = cpu_quota
def updateMemoryLimit(self, mem_limit):
- self.mem_limit = mem_limit
+ self.resources['mem_limit'] = mem_limit
d = DummyContainer()
d.name = name
return d
-
-
class testUpbSimpleCloudDcRM(SimpleTestTopology):
"""
Test the UpbSimpleCloudDc resource model.
E_MEM = 512
MAX_MU = 2048
# create dummy resource model environment
- reg = ResourceModelRegistrar(dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
+ reg = ResourceModelRegistrar(
+ dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
rm = UpbSimpleCloudDcRM(max_cu=MAX_CU, max_mu=MAX_MU)
reg.register("test_dc", rm)
c1 = createDummyContainerObject("c1", flavor="tiny")
rm.allocate(c1) # calculate allocation
- self.assertEqual(float(c1.cpu_quota) / c1.cpu_period, E_CPU / MAX_CU * 0.5) # validate compute result
- self.assertEqual(float(c1.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 32) # validate memory result
+ # validate compute result
+ self.assertEqual(float(
+ c1.resources['cpu_quota']) / c1.resources['cpu_period'], E_CPU / MAX_CU * 0.5)
+ # validate memory result
+ self.assertEqual(
+ float(c1.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 32)
c2 = createDummyContainerObject("c2", flavor="small")
rm.allocate(c2) # calculate allocation
- self.assertEqual(float(c2.cpu_quota) / c2.cpu_period, E_CPU / MAX_CU * 1) # validate compute result
- self.assertEqual(float(c2.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 128) # validate memory result
+ # validate compute result
+ self.assertEqual(float(
+ c2.resources['cpu_quota']) / c2.resources['cpu_period'], E_CPU / MAX_CU * 1)
+ # validate memory result
+ self.assertEqual(
+ float(c2.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 128)
c3 = createDummyContainerObject("c3", flavor="medium")
rm.allocate(c3) # calculate allocation
- self.assertEqual(float(c3.cpu_quota) / c3.cpu_period, E_CPU / MAX_CU * 4) # validate compute result
- self.assertEqual(float(c3.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 256) # validate memory result
+ # validate compute result
+ self.assertEqual(float(
+ c3.resources['cpu_quota']) / c3.resources['cpu_period'], E_CPU / MAX_CU * 4)
+ # validate memory result
+ self.assertEqual(
+ float(c3.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 256)
c4 = createDummyContainerObject("c4", flavor="large")
rm.allocate(c4) # calculate allocation
- self.assertEqual(float(c4.cpu_quota) / c4.cpu_period, E_CPU / MAX_CU * 8) # validate compute result
- self.assertEqual(float(c4.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 512) # validate memory result
+ # validate compute result
+ self.assertEqual(float(
+ c4.resources['cpu_quota']) / c4.resources['cpu_period'], E_CPU / MAX_CU * 8)
+ # validate memory result
+ self.assertEqual(
+ float(c4.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 512)
c5 = createDummyContainerObject("c5", flavor="xlarge")
rm.allocate(c5) # calculate allocation
- self.assertEqual(float(c5.cpu_quota) / c5.cpu_period, E_CPU / MAX_CU * 16) # validate compute result
- self.assertEqual(float(c5.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 1024) # validate memory result
-
+ # validate compute result
+ self.assertEqual(float(
+ c5.resources['cpu_quota']) / c5.resources['cpu_period'], E_CPU / MAX_CU * 16)
+ # validate memory result
+ self.assertEqual(
+ float(c5.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 1024)
def testAllocationCpuLimit(self):
"""
E_MEM = 512
MAX_MU = 4096
# create dummy resource model environment
- reg = ResourceModelRegistrar(dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
+ reg = ResourceModelRegistrar(
+ dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
rm = UpbSimpleCloudDcRM(max_cu=MAX_CU, max_mu=MAX_MU)
reg.register("test_dc", rm)
E_MEM = 512
MAX_MU = 2048
# create dummy resource model environment
- reg = ResourceModelRegistrar(dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
+ reg = ResourceModelRegistrar(
+ dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
rm = UpbSimpleCloudDcRM(max_cu=MAX_CU, max_mu=MAX_MU)
reg.register("test_dc", rm)
Test the free procedure.
