46ad661c7f
in translate_compute_flavor_and_image of tosca_compute.py Added UT cases. Closes-bug: #1432086 Change-Id: I44c47b88c57b39dea66cb86b5b4e8a4f6baa5973
175 lines
7.8 KiB
Python
Executable File
175 lines
7.8 KiB
Python
Executable File
#
|
|
# 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 translator.hot.syntax.hot_resource import HotResource
|
|
|
|
# A design issue to be resolved is how to translate the generic TOSCA server
|
|
# properties to OpenStack flavors and images. At the Atlanta design summit,
|
|
# there was discussion on using Glance to store metadata and Graffiti to
|
|
# describe artifacts. We will follow these projects to see if they can be
|
|
# leveraged for this TOSCA translation.
|
|
# For development purpose at this time, we temporarily hardcode a list of
|
|
# flavors and images here
|
|
FLAVORS = {'m1.xlarge': {'mem_size': 16384, 'disk_size': 160, 'num_cpus': 8},
|
|
'm1.large': {'mem_size': 8192, 'disk_size': 80, 'num_cpus': 4},
|
|
'm1.medium': {'mem_size': 4096, 'disk_size': 40, 'num_cpus': 2},
|
|
'm1.small': {'mem_size': 2048, 'disk_size': 20, 'num_cpus': 1},
|
|
'm1.tiny': {'mem_size': 512, 'disk_size': 1, 'num_cpus': 1},
|
|
'm1.micro': {'mem_size': 128, 'disk_size': 0, 'num_cpus': 1},
|
|
'm1.nano': {'mem_size': 64, 'disk_size': 0, 'num_cpus': 1}}
|
|
|
|
IMAGES = {'ubuntu-software-config-os-init': {'architecture': 'x86_64',
|
|
'type': 'Linux',
|
|
'distribution': 'Ubuntu',
|
|
'version': '14.04'},
|
|
'fedora-amd64-heat-config': {'architecture': 'x86_64',
|
|
'type': 'Linux',
|
|
'distribution': 'Fedora',
|
|
'version': '18'},
|
|
'F18-x86_64-cfntools': {'architecture': 'x86_64',
|
|
'type': 'Linux',
|
|
'distribution': 'Fedora',
|
|
'version': '19'},
|
|
'Fedora-x86_64-20-20131211.1-sda': {'architecture': 'x86_64',
|
|
'type': 'Linux',
|
|
'distribution': 'Fedora',
|
|
'version': '20'},
|
|
'cirros-0.3.1-x86_64-uec': {'architecture': 'x86_64',
|
|
'type': 'Linux',
|
|
'distribution': 'CirrOS',
|
|
'version': '0.3.1'}}
|
|
|
|
|
|
class ToscaCompute(HotResource):
|
|
'''Translate TOSCA node type tosca.nodes.Compute.'''
|
|
|
|
toscatype = 'tosca.nodes.Compute'
|
|
|
|
def __init__(self, nodetemplate):
|
|
super(ToscaCompute, self).__init__(nodetemplate,
|
|
type='OS::Nova::Server')
|
|
pass
|
|
|
|
def handle_properties(self):
|
|
self.properties = self.translate_compute_flavor_and_image(
|
|
self.nodetemplate.properties,
|
|
self.nodetemplate.get_capability('os'))
|
|
self.properties['user_data_format'] = 'SOFTWARE_CONFIG'
|
|
# TODO(anyone): handle user key
|
|
# hardcoded here for testing
|
|
self.properties['key_name'] = 'userkey'
|
|
|
|
# To be reorganized later based on new development in Glance and Graffiti
|
|
def translate_compute_flavor_and_image(self, properties, os_capability):
|
|
hot_properties = {}
|
|
tosca_props = {}
|
|
os_cap_props = {}
|
|
image = None
|
|
flavor = None
|
|
if properties:
|
|
for prop in properties:
|
|
tosca_props[prop.name] = prop.value
|
|
flavor = self._best_flavor(tosca_props)
|
|
if os_capability:
|
|
for prop in os_capability.get_properties_objects():
|
|
os_cap_props[prop.name] = prop.value
|
|
image = self._best_image(os_cap_props)
