src/emuvim/dcemulator/resourcemodel/__init__.py

   1 """
   2 Base classes needed for resource models support.
   3 """
   4
   5 import logging
   6 LOG = logging.getLogger("resourcemodel")
   7 LOG.setLevel(logging.DEBUG)
   8
   9
  10 class ResourceModelRegistrar(object):
  11     """
  12     Global registry to keep track of all existing resource models.
  13     """
  14
  15     def __init__(self, dc_emulation_max_cpu, dc_emulation_max_mem):
  16         self.e_cpu = dc_emulation_max_cpu
  17         self.e_mem = dc_emulation_max_mem
  18         # pointer to all resource models assigned to DCs
  19         self._resource_models = dict()
  20         LOG.info("Resource model registrar created with dc_emulation_max_cpu=%r and dc_emulation_max_mem=%r"
  21                  % (dc_emulation_max_cpu, dc_emulation_max_mem))
  22
  23     def register(self, dc, rm):
  24         """
  25         Register a new resource model.
  26         :param dc: Data center to which it is assigned.
  27         :param rm: The resource model object.
  28         :return: None
  29         """
  30         if dc in self._resource_models:
  31             raise Exception("There is already an resource model assigned to this DC.")
  32         self._resource_models[dc] = rm
  33         rm.registrar = self
  34         rm.dcs.append(dc)
  35         LOG.info("Registrar: Added resource model: %r" % rm)
  36
  37     @property
  38     def resource_models(self):
  39         """
  40         List of registered resource models
  41         :return:
  42         """
  43         return list(self._resource_models.itervalues())
  44
  45     @property
  46     def num_dcs_with_rms(self):
  47         """
  48         Total number of data centers that are connected to a resource model
  49         :return:
  50         """
  51         return sum([len(rm.dcs) for rm in list(self._resource_models.itervalues())])
  52
  53
  54 class ResourceFlavor(object):
  55     """
  56     Simple class that represents resource flavors (c.f. OpenStack).
  57     Can contain arbitrary metrics.
  58     """
  59     def __init__(self, name, metrics):
  60         self.name = name
  61         self._metrics = metrics
  62         LOG.debug("Create flavor %r with metrics: %r" % (name, metrics))
  63
  64     def get(self, metric_key):
  65         return self._metrics.get(metric_key)
  66
  67
  68 class BaseResourceModel(object):
  69     """
  70     Base class for a resource limitation model.
  71     Has to be extended by a real resource model implementtion.
  72     """
  73
  74     def __init__(self):
  75         self._flavors = dict()
  76         self._initDefaultFlavors()
  77         self.registrar = None  # pointer to registrar
  78         self.dcs = list()
  79         self._allocated_compute_instances = dict()
  80         LOG.info("Resource model %r initialized" % self)
  81
  82     def __repr__(self):
  83         return self.__class__.__name__
  84
  85     def _initDefaultFlavors(self):
  86         """
  87         initialize some default flavours (naming/sizes inspired by OpenStack)
  88         """
  89         self.addFlavour(ResourceFlavor(
  90             "tiny",  {"compute": 0.5, "memory": 32, "disk": 1}))
  91         self.addFlavour(ResourceFlavor(
  92             "small",  {"compute": 1.0, "memory": 128, "disk": 20}))
  93         self.addFlavour(ResourceFlavor(
  94             "medium",  {"compute": 4.0, "memory": 256, "disk": 40}))
  95         self.addFlavour(ResourceFlavor(
  96             "large",  {"compute": 8.0, "memory": 512, "disk": 80}))
  97         self.addFlavour(ResourceFlavor(
  98             "xlarge",  {"compute": 16.0, "memory": 1024, "disk": 160}))
  99
 100     def addFlavour(self, fl):
 101         """
 102         Add a new flavor to the resource model.
 103         :param fl: flavor object
 104         :return: None
 105         """
 106         if fl.name in self._flavors:
 107             raise Exception("Flavor with name %r already exists!" % fl.name)
 108         self._flavors[fl.name] = fl
 109
 110     def allocate(self, d):
 111         """
 112         This method has to be overwritten by a real resource model.
 113         :param d: Container object
 114         """
 115         LOG.warning("Allocating in BaseResourceModel: %r with flavor: %r" % (d.name, d.flavor_name))
 116         self._allocated_compute_instances[d.name] = d.flavor_name
 117
 118     def free(self, d):
 119         """
 120         This method has to be overwritten by a real resource model.
 121         :param d: Container object
 122         """
 123         LOG.warning("Free in BaseResourceModel: %r" % d.name)
 124         del self._allocated_compute_instances[d.name]
 125
 126     def get_state_dict(self):
 127         """
 128         Return the state of the resource model as simple dict.
 129         Helper method for logging functionality.
 130         :return:
 131         """
 132         return dict()
 133
 134     def write_allocation_log(self, d, path):
 135         """
 136         Helper to log RM info for experiments.
 137         :param d: container
 138         :param path: log path
 139         :return:
 140         """
 141         self._write_log(d, path, "allocate")
 142
 143     def write_free_log(self, d, path):
 144         """
 145         Helper to log RM info for experiments.
 146         :param d: container
 147         :param path: log path
 148         :return:
 149         """
 150         self._write_log(d, path, "free")
 151
 152     def _write_log(self, d, path, action):
 153         """
 154         Helper to log RM info for experiments.
 155         :param d: container
 156         :param path: log path
 157         :param action: allocate or free
 158         :return:
 159         """
 160         pass
 161
 162
 163 class NotEnoughResourcesAvailable(BaseException):
 164     pass