프로세스

1. 오버클라우드 관리자 인증 정보를 사용하여 언더클라우드 호스트에 로그인합니다(예: overcloudrc ).

2. 자동 스케일링 구성 파일을 위한 디렉터리를 만듭니다.

   $ mkdir -p $HOME/templates/autoscaling/

3. 서비스를 자동 스케일링하는 데 필요한 정의에 대한 리소스 레지스트리 파일을 생성합니다.

   $ cat <<EOF > $HOME/templates/autoscaling/resources-autoscaling.yaml
   resource_registry:
     OS::TripleO::Services::AodhApi: /usr/share/openstack-tripleo-heat-templates/deployment/aodh/aodh-api-container-puppet.yaml
     OS::TripleO::Services::AodhEvaluator: /usr/share/openstack-tripleo-heat-templates/deployment/aodh/aodh-evaluator-container-puppet.yaml
     OS::TripleO::Services::AodhListener: /usr/share/openstack-tripleo-heat-templates/deployment/aodh/aodh-listener-container-puppet.yaml
     OS::TripleO::Services::AodhNotifier: /usr/share/openstack-tripleo-heat-templates/deployment/aodh/aodh-notifier-container-puppet.yaml
     OS::TripleO::Services::CeilometerAgentCentral: /usr/share/openstack-tripleo-heat-templates/deployment/ceilometer/ceilometer-agent-central-container-puppet.yaml
     OS::TripleO::Services::CeilometerAgentNotification: /usr/share/openstack-tripleo-heat-templates/deployment/ceilometer/ceilometer-agent-notification-container-puppet.yaml
     OS::TripleO::Services::ComputeCeilometerAgent: /usr/share/openstack-tripleo-heat-templates/deployment/ceilometer/ceilometer-agent-compute-container-puppet.yaml
     OS::TripleO::Services::GnocchiApi: /usr/share/openstack-tripleo-heat-templates/deployment/gnocchi/gnocchi-api-container-puppet.yaml
     OS::TripleO::Services::GnocchiMetricd: /usr/share/openstack-tripleo-heat-templates/deployment/gnocchi/gnocchi-metricd-container-puppet.yaml
     OS::TripleO::Services::GnocchiStatsd: /usr/share/openstack-tripleo-heat-templates/deployment/gnocchi/gnocchi-statsd-container-puppet.yaml
     OS::TripleO::Services::HeatApi: /usr/share/openstack-tripleo-heat-templates/deployment/heat/heat-api-container-puppet.yaml
     OS::TripleO::Services::HeatEngine: /usr/share/openstack-tripleo-heat-templates/deployment/heat/heat-engine-container-puppet.yaml
     OS::TripleO::Services::Redis: /usr/share/openstack-tripleo-heat-templates/deployment/database/redis-container-puppet.yaml
   EOF

4. 환경 템플릿을 생성하여 자동 확장에 필요한 서비스를 구성합니다.

   cat <<EOF > $HOME/templates/autoscaling/parameters-autoscaling.yaml
   parameter_defaults:
     NotificationDriver: 'messagingv2'
     GnocchiDebug: false
     CeilometerEnableGnocchi: true
     ManagePipeline: true
     ManageEventPipeline: true
   
     EventPipelinePublishers:
       - gnocchi://?archive_policy=generic
     PipelinePublishers:
       - gnocchi://?archive_policy=generic
   
     ManagePolling: true
     ExtraConfig:
       ceilometer::agent::polling::polling_interval: 60
   EOF

   Red Hat Ceph Storage를 시계열 데이터베이스 서비스의 데이터 스토리지 백엔드로 사용하는 경우 매개변수-autoscaling.yaml 파일에 다음 매개변수를 추가합니다.

   parameter_defaults:
     GnocchiRbdPoolName: 'metrics'
     GnocchiBackend: 'rbd'

   메트릭을 저장하려면 먼저 정의된 아카이브 정책 일반 을 생성해야 합니다. 배포 후 이 아카이브 정책을 정의합니다. 자세한 내용은 3.1절. “자동 스케일링을 위한 일반 아카이브 정책 생성”의 내용을 참조하십시오.

5. poll _interval 매개변수를 설정합니다(예: 60초). poll _interval 매개변수 의 값은 아카이브 정책을 생성할 때 정의한 gnocchi 세분화 값과 일치해야 합니다. 자세한 내용은 3.1절. “자동 스케일링을 위한 일반 아카이브 정책 생성”의 내용을 참조하십시오.
6. 오버클라우드를 배포합니다. 자세한 내용은 다음을 참조하십시오. 2.2절. “자동 스케일링을 위해 오버클라우드 배포”

프로세스

1. stack 사용자로 환경에 로그인합니다.

