From 477b4d01e421a6fd7a1037f00539e8a79e92347e Mon Sep 17 00:00:00 2001 From: licanwei Date: Sat, 16 Feb 2019 14:07:43 +0800 Subject: [PATCH] change config parameter from 'datasource' to 'datasources' Change-Id: Iaf59ea25f8d62bf29562f21d846243f98d9b6997 --- .../strategies/vm_workload_consolidation.py | 61 +++++++++---------- .../model/faker_cluster_and_metrics.py | 40 +++++++----- .../test_vm_workload_consolidation.py | 10 ++- 3 files changed, 61 insertions(+), 50 deletions(-) diff --git a/watcher/decision_engine/strategy/strategies/vm_workload_consolidation.py b/watcher/decision_engine/strategy/strategies/vm_workload_consolidation.py index bc4df0776..5dae22849 100644 --- a/watcher/decision_engine/strategy/strategies/vm_workload_consolidation.py +++ b/watcher/decision_engine/strategy/strategies/vm_workload_consolidation.py @@ -68,6 +68,7 @@ class VMWorkloadConsolidation(base.ServerConsolidationBaseStrategy): HOST_CPU_USAGE_METRIC_NAME = 'compute.node.cpu.percent' INSTANCE_CPU_USAGE_METRIC_NAME = 'cpu_util' + AGGREGATION = 'mean' DATASOURCE_METRICS = ['instance_ram_allocated', 'instance_cpu_usage', 'instance_ram_usage', 'instance_root_disk_size'] @@ -140,11 +141,14 @@ class VMWorkloadConsolidation(base.ServerConsolidationBaseStrategy): @classmethod def get_config_opts(cls): return [ - cfg.StrOpt( - "datasource", - help="Data source to use in order to query the needed metrics", - default="gnocchi", - choices=["ceilometer", "gnocchi"]) + cfg.ListOpt( + "datasources", + help="Datasources to use in order to query the needed metrics." + " If one of strategy metric isn't available in the first" + " datasource, the next datasource will be chosen.", + item_type=cfg.types.String(choices=['gnocchi', 'ceilometer', + 'monasca']), + default=['gnocchi', 'ceilometer', 'monasca']) ] def get_available_compute_nodes(self): @@ -281,36 +285,29 @@ class VMWorkloadConsolidation(base.ServerConsolidationBaseStrategy): if instance.uuid in self.datasource_instance_data_cache.keys(): return self.datasource_instance_data_cache.get(instance.uuid) - cpu_util_metric = self.METRIC_NAMES[ - self.config.datasource]['cpu_util_metric'] - ram_util_metric = self.METRIC_NAMES[ - self.config.datasource]['ram_util_metric'] - ram_alloc_metric = self.METRIC_NAMES[ - self.config.datasource]['ram_alloc_metric'] - disk_alloc_metric = self.METRIC_NAMES[ - self.config.datasource]['disk_alloc_metric'] - - instance_cpu_util = self.datasource_backend.statistic_aggregation( - resource_id=instance.uuid, - meter_name=cpu_util_metric, - period=self.period, + instance_cpu_util = self.datasource_backend.get_instance_cpu_usage( + instance.uuid, + self.period, + self.AGGREGATION, granularity=self.granularity) - instance_ram_util = self.datasource_backend.statistic_aggregation( - resource_id=instance.uuid, - meter_name=ram_util_metric, - period=self.period, + instance_ram_util = self.datasource_backend.get_instance_memory_usage( + instance.uuid, + self.period, + self.AGGREGATION, granularity=self.granularity) if not instance_ram_util: - instance_ram_util = self.datasource_backend.statistic_aggregation( - resource_id=instance.uuid, - meter_name=ram_alloc_metric, - period=self.period, - granularity=self.granularity) - instance_disk_util = self.datasource_backend.statistic_aggregation( - resource_id=instance.uuid, - meter_name=disk_alloc_metric, - period=self.period, - granularity=self.granularity) + instance_ram_util = ( + self.datasource_backend.get_instance_ram_allocated( + instance.uuid, + self.period, + self.AGGREGATION, + granularity=self.granularity)) + instance_disk_util = ( + self.datasource_backend.get_instance_root_disk_allocated( + instance.uuid, + self.period, + self.AGGREGATION, + granularity=self.granularity)) if instance_cpu_util: total_cpu_utilization = ( diff --git a/watcher/tests/decision_engine/model/faker_cluster_and_metrics.py b/watcher/tests/decision_engine/model/faker_cluster_and_metrics.py index 595e9b667..2ad485ef4 100644 --- a/watcher/tests/decision_engine/model/faker_cluster_and_metrics.py +++ b/watcher/tests/decision_engine/model/faker_cluster_and_metrics.py @@ -88,15 +88,19 @@ class FakeCeilometerMetrics(object): period=300, granularity=300, dimensions=None, aggregation='avg', group_by='*'): if meter_name == "compute.node.cpu.percent": - return self.get_node_cpu_util(resource_id) + return self.get_node_cpu_util(resource_id, period, + aggregation, granularity) elif meter_name == "cpu_util": - return self.get_instance_cpu_util(resource_id) + return self.get_instance_cpu_util(resource_id, period, + aggregation, granularity) elif