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):
  16         self.e_cpu = dc_emulation_max_cpu
  17         # pointer to all resource models assigned to DCs
  18         self._resource_models = dict()
  19         LOG.info("Resource model registrar created with dc_emulation_max_cpu=%r" % dc_emulation_max_cpu)
  20
  21     def register(self, dc, rm):
  22         """
  23         Register a new resource model.
  24         :param dc: Data center to which it is assigned.
  25         :param rm: The resource model object.
  26         :return: None
  27         """
  28         if dc in self._resource_models:
  29             raise Exception("There is already an resource model assigned to this DC.")
  30         self._resource_models[dc] = rm
  31         rm.registrar = self
  32         rm.dcs.append(dc)
  33         LOG.info("Registrar: Added resource model: %r" % rm)
  34
  35     @property
  36     def resource_models(self):
  37         """
  38         List of registered resource models
  39         :return:
  40         """
  41         return list(self._resource_models.itervalues())
  42
  43     @property
  44     def num_dcs_with_rms(self):
  45         """
  46         Total number of data centers that are connected to a resource model
  47         :return:
  48         """
  49         return sum([len(rm.dcs) for rm in list(self._resource_models.itervalues())])
  50
  51
  52 class ResourceFlavor(object):
  53     """
  54     Simple class that represents resource flavors (c.f. OpenStack).
  55     Can contain arbitrary metrics.
  56     """
  57     def __init__(self, name, metrics):
  58         self.name = name
  59         self._metrics = metrics
  60         LOG.debug("Create flavor %r with metrics: %r" % (name, metrics))
  61
  62     def get(self, metric_key):
  63         return self._metrics.get(metric_key)
  64
  65
  66 class BaseResourceModel(object):
  67     """
  68     Base class for a resource limitation model.
  69     Has to be extended by a real resource model implementtion.
  70     """
  71
  72     def __init__(self):
  73         self._flavors = dict()
  74         self._initDefaultFlavors()
  75         self.registrar = None  # pointer to registrar
  76         self.dcs = list()
  77         self.allocated_compute_instances = dict()
  78         LOG.info("Resource model %r initialized" % self)
  79
  80     def __repr__(self):
  81         return self.__class__.__name__
  82
  83     def _initDefaultFlavors(self):
  84         """
  85         initialize some default flavours (naming/sizes inspired by OpenStack)
  86         """
  87         self.addFlavour(ResourceFlavor(
  88             "tiny",  {"compute": 1, "memory": 32, "disk": 1}))
  89         self.addFlavour(ResourceFlavor(
  90             "small",  {"compute": 4, "memory": 128, "disk": 20}))
  91         self.addFlavour(ResourceFlavor(
  92             "medium",  {"compute": 8, "memory": 256, "disk": 40}))
  93         self.addFlavour(ResourceFlavor(
  94             "large",  {"compute": 16, "memory": 512, "disk": 80}))
  95         self.addFlavour(ResourceFlavor(
  96             "xlarge",  {"compute": 32, "memory": 1024, "disk": 160}))
  97
  98     def addFlavour(self, fl):
  99         """
 100         Add a new flavor to the resource model.
 101         :param fl: flavor object
 102         :return: None
 103         """
 104         if fl.name in self._flavors:
 105             raise Exception("Flavor with name %r already exists!" % fl.name)
 106         self._flavors[fl.name] = fl
 107
 108     def allocate(self, name, flavor_name):
 109         """
 110         This method has to be overwritten by a real resource model.
 111         :param name: Name of the started compute instance.
 112         :param flavor_name:  Name of the flavor to be allocated.
 113         :return: 3-tuple: (CPU-fraction, Mem-limit, Disk-limit)
 114         """
 115         LOG.warning("Allocating in BaseResourceModel: %r with flavor: %r" % (name, flavor_name))
 116         self.allocated_compute_instances[name] = flavor_name
 117         return -1.0, -1.0, -1.0  # return invalid values to indicate that this RM is a dummy
 118
 119     def free(self, name):
 120         """
 121         This method has to be overwritten by a real resource model.
 122         :param name: Name of the compute instance that is stopped.
 123         :return: True/False
 124         """
 125         LOG.warning("Free in BaseResourceModel: %r" % name)
 126         del self.allocated_compute_instances[name]
 127         return True