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#
# 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 logging
from toscaparser.utils.gettextutils import _
from translator.common import flavors as nova_flavors
from translator.common import images as glance_images
import translator.common.utils
from translator.hot.syntax.hot_resource import HotResource
log = logging.getLogger('heat-translator')
# Name used to dynamically load appropriate map class.
TARGET_CLASS_NAME = 'ToscaCompute'
class ToscaCompute(HotResource):
"""Translate TOSCA node type tosca.nodes.Compute."""
COMPUTE_HOST_PROP = (DISK_SIZE, MEM_SIZE, NUM_CPUS) = \
('disk_size', 'mem_size', 'num_cpus')
COMPUTE_OS_PROP = (ARCHITECTURE, DISTRIBUTION, TYPE, VERSION) = \
('architecture', 'distribution', 'type', 'version')
IMAGE_OS_PROP = (OS_DISTRO, OS_TYPE, OS_VERSION) = \
('os_distro', 'os_type', 'os_version')
toscatype = 'tosca.nodes.Compute'
ALLOWED_NOVA_SERVER_PROPS = \
('admin_pass', 'availability_zone', 'block_device_mapping',
'block_device_mapping_v2', 'config_drive', 'diskConfig', 'flavor',
'flavor_update_policy', 'image', 'image_update_policy', 'key_name',
'metadata', 'name', 'networks', 'personality', 'reservation_id',
'scheduler_hints', 'security_groups', 'software_config_transport',
'user_data', 'user_data_format', 'user_data_update_policy')
def __init__(self, nodetemplate, csar_dir=None):
super(ToscaCompute, self).__init__(nodetemplate,
type='OS::Nova::Server',
csar_dir=csar_dir)
# List with associated hot port resources with this server
self.assoc_port_resources = []
pass
def handle_properties(self):
self.properties = self.translate_compute_flavor_and_image(
self.nodetemplate.get_capability('host'),
self.nodetemplate.get_capability('os'))
self.properties['user_data_format'] = 'SOFTWARE_CONFIG'
self.properties['software_config_transport'] = 'POLL_SERVER_HEAT'
tosca_props = self.get_tosca_props()
for key, value in tosca_props.items():
if key in self.ALLOWED_NOVA_SERVER_PROPS:
self.properties[key] = value
# To be reorganized later based on new development in Glance and Graffiti
def translate_compute_flavor_and_image(self,
host_capability,
os_capability):
hot_properties = {}
host_cap_props = {}
os_cap_props = {}
image = None
flavor = None
if host_capability:
for prop in host_capability.get_properties_objects():
host_cap_props[prop.name] = prop.value
# if HOST properties are not specified, we should not attempt to
# find best match of flavor
if host_cap_props:
flavor = self._best_flavor(host_cap_props)
if os_capability:
for prop in os_capability.get_properties_objects():
os_cap_props[prop.name] = prop.value
# if OS properties are not specified, we should not attempt to
# find best match of image
if os_cap_props:
image = self._best_image(os_cap_props)
hot_properties['flavor'] = flavor
if image:
hot_properties['image'] = image
else:
hot_properties.pop('image', None)
return hot_properties
def _best_flavor(self, properties):
log.info(_('Choosing the best flavor for given attributes.'))
# Check whether user exported all required environment variables.
flavors = nova_flavors.get_flavors()
# 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(self.NUM_CPUS)
if cpu is None:
self._log_compute_msg(self.NUM_CPUS, 'flavor')
match_cpu = self._match_flavors(match_all, flavors, self.NUM_CPUS, cpu)
# flavors that fit the mem size
mem = properties.get(self.MEM_SIZE)
if mem:
mem = translator.common.utils.MemoryUnit.convert_unit_size_to_num(
mem, 'MB')
else:
self._log_compute_msg(self.MEM_SIZE, 'flavor')
match_cpu_mem = self._match_flavors(match_cpu, flavors,
self.MEM_SIZE, mem)
# flavors that fit the disk size
disk = properties.get(self.DISK_SIZE)
if disk:
disk = translator.common.utils.MemoryUnit.\
convert_unit_size_to_num(disk, 'GB')
else:
self._log_compute_msg(self.DISK_SIZE, 'flavor')
match_cpu_mem_disk = self._match_flavors(match_cpu_mem, flavors,
self.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):
# Check whether user exported all required environment variables.
images = glance_images.get_images()
match_all = images.keys()
architecture = properties.get(self.ARCHITECTURE)
if architecture is None:
self._log_compute_msg(self.ARCHITECTURE, 'image')
match_arch = self._match_images(match_all, images,
[self.ARCHITECTURE], architecture)
image_type = properties.get(self.TYPE)
if image_type is None:
self._log_compute_msg(self.TYPE, 'image')
match_type = self._match_images(match_arch, images, [self.TYPE,
self.OS_TYPE],
image_type)
distribution = properties.get(self.DISTRIBUTION)
if distribution is None:
self._log_compute_msg(self.DISTRIBUTION, 'image')
match_distribution = self._match_images(match_type, images,
[self.DISTRIBUTION,
self.OS_DISTRO],
distribution)
version = properties.get(self.VERSION)
if version is None:
self._log_compute_msg(self.VERSION, 'image')
match_version = self._match_images(match_distribution, images,
[self.VERSION, self.OS_VERSION],
version)
if len(match_version):
return list(match_version)[0]
@staticmethod
def _match_flavors(this_list, this_dict, attr, size):
"""Return from this list all flavors matching the attribute size."""
if not size:
return list(this_list)
matching_flavors = []
for flavor in this_list:
if isinstance(size, int):
if this_dict[flavor][attr] >= size:
matching_flavors.append(flavor)
log.debug(_('Returning list of flavors matching the attribute size.'))
return matching_flavors
@staticmethod
def _least_flavor(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
@staticmethod
def _match_images(this_list, this_dict, attr_list, prop):
if not prop:
return this_list
matching_images = []
for image in this_list:
for attr in attr_list:
if attr in this_dict[image]:
if this_dict[image][attr].lower() == str(prop).lower():
matching_images.insert(0, image)
else:
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.
# Note: We treat private and public IP addresses equally, but
# this will change in the future when TOSCA starts to support
# multiple private/public IP addresses.
log.debug(_('Converting TOSCA attribute for a nodetemplate to a HOT \
attriute.'))
if attribute == 'private_address' or \
attribute == 'public_address':
attr['get_attr'] = [self.name, 'first_address']
return attr
@staticmethod
def _log_compute_msg(prop, what):
msg = _('No value is provided for Compute capability '
'property "%(prop)s". This may set an undesired "%(what)s" '
'in the template.') % {'prop': prop, 'what': what}
log.warning(msg)
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