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Remove obsolete Resource element

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Partially Implements: blueprint graph-based-cluster-model

Change-Id: I2765d1c7a864d6658c847dcd988314fc8f11049c
This commit is contained in:
Vincent Françoise
2017-01-11 15:29:25 +01:00
parent d433d6b3c8
commit edd3d219d5
21 changed files with 286 additions and 594 deletions
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53
watcher/decision_engine/strategy/strategies/workload_balance.py
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@@ -145,17 +145,16 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
},
}
def calculate_used_resource(self, node, cap_cores, cap_mem,
cap_disk):
def calculate_used_resource(self, node):
"""Calculate the used vcpus, memory and disk based on VM flavors"""
instances = self.compute_model.get_node_instances(node)
vcpus_used = 0
memory_mb_used = 0
disk_gb_used = 0
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)
vcpus_used += instance.vcpus
memory_mb_used += instance.memory
disk_gb_used += instance.disk
return vcpus_used, memory_mb_used, disk_gb_used
@@ -200,18 +199,10 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
def filter_destination_hosts(self, hosts, instance_to_migrate,
avg_workload, workload_cache):
'''Only return hosts with sufficient available resources'''
cap_cores = self.compute_model.get_resource_by_uuid(
element.ResourceType.cpu_cores)
cap_disk = self.compute_model.get_resource_by_uuid(
element.ResourceType.disk)
cap_mem = self.compute_model.get_resource_by_uuid(
element.ResourceType.memory)
required_cores = cap_cores.get_capacity(instance_to_migrate)
required_disk = cap_disk.get_capacity(instance_to_migrate)
required_mem = cap_mem.get_capacity(instance_to_migrate)
"""Only return hosts with sufficient available resources"""
required_cores = instance_to_migrate.vcpus
required_disk = instance_to_migrate.disk
required_mem = instance_to_migrate.memory
# filter nodes without enough resource
destination_hosts = []
@@ -221,16 +212,16 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
workload = instance_data['workload']
# calculate the available resources
cores_used, mem_used, disk_used = self.calculate_used_resource(
host, cap_cores, cap_mem, cap_disk)
cores_available = cap_cores.get_capacity(host) - cores_used
disk_available = cap_disk.get_capacity(host) - disk_used
mem_available = cap_mem.get_capacity(host) - mem_used
host)
cores_available = host.vcpus - cores_used
disk_available = host.disk - disk_used
mem_available = host.memory - mem_used
if (
cores_available >= required_cores and
disk_available >= required_disk and
mem_available >= required_mem and
(src_instance_workload + workload) < self.threshold / 100 *
cap_cores.get_capacity(host)
((src_instance_workload + workload) <
self.threshold / 100 * host.vcpus)
):
destination_hosts.append(instance_data)
@@ -249,9 +240,6 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
cluster_size = len(nodes)
if not nodes:
raise wexc.ClusterEmpty()
# get cpu cores capacity of nodes and instances
cap_cores = self.compute_model.get_resource_by_uuid(
element.ResourceType.vcpus)
overload_hosts = []
nonoverload_hosts = []
# total workload of cluster
@@ -259,8 +247,7 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
# use workload_cache to store the workload of VMs for reuse purpose
workload_cache = {}
for node_id in nodes:
node = self.compute_model.get_node_by_uuid(
node_id)
node = self.compute_model.get_node_by_uuid(node_id)
instances = self.compute_model.get_node_instances(node)
node_workload = 0.0
for instance in instances:
@@ -277,19 +264,17 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
if cpu_util is None:
LOG.debug("Instance (%s): cpu_util is None", instance.uuid)
continue
instance_cores = cap_cores.get_capacity(instance)
workload_cache[instance.uuid] = cpu_util * instance_cores / 100
workload_cache[instance.uuid] = cpu_util * instance.vcpus / 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
node_cpu_util = node_workload / node.vcpus * 100
cluster_workload += node_workload
instance_data = {
'node': node, "cpu_util": hy_cpu_util,
'node': node, "cpu_util": node_cpu_util,
'workload': node_workload}
if hy_cpu_util >= self.threshold:
if node_cpu_util >= self.threshold:
# mark the node to release resources
overload_hosts.append(instance_data)
else: