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         LOG.info("Registrar: Added resource model: %r" % rm)
  33
  34     @property
  35     def resource_models(self):
  36         return list(self._resource_models.itervalues())
  37
  38
  39 class ResourceFlavor(object):
  40     """
  41     Simple class that represents resource flavors (c.f. OpenStack).
  42     Can contain arbitrary metrics.
  43     """
  44     def __init__(self, name, metrics):
  45         self.name = name
  46         self._metrics = metrics
  47         LOG.debug("Create flavor %r with metrics: %r" % (name, metrics))
  48
  49     def get(self, metric_key):
  50         return self._metrics.get(metric_key)
  51
  52
  53 class BaseResourceModel(object):
  54     """
  55     Base class for a resource limitation model.
  56     Has to be extended by a real resource model implementtion.
  57     """
  58
  59     def __init__(self):
  60         self._flavors = dict()
  61         self._initDefaultFlavors()
  62         self.registrar = None  # pointer to registrar
  63         self.allocated_compute_instances = dict()
  64         LOG.info("Resource model %r initialized" % self)
  65
  66     def __repr__(self):
  67         return self.__class__.__name__
  68
  69     def _initDefaultFlavors(self):
  70         """
  71         initialize some default flavours (naming/sizes inspired by OpenStack)
  72         """
  73         self.addFlavour(ResourceFlavor(
  74             "tiny",  {"compute": 1, "memory": 32, "disk": 1}))
  75         self.addFlavour(ResourceFlavor(
  76             "small",  {"compute": 4, "memory": 128, "disk": 20}))
  77         self.addFlavour(ResourceFlavor(
  78             "medium",  {"compute": 8, "memory": 256, "disk": 40}))
  79         self.addFlavour(ResourceFlavor(
  80             "large",  {"compute": 16, "memory": 512, "disk": 80}))
  81         self.addFlavour(ResourceFlavor(
  82             "xlarge",  {"compute": 32, "memory": 1024, "disk": 160}))
  83
  84     def addFlavour(self, fl):
  85         """
  86         Add a new flavor to the resource model.
  87         :param fl: flavor object
  88         :return: None
  89         """
  90         if fl.name in self._flavors:
  91             raise Exception("Flavor with name %r already exists!" % fl.name)
  92         self._flavors[fl.name] = fl
  93
  94     def allocate(self, name, flavor_name):
  95         """
  96         This method has to be overwritten by a real resource model.
  97         :param name: Name of the started compute instance.
  98         :param flavor_name:  Name of the flavor to be allocated.
  99         :return: 3-tuple: (CPU-fraction, Mem-limit, Disk-limit)
 100         """
 101         LOG.warning("Allocating in BaseResourceModel: %r with flavor: %r" % (name, flavor_name))
 102         self.allocated_compute_instances[name] = flavor_name
 103         return -1.0, -1.0, -1.0  # return invalid values to indicate that this RM is a dummy
 104
 105     def free(self, name):
 106         """
 107         This method has to be overwritten by a real resource model.
 108         :param name: Name of the compute instance that is stopped.
 109         :return: True/False
 110         """
 111         LOG.warning("Free in BaseResourceModel: %r" % name)
 112         del self.allocated_compute_instances[name]
 113         return True