Merge "Handle deprecated "cpu_util" metric" into stable/2023.2

The Nova collector json schema validation started [1][2] failing after
the jsonschema upper constraint was bumped from 4.17.3 to 4.19.1 [3].

The reason is that jsonschema v4.18.0a1 switched to a reference
resolving library [4], which treats the aggregate "id" as a jsonschema
id and expects it to be a string [5]. For this reason, we're now getting
AttributeError exceptions.

As a workaround, we'll rename the "id" ref element as "host_aggr_id".

Also, the watcher-tempest-multinode job is configured to use Focal,
which is no longer supported by Devstack [6]. That being considered,
we'll switch to Ubuntu Jammy (22.04).

While at it, we're disabling Cinder Backup, which isn't used while
testing Watched. It currently causes Devstack failures since it
uses the Swift backend by default, which is disabled.

[1] https://paste.opendev.org/raw/bjQ1uIdbDMnmA1UEhxLL/
[2] https://paste.opendev.org/raw/bNgxqulBwBLYB7tNhrU4/
[3] ab0dcbdda2
[4] https://github.com/python-jsonschema/jsonschema/releases/tag/v4.18.0a1
[5] c23a5dc1c9/referencing/jsonschema.py (L54-L55C18)
[6] https://paste.openstack.org/raw/bSoSyXgbtmq6d9768HQn/

Change-Id: I300620c2ec4857b1e0d402a9b57a637f576eeb24
(cherry picked from commit 922478fbda)

.gitreview

@@ -2,3 +2,4 @@
 host=review.opendev.org
 port=29418
 project=openstack/watcher.git
+defaultbranch=stable/2023.2

.zuul.yaml

@@ -89,7 +89,7 @@
 - job:
     name: watcher-tempest-multinode
     parent: watcher-tempest-functional
-    nodeset: openstack-two-node-focal
+    nodeset: openstack-two-node-jammy
     roles:
       - zuul: openstack/tempest
     group-vars:
@@ -107,6 +107,7 @@
           watcher-api: false
           watcher-decision-engine: true
           watcher-applier: false
+          c-bak: false
           ceilometer: false
           ceilometer-acompute: false
           ceilometer-acentral: false

doc/source/configuration/configuring.rst

@@ -372,7 +372,7 @@ You can configure and install Ceilometer by following the documentation below :
 #. https://docs.openstack.org/ceilometer/latest
 
 The built-in strategy 'basic_consolidation' provided by watcher requires
-"**compute.node.cpu.percent**" and "**cpu_util**" measurements to be collected
+"**compute.node.cpu.percent**" and "**cpu**" measurements to be collected
 by Ceilometer.
 The measurements available depend on the hypervisors that OpenStack manages on
 the specific implementation.

doc/source/contributor/plugin/strategy-plugin.rst

@@ -300,6 +300,6 @@ Using that you can now query the values for that specific metric:
 .. code-block:: py
 
     avg_meter = self.datasource_backend.statistic_aggregation(
-        instance.uuid, 'cpu_util', self.periods['instance'],
+        instance.uuid, 'instance_cpu_usage', self.periods['instance'],
         self.granularity,
         aggregation=self.aggregation_method['instance'])

doc/source/strategies/basic-server-consolidation.rst

@@ -26,8 +26,7 @@ metric                       service name plugins comment
                                                   ``compute_monitors`` option
                                                   to ``cpu.virt_driver`` in
                                                   the nova.conf.
-``cpu_util``                 ceilometer_  none    cpu_util has been removed
-                                                  since Stein.
+``cpu``                      ceilometer_  none
 ============================ ============ ======= ===========================
 
 .. _ceilometer: https://docs.openstack.org/ceilometer/latest/admin/telemetry-measurements.html#openstack-compute

doc/source/strategies/vm_workload_consolidation.rst

@@ -22,8 +22,7 @@ The *vm_workload_consolidation* strategy requires the following metrics:
 ============================ ============ ======= =========================
 metric                       service name plugins comment
 ============================ ============ ======= =========================
-``cpu_util``                 ceilometer_  none    cpu_util has been removed
-                                                  since Stein.
+``cpu``                      ceilometer_  none
 ``memory.resident``          ceilometer_  none
 ``memory``                   ceilometer_  none
 ``disk.root.size``           ceilometer_  none

doc/source/strategies/workload-stabilization.rst

@@ -27,9 +27,8 @@ metric                       service name plugins comment
                                                   to ``cpu.virt_driver`` in the
                                                   nova.conf.
 ``hardware.memory.used``     ceilometer_  SNMP_
-``cpu_util``                 ceilometer_  none    cpu_util has been removed
-                                                  since Stein.
-``memory.resident``          ceilometer_  none
+``cpu``                      ceilometer_  none
+``instance_ram_usage``       ceilometer_  none
 ============================ ============ ======= =============================
 