2. director 환경의 경우 stackrc 언더클라우드 인증 정보 파일을 소싱합니다.

   [stack@undercloud ~]$ source ~/stackrc

검증

1. 배포가 성공했는지 확인하고 자동 스케일링을 위해 서비스 API 끝점을 사용할 수 있는지 확인합니다.

   $ openstack endpoint list --service metric
   +----------------------------------+-----------+--------------+--------------+---------+-----------+--------------------------+
   | ID                               | Region    | Service Name | Service Type | Enabled | Interface | URL                      |
   +----------------------------------+-----------+--------------+--------------+---------+-----------+--------------------------+
   | 2956a12327b744b29abd4577837b2e6f | regionOne | gnocchi      | metric       | True    | internal  | http://192.168.25.3:8041 |
   | 583453c58b064f69af3de3479675051a | regionOne | gnocchi      | metric       | True    | admin     | http://192.168.25.3:8041 |
   | fa029da0e2c047fc9d9c50eb6b4876c6 | regionOne | gnocchi      | metric       | True    | public    | http://192.168.25.3:8041 |
   +----------------------------------+-----------+--------------+--------------+---------+-----------+--------------------------+

   $ openstack endpoint list --service alarming
   +----------------------------------+-----------+--------------+--------------+---------+-----------+--------------------------+
   | ID                               | Region    | Service Name | Service Type | Enabled | Interface | URL                      |
   +----------------------------------+-----------+--------------+--------------+---------+-----------+--------------------------+
   | 08c70ec137b44ed68590f4d5c31162bb | regionOne | aodh         | alarming     | True    | internal  | http://192.168.25.3:8042 |
   | 194042887f3d4eb4b638192a0fe60996 | regionOne | aodh         | alarming     | True    | admin     | http://192.168.25.3:8042 |
   | 2604b693740245ed8960b31dfea1f963 | regionOne | aodh         | alarming     | True    | public    | http://192.168.25.3:8042 |
   +----------------------------------+-----------+--------------+--------------+---------+-----------+--------------------------+

   오버클라우드 인증 정보를 사용하여 heat 서비스를 확인합니다.

   (undercloud) [stack@undercloud-0 ~]$ source ~/overcloudrc
   
   $ openstack endpoint list --service orchestration
   +----------------------------------+-----------+--------------+---------------+---------+-----------+-------------------------------------------+
   | ID                               | Region    | Service Name | Service Type  | Enabled | Interface | URL                                       |
   +----------------------------------+-----------+--------------+---------------+---------+-----------+-------------------------------------------+
   | 00966a24dd4141349e12680307c11848 | regionOne | heat         | orchestration | True    | admin     | http://192.168.25.3:8004/v1/%(tenant_id)s |
   | 831e411bb6d44f6db9f5103d659f901e | regionOne | heat         | orchestration | True    | public    | http://192.168.25.3:8004/v1/%(tenant_id)s |
   | d5be22349add43ae95be4284a42a4a60 | regionOne | heat         | orchestration | True    | internal  | http://192.168.25.3:8004/v1/%(tenant_id)s |
   +----------------------------------+-----------+--------------+---------------+---------+-----------+-------------------------------------------+

2. 서비스가 오버클라우드에서 실행 중인지 확인합니다.

   $ sudo podman ps --filter=name='heat|gnocchi|ceilometer|aodh'
   CONTAINER ID  IMAGE                                                                  COMMAND      CREATED         STATUS                       PORTS       NAMES
   31e75d62367f  registry.redhat.io/rhosp-rhel9/openstack-aodh-api:17.1                 kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              aodh_api
   77acf3487736  registry.redhat.io/rhosp-rhel9/openstack-aodh-listener:17.1            kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              aodh_listener
   29ec47b69799  registry.redhat.io/rhosp-rhel9/openstack-aodh-evaluator:17.1           kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              aodh_evaluator
   43efaa86c769  registry.redhat.io/rhosp-rhel9/openstack-aodh-notifier:17.1            kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              aodh_notifier
   0ac8cb2c7470  registry.redhat.io/rhosp-rhel9/openstack-aodh-api:17.1                 kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              aodh_api_cron
   31b55e091f57  registry.redhat.io/rhosp-rhel9/openstack-ceilometer-central:17.1       kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              ceilometer_agent_central
   5f61331a17d8  registry.redhat.io/rhosp-rhel9/openstack-ceilometer-compute:17.1       kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              ceilometer_agent_compute
   7c5ef75d8f1b  registry.redhat.io/rhosp-rhel9/openstack-ceilometer-notification:17.1  kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              ceilometer_agent_notification
   88fa57cc1235  registry.redhat.io/rhosp-rhel9/openstack-gnocchi-api:17.1              kolla_start  23 minutes ago  Up 23 minutes ago (healthy)              gnocchi_api
   0f05a58197d5  registry.redhat.io/rhosp-rhel9/openstack-gnocchi-metricd:17.1          kolla_start  23 minutes ago  Up 23 minutes ago (healthy)              gnocchi_metricd
   6d806c285500  registry.redhat.io/rhosp-rhel9/openstack-gnocchi-statsd:17.1           kolla_start  23 minutes ago  Up 23 minutes ago (healthy)              gnocchi_statsd
   7c02cac34c69  registry.redhat.io/rhosp-rhel9/openstack-heat-api:17.1                 kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              heat_api_cron
   d3903df545ce  registry.redhat.io/rhosp-rhel9/openstack-heat-api:17.1                 kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              heat_api
   db1d33506e3d  registry.redhat.io/rhosp-rhel9/openstack-heat-api-cfn:17.1             kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              heat_api_cfn
   051446294c70  registry.redhat.io/rhosp-rhel9/openstack-heat-engine:17.1              kolla_start  27 minutes ago  Up 27 minutes ago (healthy)              heat_engine

3. 시계열 데이터베이스 서비스를 사용할 수 있는지 확인합니다.

   $ openstack metric status --fit-width
   +-----------------------------------------------------+--------------------------------------------------------------------------------------------------------------------+
   | Field                                               | Value                                                                                                              |
   +-----------------------------------------------------+--------------------------------------------------------------------------------------------------------------------+
   | metricd/processors                                  | ['host-80.general.local.0.a94fbf77-1ac0-49ed-bfe2-a89f014fde01',                                             |
   |                                                     | 'host-80.general.local.3.28ca78d7-a80e-4515-8060-233360b410eb',                                              |
   |                                                     | 'host-80.general.local.1.7e8b5a5b-2ca1-49be-bc22-25f51d67c00a',                                              |
   |                                                     | 'host-80.general.local.2.3c4fe59e-23cd-4742-833d-42ff0a4cb692']                                              |
   | storage/number of metric having measures to process | 0                                                                                                                  |
   | storage/total number of measures to process         | 0                                                                                                                  |
   +-----------------------------------------------------+--------------------------------------------------------------------------------------------------------------------+

프로세스

1. stack 사용자로 환경에 로그인합니다.

2. director 환경의 경우 stackrc 파일을 소싱합니다.

   [stack@undercloud ~]$ source ~/stackrc

3. $HOME/templates/autoscaling/parameters-autoscaling.yaml 에 정의된 아카이브 정책을 생성합니다.

   $ openstack metric archive-policy create generic \
     --back-window 0 \
     --definition timespan:'4:00:00',granularity:'0:01:00',points:240 \
     --aggregation-method 'rate:mean' \
     --aggregation-method 'mean'

프로세스

1. stack 사용자로 환경에 로그인합니다.

   $ source ~/stackrc

2. 자동 스케일링 그룹에 대한 인스턴스 구성을 저장할 디렉터리를 만듭니다.

   $ mkdir -p $HOME/templates/autoscaling/vnf/

3. 인스턴스 구성 템플릿을 생성합니다(예: $HOME/templates/autoscaling/vnf/instance.yaml ).

4. instance.yaml 파일에 다음 구성을 추가합니다.

   cat <<EOF > $HOME/templates/autoscaling/vnf/instance.yaml
   heat_template_version: wallaby
   description: Template to control scaling of VNF instance
   
   parameters:
     metadata:
       type: json
     image:
       type: string
       description: image used to create instance
       default: fedora36
     flavor:
       type: string
       description: instance flavor to be used
       default: m1.small
     key_name:
       type: string
       description: keypair to be used
       default: default
     network:
       type: string
       description: project network to attach instance to
       default: private
     external_network:
       type: string
       description: network used for floating IPs
       default: public
   
   resources:
     vnf:
       type: OS::Nova::Server
       properties:
         flavor: {get_param: flavor}
         key_name: {get_param: key_name}
         image: { get_param: image }
         metadata: { get_param: metadata }
         networks:
           - port: { get_resource: port }
   
     port:
       type: OS::Neutron::Port
       properties:
         network: {get_param: network}
         security_groups:
           - basic
   
     floating_ip:
       type: OS::Neutron::FloatingIP
       properties:
         floating_network: {get_param: external_network }
   
     floating_ip_assoc:
       type: OS::Neutron::FloatingIPAssociation
       properties:
         floatingip_id: { get_resource: floating_ip }
         port_id: { get_resource: port }
   EOF