:return:
"""
- # config
- E_CPU = 1.0
- MAX_CU = 100
# create dummy resource model environment
- reg = ResourceModelRegistrar(dc_emulation_max_cpu=1.0, dc_emulation_max_mem=512)
+ reg = ResourceModelRegistrar(
+ dc_emulation_max_cpu=1.0, dc_emulation_max_mem=512)
rm = UpbSimpleCloudDcRM(max_cu=100, max_mu=100)
reg.register("test_dc", rm)
c1 = createDummyContainerObject("c6", flavor="tiny")
self.assertTrue(len(r._allocated_compute_instances) == 1)
# check if there is a real limitation set for containers cgroup
- # deactivated for now, seems not to work in docker-in-docker setup used in CI
- self.assertEqual(float(tc1.cpu_quota)/tc1.cpu_period, 0.005)
+ # deactivated for now, seems not to work in docker-in-docker setup used
+ # in CI
+ self.assertEqual(
+ float(tc1.resources['cpu_quota']) / tc1.resources['cpu_period'], 0.005)
# check if free was called during stopCompute
self.dc[0].stopCompute("tc1")
E_MEM = 512
MAX_MU = 2048
# create dummy resource model environment
- reg = ResourceModelRegistrar(dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
+ reg = ResourceModelRegistrar(
+ dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
rm = UpbOverprovisioningCloudDcRM(max_cu=MAX_CU, max_mu=MAX_MU)
reg.register("test_dc", rm)
c1 = createDummyContainerObject("c1", flavor="small")
rm.allocate(c1) # calculate allocation
- self.assertAlmostEqual(float(c1.cpu_quota) / c1.cpu_period, E_CPU / MAX_CU * 1.0, places=5)
- self.assertAlmostEqual(float(c1.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 128)
+ self.assertAlmostEqual(float(
+ c1.resources['cpu_quota']) / c1.resources['cpu_period'], E_CPU / MAX_CU * 1.0, places=5)
+ self.assertAlmostEqual(
+ float(c1.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 128)
self.assertAlmostEqual(rm.cpu_op_factor, 1.0)
c2 = createDummyContainerObject("c2", flavor="small")
rm.allocate(c2) # calculate allocation
- self.assertAlmostEqual(float(c2.cpu_quota) / c2.cpu_period, E_CPU / MAX_CU * 1.0, places=5)
- self.assertAlmostEqual(float(c2.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 128)
+ self.assertAlmostEqual(float(
+ c2.resources['cpu_quota']) / c2.resources['cpu_period'], E_CPU / MAX_CU * 1.0, places=5)
+ self.assertAlmostEqual(
+ float(c2.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 128)
self.assertAlmostEqual(rm.cpu_op_factor, 1.0)
c3 = createDummyContainerObject("c3", flavor="small")
rm.allocate(c3) # calculate allocation
- self.assertAlmostEqual(float(c3.cpu_quota) / c3.cpu_period, E_CPU / MAX_CU * 1.0, places=5)
- self.assertAlmostEqual(float(c3.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 128)
+ self.assertAlmostEqual(float(
+ c3.resources['cpu_quota']) / c3.resources['cpu_period'], E_CPU / MAX_CU * 1.0, places=5)
+ self.assertAlmostEqual(
+ float(c3.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 128)
self.assertAlmostEqual(rm.cpu_op_factor, 1.0)
# from this container onwards, we should go to over provisioning mode:
c4 = createDummyContainerObject("c4", flavor="small")
rm.allocate(c4) # calculate allocation
- self.assertAlmostEqual(float(c4.cpu_quota) / c4.cpu_period, E_CPU / MAX_CU * (float(3) / 4), places=5)
- self.assertAlmostEqual(float(c4.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 128, places=5)
+ self.assertAlmostEqual(float(
+ c4.resources['cpu_quota']) / c4.resources['cpu_period'], E_CPU / MAX_CU * (float(3) / 4), places=5)
+ self.assertAlmostEqual(float(
+ c4.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 128, places=5)
self.assertAlmostEqual(rm.cpu_op_factor, 0.75)
c5 = createDummyContainerObject("c5", flavor="small")
rm.allocate(c5) # calculate allocation
- self.assertAlmostEqual(float(c5.cpu_quota) / c5.cpu_period, E_CPU / MAX_CU * (float(3) / 5), places=5)
- self.assertAlmostEqual(float(c5.mem_limit/1024/1024), float(E_MEM) / MAX_MU * 128)
+ self.assertAlmostEqual(float(
+ c5.resources['cpu_quota']) / c5.resources['cpu_period'], E_CPU / MAX_CU * (float(3) / 5), places=5)
+ self.assertAlmostEqual(
+ float(c5.resources['mem_limit'] / 1024 / 1024), float(E_MEM) / MAX_MU * 128)
self.assertAlmostEqual(rm.cpu_op_factor, 0.6)
E_MEM = 512
MAX_MU = 2048
# create dummy resource model environment
- reg = ResourceModelRegistrar(dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
+ reg = ResourceModelRegistrar(
+ dc_emulation_max_cpu=E_CPU, dc_emulation_max_mem=E_MEM)
rm = UpbDummyRM(max_cu=MAX_CU, max_mu=MAX_MU)
reg.register("test_dc", rm)
c2 = createDummyContainerObject("c2", flavor="small")
rm.allocate(c2) # calculate allocation
self.assertEqual(len(rm._allocated_compute_instances), 2)
-