meter_name == "memory.resident": - return self.get_instance_ram_util(resource_id) + return self.get_instance_ram_util(resource_id, period, + aggregation, granularity) elif meter_name == "disk.root.size": - return self.get_instance_disk_root_size(resource_id) + return self.get_instance_disk_root_size(resource_id, period, + aggregation, granularity) - def get_node_cpu_util(self, r_id): + def get_node_cpu_util(self, r_id, period, aggregation, granularity): """Calculates node utilization dynamicaly. node CPU utilization should consider @@ -118,7 +122,7 @@ class FakeCeilometerMetrics(object): return util_sum * 100.0 @staticmethod - def get_instance_cpu_util(r_id): + def get_instance_cpu_util(r_id, period, aggregation, granularity): instance_cpu_util = dict() instance_cpu_util['INSTANCE_0'] = 10 instance_cpu_util['INSTANCE_1'] = 30 @@ -133,7 +137,7 @@ class FakeCeilometerMetrics(object): return instance_cpu_util[str(r_id)] @staticmethod - def get_instance_ram_util(r_id): + def get_instance_ram_util(r_id, period, aggregation, granularity): instance_ram_util = dict() instance_ram_util['INSTANCE_0'] = 1 instance_ram_util['INSTANCE_1'] = 2 @@ -148,7 +152,7 @@ class FakeCeilometerMetrics(object): return instance_ram_util[str(r_id)] @staticmethod - def get_instance_disk_root_size(r_id): + def get_instance_disk_root_size(r_id, period, aggregation, granularity): instance_disk_util = dict() instance_disk_util['INSTANCE_0'] = 10 instance_disk_util['INSTANCE_1'] = 15 @@ -171,15 +175,19 @@ class FakeGnocchiMetrics(object): period=300, granularity=300, dimensions=None, aggregation='avg', group_by='*'): if meter_name == "compute.node.cpu.percent": - return self.get_node_cpu_util(resource_id) + return self.get_node_cpu_util(resource_id, period, + aggregation, granularity) elif meter_name == "cpu_util": - return self.get_instance_cpu_util(resource_id) + return self.get_instance_cpu_util(resource_id, period, + aggregation, granularity) elif meter_name == "memory.resident": - return self.get_instance_ram_util(resource_id) + return self.get_instance_ram_util(resource_id, period, + aggregation, granularity) elif meter_name == "disk.root.size": - return self.get_instance_disk_root_size(resource_id) + return self.get_instance_disk_root_size(resource_id, period, + aggregation, granularity) - def get_node_cpu_util(self, r_id): + def get_node_cpu_util(self, r_id, period, aggregation, granularity): """Calculates node utilization dynamicaly. node CPU utilization should consider @@ -202,7 +210,7 @@ class FakeGnocchiMetrics(object): return util_sum * 100.0 @staticmethod - def get_instance_cpu_util(r_id): + def get_instance_cpu_util(r_id, period, aggregation, granularity): instance_cpu_util = dict() instance_cpu_util['INSTANCE_0'] = 10 instance_cpu_util['INSTANCE_1'] = 30 @@ -217,7 +225,7 @@ class FakeGnocchiMetrics(object): return instance_cpu_util[str(r_id)] @staticmethod - def get_instance_ram_util(r_id): + def get_instance_ram_util(r_id, period, aggregation, granularity): instance_ram_util = dict() instance_ram_util['INSTANCE_0'] = 1 instance_ram_util['INSTANCE_1'] = 2 @@ -232,7 +240,7 @@ class FakeGnocchiMetrics(object): return instance_ram_util[str(r_id)] @staticmethod - def get_instance_disk_root_size(r_id): + def get_instance_disk_root_size(r_id, period, aggregation, granularity): instance_disk_util = dict() instance_disk_util['INSTANCE_0'] = 10 instance_disk_util['INSTANCE_1'] = 15 diff --git a/watcher/tests/decision_engine/strategy/strategies/test_vm_workload_consolidation.py b/watcher/tests/decision_engine/strategy/strategies/test_vm_workload_consolidation.py index dd75fb3d9..f2d608f1c 100644 --- a/watcher/tests/decision_engine/strategy/strategies/test_vm_workload_consolidation.py +++ b/watcher/tests/decision_engine/strategy/strategies/test_vm_workload_consolidation.py @@ -75,9 +75,15 @@ class TestVMWorkloadConsolidation(base.TestCase): self.m_model.return_value = model_root.ModelRoot() self.m_datasource.return_value = mock.Mock( - statistic_aggregation=self.fake_metrics.mock_get_statistics) + get_instance_cpu_usage=( + self.fake_metrics.get_instance_cpu_util), + get_instance_memory_usage=( + self.fake_metrics.get_instance_ram_util), + get_instance_root_disk_allocated=( + self.fake_metrics.get_instance_disk_root_size), + ) self.strategy = strategies.VMWorkloadConsolidation( - config=mock.Mock(datasource=self.datasource)) + config=mock.Mock(datasources=self.datasource)) def test_exception_stale_cdm(self): self.fake_cluster.set_cluster_data_model_as_stale()