   • parameters 매개변수는 이 새 리소스에 대한 사용자 지정 매개 변수를 정의합니다.
   • resources 매개변수의 vnf 하위 매개변수는 OS::Heat::AutoScalingGroup 에서 참조하는 사용자 지정 하위 리소스의 이름을 정의합니다(예: OS::Nova::Server::VNF ).

5. heat 템플릿에서 참조할 리소스를 생성합니다.

   $ cat <<EOF > $HOME/templates/autoscaling/vnf/resources.yaml
   resource_registry:
     "OS::Nova::Server::VNF": $HOME/templates/autoscaling/vnf/instance.yaml
   EOF

6. heat에 대한 배포 템플릿을 생성하여 인스턴스 스케일링을 제어합니다.

   $ cat <<EOF > $HOME/templates/autoscaling/vnf/template.yaml
   heat_template_version: wallaby
   description:  Example auto scale group, policy and alarm
   resources:
     scaleup_group:
       type: OS::Heat::AutoScalingGroup
       properties:
         max_size: 3
         min_size: 1
         #desired_capacity: 1
         resource:
           type: OS::Nova::Server::VNF
           properties:
             metadata: {"metering.server_group": {get_param: "OS::stack_id"}}
   
     scaleup_policy:
       type: OS::Heat::ScalingPolicy
       properties:
         adjustment_type: change_in_capacity
         auto_scaling_group_id: { get_resource: scaleup_group }
         cooldown: 60
         scaling_adjustment: 1
   
     scaledown_policy:
       type: OS::Heat::ScalingPolicy
       properties:
         adjustment_type: change_in_capacity
         auto_scaling_group_id: { get_resource: scaleup_group }
         cooldown: 60
         scaling_adjustment: -1
   
     cpu_alarm_high:
       type: OS::Aodh::GnocchiAggregationByResourcesAlarm
       properties:
         description: Scale up instance if CPU > 50%
         metric: cpu
         aggregation_method: rate:mean
         granularity: 60
         evaluation_periods: 3
         threshold: 60000000000.0
         resource_type: instance
         comparison_operator: gt
         alarm_actions:
           - str_replace:
               template: trust+url
               params:
                 url: {get_attr: [scaleup_policy, signal_url]}
         query:
           list_join:
             - ''
             - - {'=': {server_group: {get_param: "OS::stack_id"}}}
   
     cpu_alarm_low:
       type: OS::Aodh::GnocchiAggregationByResourcesAlarm
       properties:
         description: Scale down instance if CPU < 20%
         metric: cpu
         aggregation_method: rate:mean
         granularity: 60
         evaluation_periods: 3
         threshold: 24000000000.0
         resource_type: instance
         comparison_operator: lt
         alarm_actions:
           - str_replace:
               template: trust+url
               params:
                 url: {get_attr: [scaledown_policy, signal_url]}
         query:
           list_join:
             - ''
             - - {'=': {server_group: {get_param: "OS::stack_id"}}}
   
   outputs:
     scaleup_policy_signal_url:
       value: {get_attr: [scaleup_policy, alarm_url]}
   
     scaledown_policy_signal_url:
       value: {get_attr: [scaledown_policy, alarm_url]}
   EOF

   참고

   스택의 출력은 정보이며 ScalingPolicy 또는 AutoScalingGroup에서 참조되지 않습니다. 출력을 보려면 openstack stack show <stack_name> 명령을 사용합니다.

프로세스

1. 오버클라우드 관리자 인증 정보를 사용하여 언더클라우드 호스트에 로그인합니다. 예를 들면 overcloudrc:

   (undercloud)$ source ~/overcloudrc

2. 스택을 생성합니다.

   $ openstack stack create \
     -t $HOME/templates/autoscaling/vnf/template.yaml \
     -e $HOME/templates/autoscaling/vnf/resources.yaml \
     vnf

검증

1. 스택이 생성되었는지 확인합니다.