 .. _ceilometer: https://docs.openstack.org/ceilometer/latest/admin/telemetry-measurements.html#openstack-compute
@@ -107,10 +106,10 @@ parameter            type   default Value         description
                                                   period of all received ones.
 ==================== ====== ===================== =============================
 
-.. |metrics| replace:: ["cpu_util", "memory.resident"]
-.. |thresholds| replace:: {"cpu_util": 0.2, "memory.resident": 0.2}
-.. |weights| replace:: {"cpu_util_weight": 1.0, "memory.resident_weight": 1.0}
-.. |instance_metrics| replace:: {"cpu_util": "compute.node.cpu.percent", "memory.resident": "hardware.memory.used"}
+.. |metrics| replace:: ["instance_cpu_usage", "instance_ram_usage"]
+.. |thresholds| replace:: {"instance_cpu_usage": 0.2, "instance_ram_usage": 0.2}
+.. |weights| replace:: {"instance_cpu_usage_weight": 1.0, "instance_ram_usage_weight": 1.0}
+.. |instance_metrics| replace:: {"instance_cpu_usage": "compute.node.cpu.percent", "instance_ram_usage": "hardware.memory.used"}
 .. |periods| replace:: {"instance": 720, "node": 600}
 
 Efficacy Indicator
@@ -136,8 +135,8 @@ How to use it ?
       at1 workload_balancing --strategy workload_stabilization
 
     $ openstack optimize audit create -a at1 \
-      -p thresholds='{"memory.resident": 0.05}' \
-      -p metrics='["memory.resident"]'
+      -p thresholds='{"instance_ram_usage": 0.05}' \
+      -p metrics='["instance_ram_usage"]'
 
 External Links
 --------------

doc/source/strategies/workload_balance.rst

@@ -24,8 +24,7 @@ The *workload_balance* strategy requires the following metrics:
 ======================= ============ ======= =========================
 metric                  service name plugins comment
 ======================= ============ ======= =========================
-``cpu_util``            ceilometer_  none    cpu_util has been removed
-                                             since Stein.
+``cpu``                 ceilometer_  none
 ``memory.resident``     ceilometer_  none
 ======================= ============ ======= =========================
 
@@ -65,15 +64,16 @@ Configuration
 
 Strategy parameters are:
 
-============== ====== ============= ====================================
+============== ====== ==================== ====================================
 parameter      type   default Value        description
-============== ====== ============= ====================================
-``metrics``    String 'cpu_util'    Workload balance base on cpu or ram
-                                    utilization. choice: ['cpu_util',
-                                    'memory.resident']
+============== ====== ==================== ====================================
+``metrics``    String 'instance_cpu_usage' Workload balance base on cpu or ram
+                                           utilization. Choices:
+                                           ['instance_cpu_usage',
+                                           'instance_ram_usage']
 ``threshold``  Number 25.0                 Workload threshold for migration
 ``period``     Number 300                  Aggregate time period of ceilometer
-============== ====== ============= ====================================
+============== ====== ==================== ====================================
 
 Efficacy Indicator
 ------------------
@@ -95,7 +95,7 @@ How to use it ?
       at1 workload_balancing --strategy workload_balance
 
     $ openstack optimize audit create -a at1 -p threshold=26.0 \
-            -p period=310 -p metrics=cpu_util
+            -p period=310 -p metrics=instance_cpu_usage
 
 External Links
 --------------

tox.ini

@@ -8,7 +8,7 @@ basepython = python3
 usedevelop = True
 allowlist_externals = find
                       rm
-install_command = pip install -c{env:TOX_CONSTRAINTS_FILE:https://releases.openstack.org/constraints/upper/master} {opts} {packages}
+install_command = pip install -c{env:TOX_CONSTRAINTS_FILE:https://releases.openstack.org/constraints/upper/2023.2} {opts} {packages}
 setenv =
    VIRTUAL_ENV={envdir}
 deps =

watcher/decision_engine/datasources/gnocchi.py

@@ -38,7 +38,7 @@ class GnocchiHelper(base.DataSourceBase):
                       host_inlet_temp='hardware.ipmi.node.temperature',
                       host_airflow='hardware.ipmi.node.airflow',
                       host_power='hardware.ipmi.node.power',
-                      instance_cpu_usage='cpu_util',
+                      instance_cpu_usage='cpu',
                       instance_ram_usage='memory.resident',
                       instance_ram_allocated='memory',
                       instance_l3_cache_usage='cpu_l3_cache',
@@ -93,6 +93,25 @@ class GnocchiHelper(base.DataSourceBase):
 
             resource_id = resources[0]['id']
 
