Openstack虚拟机创建中的RPC调用

参考《Openstack设计与实现》
https://blog.apporc.org/2016/04/nova-%E5%88%9B%E5%BB%BA%E8%99%9A%E6%8B%9F%E6%9C%BA%E6%B5%81%E7%A8%8B/
https://github.com/Moonlight-shadow/openstack-workflow

虚拟机创建过程如图1-1

图1-1

如上图，nova-api在收到客户端创建虚拟机的HTTP请求后，通过RPC调用nova.conductor.manager.ComputeTaskManager中的build_instances()方法。nova-conductor会在build_instance()生成request_spec字典，其中包括了详细的虚拟机信息，nova-scheduler会根据这些信息为虚拟机选择一个最佳的主机，然后nova-conductor再通过RPC调用nova-compute创建虚拟机。虚拟机的创建过程即nova中各组件的RPC调用过程。

代码分析

nova-api接收到创建虚拟机的http请求之后，通过nova-api调用compute.API的create方法来创建虚拟机

#nova/api/openstack/compute/servers.py
from nova import compute

class ServersController(wsgi.Controller):
  def __init__(self, **kwargs):
    ...
    super(ServersController, self).__init__(**kwargs)
    self.compute_api = compute.API(skip_policy_check=True)
    #调用compute.API

  def create(self, req, body):  
    #为特定用户创建虚拟机
    context = req.environ['nova.context']
    server_dict = body['server']
    password = self._get_server_admin_password(server_dict)
    name = common.normalize_name(server_dict['name'])
    #要创建实例的各项参数
    create_kwargs = {}

    try:
      inst_type = flavors.get_flavor_by_flavor_id(
                flavor_id, ctxt=context, read_deleted="no")
      #调用compute.API的create方法进行虚拟机创建
      (instances, resv_id) = self.compute_api.create(context,
                inst_type,
                image_uuid,
                display_name=name,
                display_description=name,
                metadata=server_dict.get('metadata', {}),
                admin_password=password,
                requested_networks=requested_networks,
                check_server_group_quota=True,
                **create_kwargs)
      ...

API的create方法返回值调用APi的_creat_instance()

class API(base.Base):

  def compute_task_api(self):
    if self._compute_task_api is None:
        # TODO(alaski): Remove calls into here from conductor manager so
        # that this isn't necessary. #1180540

        #调用conductor的ComputeTaskAPI类
        from nova import conductor
        self._compute_task_api = conductor.ComputeTaskAPI()
    return self._compute_task_api

  def _create_instance(self, context, instance_type,
               image_href, kernel_id, ramdisk_id,
               min_count, max_count,
               display_name, display_description,
               key_name, key_data, security_groups,
               availability_zone, user_data, metadata,
               injected_files, admin_password,
               access_ip_v4, access_ip_v6,
               requested_networks, config_drive,
               block_device_mapping, auto_disk_config,
               reservation_id=None, scheduler_hints=None,
               legacy_bdm=True, shutdown_terminate=False,
               check_server_group_quota=False):

         # self._compute_task_api = conductor.ComputeTaskAPI() 调用调用conductor的ComputeTaskAPI类的build_instances方法
         self.compute_task_api.build_instances(context,
                  instances=instances, image=boot_meta,
                  filter_properties=filter_properties,
                  admin_password=admin_password,
                  injected_files=injected_files,
                  requested_networks=requested_networks,
                  security_groups=security_groups,
                  block_device_mapping=block_device_mapping,
                  legacy_bdm=False)

          return (instances, reservation_id)

ComputeTaskAPI中build_instances方法的实现

#/nova/compute/api.py
class ComputeTaskAPI(object):
    """ComputeTask API that queues up compute tasks for nova-conductor."""

    def __init__(self):
        self.conductor_compute_rpcapi = rpcapi.ComputeTaskAPI()

    #云主机调整大小
    def resize_instance(self, context, instance, extra_instance_updates,
                        scheduler_hint, flavor, reservations,
                        clean_shutdown=True):
        # NOTE(comstud): 'extra_instance_updates' is not used here but is
        # needed for compatibility with the cells_rpcapi version of this
        # method.
        self.conductor_compute_rpcapi.migrate_server(
            context, instance, scheduler_hint, live=False, rebuild=False,
            flavor=flavor, block_migration=None, disk_over_commit=None,
            reservations=reservations, clean_shutdown=clean_shutdown)

    #rpc调用
    def live_migrate_instance(self, context, instance, host_name,
                              block_migration, disk_over_commit):
        scheduler_hint = {'host': host_name}
        self.conductor_compute_rpcapi.migrate_server(
            context, instance, scheduler_hint, True, False, None,
            block_migration, disk_over_commit, None)

    #创建云主机，调用rpcapi.ComputeTaskAPI()的build_instances方法
    def build_instances(self, context, instances, image, filter_properties,
            admin_password, injected_files, requested_networks,
            security_groups, block_device_mapping, legacy_bdm=True):
        self.conductor_compute_rpcapi.build_instances(context,
                instances=instances, image=image,
                filter_properties=filter_properties,
                admin_password=admin_password, injected_files=injected_files,
                requested_networks=requested_networks,
                security_groups=security_groups,
                block_device_mapping=block_device_mapping,
                legacy_bdm=legacy_bdm)


    def unshelve_instance(self, context, instance):
        self.conductor_compute_rpcapi.unshelve_instance(context,
                instance=instance)