   $ openstack stack show vnf -c id -c stack_status
   +--------------+--------------------------------------+
   | Field        | Value                                |
   +--------------+--------------------------------------+
   | id           | cb082cbd-535e-4779-84b0-98925e103f5e |
   | stack_status | CREATE_COMPLETE                      |
   +--------------+--------------------------------------+

2. 알람, 확장 정책, 자동 스케일링 그룹을 포함하여 스택 리소스가 생성되었는지 확인합니다.

   $ export STACK_ID=$(openstack stack show vnf -c id -f value)

   $ openstack stack resource list $STACK_ID
   +------------------+--------------------------------------+----------------------------------------------+-----------------+----------------------+
   | resource_name    | physical_resource_id                 | resource_type                                | resource_status | updated_time         |
   +------------------+--------------------------------------+----------------------------------------------+-----------------+----------------------+
   | cpu_alarm_high   | d72d2e0d-1888-4f89-b888-02174c48e463 | OS::Aodh::GnocchiAggregationByResourcesAlarm | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
   | scaleup_policy   | 1c4446b7242e479090bef4b8075df9d4     | OS::Heat::ScalingPolicy                      | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
   | cpu_alarm_low    | b9c04ef4-8b57-4730-af03-1a71c3885914 | OS::Aodh::GnocchiAggregationByResourcesAlarm | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
   | scaledown_policy | a5af7faf5a1344849c3425cb2c5f18db     | OS::Heat::ScalingPolicy                      | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
   | scaleup_group    | 9609f208-6d50-4b8f-836e-b0222dc1e0b1 | OS::Heat::AutoScalingGroup                   | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
   +------------------+--------------------------------------+----------------------------------------------+-----------------+----------------------+

3. 스택 생성을 통해 인스턴스가 시작되었는지 확인합니다.

   $ openstack server list --long | grep $STACK_ID
   
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7 | vn-dvaxcqb-6bqh2qd2fpif-hicmkm5dzjug-vnf-ywrydc5wqjjc | ACTIVE | None       | Running     | private=192.168.100.61, 192.168.25.99 | fedora36   | a6aa7b11-1b99-4c62-a43b-d0b7c77f4b72 | m1.small    | 5cd46fec-50c2-43d5-89e8-ed3fa7660852 | nova              | host-80.localdomain | metering.server_group='cb082cbd-535e-4779-84b0-98925e103f5e' |

4. 스택에 대한 알람이 생성되었는지 확인합니다.

   1. 알람 ID를 나열합니다. 알람 상태는 일정 기간 동안 충분하지 않은 데이터 상태에 있을 수 있습니다. 최소 시간은 데이터 수집 및 데이터 스토리지 세분성 설정의 폴링 간격입니다.

      $ openstack alarm list
      +--------------------------------------+--------------------------------------------+---------------------------------+-------+----------+---------+
      | alarm_id                             | type                                       | name                            | state | severity | enabled |
      +--------------------------------------+--------------------------------------------+---------------------------------+-------+----------+---------+
      | b9c04ef4-8b57-4730-af03-1a71c3885914 | gnocchi_aggregation_by_resources_threshold | vnf-cpu_alarm_low-pve5eal6ykst  | alarm | low      | True    |
      | d72d2e0d-1888-4f89-b888-02174c48e463 | gnocchi_aggregation_by_resources_threshold | vnf-cpu_alarm_high-5xx7qvfsurxe | ok    | low      | True    |
      +--------------------------------------+--------------------------------------------+---------------------------------+-------+----------+---------+

   2. 스택의 리소스를 나열하고 cpu_alarm_high 및 cpu_alarm_low 리소스의 physical_resource_id 값을 기록해 둡니다.

      $ openstack stack resource list $STACK_ID
      +------------------+--------------------------------------+----------------------------------------------+-----------------+----------------------+
      | resource_name    | physical_resource_id                 | resource_type                                | resource_status | updated_time         |
      +------------------+--------------------------------------+----------------------------------------------+-----------------+----------------------+
      | cpu_alarm_high   | d72d2e0d-1888-4f89-b888-02174c48e463 | OS::Aodh::GnocchiAggregationByResourcesAlarm | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
      | scaleup_policy   | 1c4446b7242e479090bef4b8075df9d4     | OS::Heat::ScalingPolicy                      | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
      | cpu_alarm_low    | b9c04ef4-8b57-4730-af03-1a71c3885914 | OS::Aodh::GnocchiAggregationByResourcesAlarm | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
      | scaledown_policy | a5af7faf5a1344849c3425cb2c5f18db     | OS::Heat::ScalingPolicy                      | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
      | scaleup_group    | 9609f208-6d50-4b8f-836e-b0222dc1e0b1 | OS::Heat::AutoScalingGroup                   | CREATE_COMPLETE | 2022-10-06T23:08:37Z |
      +------------------+--------------------------------------+----------------------------------------------+-----------------+----------------------+

      physical_resource_id 값은 openstack alarm list 명령의 출력에 있는 alarm_id 와 일치해야 합니다.