+        if meter_name == "instance_cpu_usage":
+            if resource_type != "instance":
+                LOG.warning("Unsupported resource type for metric "
+                            "'instance_cpu_usage': ", resource_type)
+                return
+
+            # The "cpu_util" gauge (percentage) metric has been removed.
+            # We're going to obtain the same result by using the rate of change
+            # aggregate operation.
+            if aggregate not in ("mean", "rate:mean"):
+                LOG.warning("Unsupported aggregate for instance_cpu_usage "
+                            "metric: %s. "
+                            "Supported aggregates: mean, rate:mean ",
+                            aggregate)
+                return
+
+            # TODO(lpetrut): consider supporting other aggregates.
+            aggregate = "rate:mean"
+
         raw_kwargs = dict(
             metric=meter,
             start=start_time,
@@ -117,6 +136,17 @@ class GnocchiHelper(base.DataSourceBase):
                 # Airflow from hardware.ipmi.node.airflow is reported as
                 # 1/10 th of actual CFM
                 return_value *= 10
+            if meter_name == "instance_cpu_usage":
+                # "rate:mean" can return negative values for migrated vms.
+                return_value = max(0, return_value)
+
+                # We're converting the cumulative cpu time (ns) to cpu usage
+                # percentage.
+                vcpus = resource.vcpus
+                if not vcpus:
+                    LOG.warning("instance vcpu count not set, assuming 1")
+                    vcpus = 1
+                return_value *= 100 / (granularity * 10e+8) / vcpus
 
         return return_value
 

watcher/decision_engine/model/collector/nova.py

@@ -48,7 +48,7 @@ class NovaClusterDataModelCollector(base.BaseClusterDataModelCollector):
                     "type": "array",
                     "items": {
                         "anyOf": [
-                            {"$ref": HOST_AGGREGATES + "id"},
+                            {"$ref": HOST_AGGREGATES + "host_aggr_id"},
                             {"$ref": HOST_AGGREGATES + "name"},
                         ]
                     }
@@ -98,7 +98,8 @@ class NovaClusterDataModelCollector(base.BaseClusterDataModelCollector):
                                 "type": "array",
                                 "items": {
                                     "anyOf": [
-                                        {"$ref": HOST_AGGREGATES + "id"},
+                                        {"$ref":
+                                            HOST_AGGREGATES + "host_aggr_id"},
                                         {"$ref": HOST_AGGREGATES + "name"},
                                     ]
                                 }
@@ -129,7 +130,7 @@ class NovaClusterDataModelCollector(base.BaseClusterDataModelCollector):
             "additionalProperties": False
         },
         "host_aggregates": {
-            "id": {
+            "host_aggr_id": {
                 "properties": {
                     "id": {
                         "oneOf": [

watcher/decision_engine/strategy/strategies/workload_balance.py

@@ -295,7 +295,7 @@ class WorkloadBalance(base.WorkloadStabilizationBaseStrategy):
                         self.threshold)
             return self.solution
 
-        # choose the server with largest cpu_util
+        # choose the server with largest cpu usage
         source_nodes = sorted(source_nodes,
                               reverse=True,
                               key=lambda x: (x[self._meter]))

watcher/tests/decision_engine/datasources/test_gnocchi_helper.py

@@ -40,17 +40,25 @@ class TestGnocchiHelper(base.BaseTestCase):
         self.addCleanup(stat_agg_patcher.stop)
 
     def test_gnocchi_statistic_aggregation(self, mock_gnocchi):
+        vcpus = 2
+        mock_instance = mock.Mock(
+            id='16a86790-327a-45f9-bc82-45839f062fdc',
+            vcpus=vcpus)
+
         gnocchi = mock.MagicMock()
+        # cpu time rate of change (ns)
+        mock_rate_measure = 360 * 10e+8 * vcpus * 5.5 / 100
         expected_result = 5.5
 
-        expected_measures = [["2017-02-02T09:00:00.000000", 360, 5.5]]
+        expected_measures = [
+            ["2017-02-02T09:00:00.000000", 360, mock_rate_measure]]
 
         gnocchi.metric.get_measures.return_value = expected_measures
         mock_gnocchi.return_value = gnocchi
 
         helper = gnocchi_helper.GnocchiHelper()
         result = helper.statistic_aggregation(
-            resource=mock.Mock(id='16a86790-327a-45f9-bc82-45839f062fdc'),
+            resource=mock_instance,
             resource_type='instance',
             meter_name='instance_cpu_usage',
             period=300,
@@ -59,6 +67,14 @@ class TestGnocchiHelper(base.BaseTestCase):
         )
         self.assertEqual(expected_result, result)
 
+        gnocchi.metric.get_measures.assert_called_once_with(
+            metric="cpu",
+            start=mock.ANY,
+            stop=mock.ANY,
+            resource_id=mock_instance.uuid,
+            granularity=360,
+            aggregation="rate:mean")
+
     def test_gnocchi_statistic_series(self, mock_gnocchi):
         gnocchi = mock.MagicMock()
         expected_result = {