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Graph cluster model instead of mapping one

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In this changeset, I use https://review.openstack.org/#/c/362730/
as an example to make the existing ModelRoot fully graph-based.

Change-Id: I3a1ec8674b885d75221035459233722c18972f67
Implements: blueprint graph-based-cluster-model
This commit is contained in:
Vincent Françoise
2017-01-10 16:06:06 +01:00
parent 41f579d464
commit d433d6b3c8
44 changed files with 1001 additions and 993 deletions
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32
watcher/decision_engine/strategy/strategies/workload_balance.py
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@@ -148,12 +148,11 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
def calculate_used_resource(self, node, cap_cores, cap_mem,
cap_disk):
"""Calculate the used vcpus, memory and disk based on VM flavors"""
instances = self.compute_model.mapping.get_node_instances(node)
instances = self.compute_model.get_node_instances(node)
vcpus_used = 0
memory_mb_used = 0
disk_gb_used = 0
for instance_id in instances:
instance = self.compute_model.get_instance_by_uuid(instance_id)
for instance in instances:
vcpus_used += cap_cores.get_capacity(instance)
memory_mb_used += cap_mem.get_capacity(instance)
disk_gb_used += cap_disk.get_capacity(instance)
@@ -169,27 +168,25 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
"""
for instance_data in hosts:
source_node = instance_data['node']
source_instances = self.compute_model.mapping.get_node_instances(
source_instances = self.compute_model.get_node_instances(
source_node)
if source_instances:
delta_workload = instance_data['workload'] - avg_workload
min_delta = 1000000
instance_id = None
for inst_id in source_instances:
for instance in source_instances:
try:
# select the first active VM to migrate
instance = self.compute_model.get_instance_by_uuid(
inst_id)
if (instance.state !=
element.InstanceState.ACTIVE.value):
LOG.debug("Instance not active, skipped: %s",
instance.uuid)
continue
current_delta = (
delta_workload - workload_cache[inst_id])
delta_workload - workload_cache[instance.uuid])
if 0 <= current_delta < min_delta:
min_delta = current_delta
instance_id = inst_id
instance_id = instance.uuid
except wexc.InstanceNotFound:
LOG.error(_LE("Instance not found; error: %s"),
instance_id)
@@ -254,7 +251,7 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
raise wexc.ClusterEmpty()
# get cpu cores capacity of nodes and instances
cap_cores = self.compute_model.get_resource_by_uuid(
element.ResourceType.cpu_cores)
element.ResourceType.vcpus)
overload_hosts = []
nonoverload_hosts = []
# total workload of cluster
@@ -264,13 +261,12 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
for node_id in nodes:
node = self.compute_model.get_node_by_uuid(
node_id)
instances = self.compute_model.mapping.get_node_instances(node)
instances = self.compute_model.get_node_instances(node)
node_workload = 0.0
for instance_id in instances:
instance = self.compute_model.get_instance_by_uuid(instance_id)
for instance in instances:
try:
cpu_util = self.ceilometer.statistic_aggregation(
resource_id=instance_id,
resource_id=instance.uuid,
meter_name=self._meter,
period=self._period,
aggregate='avg')
@@ -279,12 +275,12 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
LOG.error(_LE("Can not get cpu_util from Ceilometer"))
continue
if cpu_util is None:
LOG.debug("Instance (%s): cpu_util is None", instance_id)
LOG.debug("Instance (%s): cpu_util is None", instance.uuid)
continue
instance_cores = cap_cores.get_capacity(instance)
workload_cache[instance_id] = cpu_util * instance_cores / 100
node_workload += workload_cache[instance_id]
LOG.debug("VM (%s): cpu_util %f", instance_id, cpu_util)
workload_cache[instance.uuid] = cpu_util * instance_cores / 100
node_workload += workload_cache[instance.uuid]
LOG.debug("VM (%s): cpu_util %f", instance.uuid, cpu_util)
node_cores = cap_cores.get_capacity(node)
hy_cpu_util = node_workload / node_cores * 100