    #重建云主机  
    def rebuild_instance(self, context, instance, orig_image_ref, image_ref,
                         injected_files, new_pass, orig_sys_metadata,
                         bdms, recreate=False, on_shared_storage=False,
                         preserve_ephemeral=False, host=None, kwargs=None):
        # kwargs unused but required for cell compatibility
        self.conductor_compute_rpcapi.rebuild_instance(context,
                instance=instance,
                new_pass=new_pass,
                injected_files=injected_files,
                image_ref=image_ref,
                orig_image_ref=orig_image_ref,
                orig_sys_metadata=orig_sys_metadata,
                bdms=bdms,
                recreate=recreate,
                on_shared_storage=on_shared_storage,
                preserve_ephemeral=preserve_ephemeral,
                host=host)

到了conductor.rpcapi

# nova/conductor/rpcapi.py
class ComputeTaskAPI(object):
    """Client side of the conductor 'compute' namespaced RPC API"""

    def build_instances(self, context, instances, image, filter_properties,
        admin_password, injected_files, requested_networks,
        security_groups, block_device_mapping, legacy_bdm=True):
    image_p = jsonutils.to_primitive(image)
    version = '1.10'
    if not self.client.can_send_version(version):
        version = '1.9'
        if 'instance_type' in filter_properties:
            flavor = filter_properties['instance_type']
            flavor_p = objects_base.obj_to_primitive(flavor)
            filter_properties = dict(filter_properties,
                                     instance_type=flavor_p)
    kw = {'instances': instances, 'image': image_p,
           'filter_properties': filter_properties,
           'admin_password': admin_password,
           'injected_files': injected_files,
           'requested_networks': requested_networks,
           'security_groups': security_groups}
    if not self.client.can_send_version(version):
        version = '1.8'
        kw['requested_networks'] = kw['requested_networks'].as_tuples()
    if not self.client.can_send_version('1.7'):
        version = '1.5'
        bdm_p = objects_base.obj_to_primitive(block_device_mapping)
        kw.update({'block_device_mapping': bdm_p,
                   'legacy_bdm': legacy_bdm})

    cctxt = self.client.prepare(version=version)
    #RPC主要用于异步形式，比如下面就用于双肩虚拟机，在创建过程，可能需要比较长的时间
    #如果使用RPC call显然对性能有很大影响。cast（）的第二个参数是RPC调用的函数名，后面的参数
    #将作为参数传递给函数。
    #关于同步异步阻塞非阻塞请看 http://blog.youkuaiyun.com/moolight_shadow/article/details/70212874
    # 这儿就调用上面的build_instances方法进行RPC通信。把创建请求扔到消息队列中
    cctxt.cast(context, 'build_instances', **kw)

cast() 方法发送出去的 rpc 请求是没有回复的。所以创建虚拟机的请求在_create_instance()一步直接返回了，此时虚拟机并没有创建完毕，但是创建的请求已成功发往了 nova-conductor。后续虚拟机的创建情况通过虚拟机的状态反映。
nova-conductor 提供了 build_instances() 这个 rpc 方法，所以它一直在紧切注视着 rabbitmq 消息队列。当看到有一个请求指向自己时，它就捡起了这个请求，准备进行 build_instances() 操作。进入 nova/conductor/manager.py 这里，做的事情非常明显，发送一个请求到 nova-scheduler，得到一个选好的运行 nova-compute的主机，然后将请求发给 nova-compute。

在nova-conductor进程中进行处理

class ComputeTaskManager(base.Base):
  def build_instances(self, context, instances, image, filter_properties,
        admin_password, injected_files, requested_networks,
        security_groups, block_device_mapping=None, legacy_bdm=True):
    # TODO(ndipanov): Remove block_device_mapping and legacy_bdm in version
    #                 2.0 of the RPC API.
    request_spec = scheduler_utils.build_request_spec(context, image,
                                                      instances)


    for (instance, host) in itertools.izip(instances, hosts):
        try:
            instance.refresh()
        except (exception.InstanceNotFound,
                exception.InstanceInfoCacheNotFound):
            LOG.debug('Instance deleted during build', instance=instance)
            continue
        local_filter_props = copy.deepcopy(filter_properties)
        scheduler_utils.populate_filter_properties(local_filter_props,
            host)
        # The block_device_mapping passed from the api doesn't contain
        # instance specific information
        bdms = objects.BlockDeviceMappingList.get_by_instance_uuid(
                context, instance.uuid)

        self.compute_rpcapi.build_and_run_instance(context,
                instance=instance, host=host['host'], image=image,
                request_spec=request_spec,
                filter_properties=local_filter_props,
                admin_password=admin_password,
                injected_files=injected_files,
                requested_networks=requested_networks,
                security_groups=security_groups,
                block_device_mapping=bdms, node=host['nodename'],
                limits=host['limits'])