|
|
hot_properties['flavor'] = flavor
|
|
hot_properties['image'] = image
|
|
# TODO(anyone): consider adding the flavor or image as a template
|
|
# parameter if no match is found.
|
|
return hot_properties
|
|
|
|
def _best_flavor(self, properties):
|
|
# start with all flavors
|
|
match_all = FLAVORS.keys()
|
|
|
|
# TODO(anyone): Handle the case where the value contains something like
|
|
# get_input instead of a value.
|
|
# flavors that fit the CPU count
|
|
cpu = properties.get('num_cpus')
|
|
match_cpu = self._match_flavors(match_all, FLAVORS, 'num_cpus', cpu)
|
|
|
|
# flavors that fit the mem size
|
|
mem = properties.get('mem_size')
|
|
match_cpu_mem = self._match_flavors(match_cpu, FLAVORS,
|
|
'mem_size', mem)
|
|
# flavors that fit the disk size
|
|
disk = properties.get('disk_size')
|
|
match_cpu_mem_disk = self._match_flavors(match_cpu_mem, FLAVORS,
|
|
'disk_size', disk)
|
|
# if multiple match, pick the flavor with the least memory
|
|
# the selection can be based on other heuristic, e.g. pick one with the
|
|
# least total resource
|
|
if len(match_cpu_mem_disk) > 1:
|
|
return self._least_flavor(match_cpu_mem_disk, FLAVORS, 'mem_size')
|
|
elif len(match_cpu_mem_disk) == 1:
|
|
return match_cpu_mem_disk[0]
|
|
else:
|
|
return None
|
|
|
|
def _best_image(self, properties):
|
|
match_all = IMAGES.keys()
|
|
architecture = properties.get('architecture')
|
|
match_arch = self._match_images(match_all, IMAGES,
|
|
'architecture', architecture)
|
|
type = properties.get('type')
|
|
match_type = self._match_images(match_arch, IMAGES, 'type', type)
|
|
distribution = properties.get('distribution')
|
|
match_distribution = self._match_images(match_type, IMAGES,
|
|
'distribution',
|
|
distribution)
|
|
version = properties.get('version')
|
|
match_version = self._match_images(match_distribution, IMAGES,
|
|
'version', version)
|
|
|
|
if len(match_version):
|
|
return list(match_version)[0]
|
|
|
|
def _match_flavors(self, this_list, this_dict, attr, size):
|
|
'''Return from this list all flavors matching the attribute size.'''
|
|
if not size:
|
|
return this_list
|
|
matching_flavors = []
|
|
for flavor in this_list:
|
|
if isinstance(size, int):
|
|
if this_dict[flavor][attr] >= size:
|
|
matching_flavors.append(flavor)
|
|
return matching_flavors
|
|
|
|
def _least_flavor(self, this_list, this_dict, attr):
|
|
'''Return from this list the flavor with the smallest attr.'''
|
|
least_flavor = this_list[0]
|
|
for flavor in this_list:
|
|
if this_dict[flavor][attr] < this_dict[least_flavor][attr]:
|
|
least_flavor = flavor
|
|
return least_flavor
|
|
|
|
def _match_images(self, this_list, this_dict, attr, prop):
|
|
if not prop:
|
|
return this_list
|
|
matching_images = []
|
|
for image in this_list:
|
|
if this_dict[image][attr] == str(prop):
|
|
matching_images.append(image)
|
|
return matching_images
|
|
|
|
def get_hot_attribute(self, attribute, args):
|
|
attr = {}
|
|
# Convert from a TOSCA attribute for a nodetemplate to a HOT
|
|
# attribute for the matching resource. Unless there is additional
|
|
# runtime support, this should be a one to one mapping.
|
|
if attribute == 'ip_address':
|
|
attr['get_attr'] = [self.name, 'networks', '"private"', 0]
|
|
return attr
|