5. 스택에 대한 지표 리소스가 있는지 확인합니다. server_group 쿼리의 값을 스택 ID로 설정합니다.

   $ openstack metric resource search --sort-column launched_at -c id -c display_name -c launched_at -c deleted_at --type instance server_group="$STACK_ID"
   +--------------------------------------+-------------------------------------------------------+----------------------------------+------------+
   | id                                   | display_name                                          | launched_at                      | deleted_at |
   +--------------------------------------+-------------------------------------------------------+----------------------------------+------------+
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7 | vn-dvaxcqb-6bqh2qd2fpif-hicmkm5dzjug-vnf-ywrydc5wqjjc | 2022-10-06T23:09:28.496566+00:00 | None       |
   +--------------------------------------+-------------------------------------------------------+----------------------------------+------------+

6. 스택을 통해 생성된 인스턴스 리소스에 대한 측정이 있는지 확인합니다.

   $ openstack metric aggregates --resource-type instance --sort-column timestamp '(metric cpu rate:mean)' server_group="$STACK_ID"
   +----------------------------------------------------+---------------------------+-------------+---------------+
   | name                                               | timestamp                 | granularity |         value |
   +----------------------------------------------------+---------------------------+-------------+---------------+
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:11:00+00:00 |        60.0 | 69470000000.0 |
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:12:00+00:00 |        60.0 | 81060000000.0 |
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:13:00+00:00 |        60.0 | 82840000000.0 |
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:14:00+00:00 |        60.0 | 66660000000.0 |
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:15:00+00:00 |        60.0 |  7360000000.0 |
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:16:00+00:00 |        60.0 |  3150000000.0 |
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:17:00+00:00 |        60.0 |  2760000000.0 |
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:18:00+00:00 |        60.0 |  3470000000.0 |
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:19:00+00:00 |        60.0 |  2770000000.0 |
   | 62e1b27c-8d9d-44a5-a0f0-80e7e6d437c7/cpu/rate:mean | 2022-10-06T23:20:00+00:00 |        60.0 |  2700000000.0 |
   +----------------------------------------------------+---------------------------+-------------+---------------+

프로세스

1. stack 사용자로 호스트 환경에 로그인합니다.

2. director 환경의 경우 stackrc 파일을 소싱합니다.

   [stack@undercloud ~]$ source ~/stackrc

3. 인스턴스에 로그인합니다.

   $ ssh -i ~/mykey.pem cirros@192.168.122.8

4. 여러 dd 명령을 실행하여 부하를 생성합니다.

   [instance ~]$ sudo dd if=/dev/zero of=/dev/null &
   [instance ~]$ sudo dd if=/dev/zero of=/dev/null &
   [instance ~]$ sudo dd if=/dev/zero of=/dev/null &

5. 실행 중인 인스턴스를 종료하고 호스트로 돌아갑니다.

6. dd 명령을 실행한 후 인스턴스에서 100% CPU 사용을 기대할 수 있습니다. 경고가 트리거되었는지 확인합니다.

   $ openstack alarm list
   +--------------------------------------+--------------------------------------------+-------------------------------------+-------+----------+---------+
   | alarm_id                             | type                                       | name                                | state | severity | enabled |
   +--------------------------------------+--------------------------------------------+-------------------------------------+-------+----------+---------+
   | 022f707d-46cc-4d39-a0b2-afd2fc7ab86a | gnocchi_aggregation_by_resources_threshold | example-cpu_alarm_high-odj77qpbld7j | alarm | low      | True    |
   | 46ed2c50-e05a-44d8-b6f6-f1ebd83af913 | gnocchi_aggregation_by_resources_threshold | example-cpu_alarm_low-m37jvnm56x2t  | ok    | low      | True    |
   +--------------------------------------+--------------------------------------------+-------------------------------------+-------+----------+---------+

7. 약 60초 후에 오케스트레이션에서 다른 인스턴스를 시작하여 그룹에 추가합니다. 인스턴스가 생성되었는지 확인하려면 다음 명령을 입력합니다.

   $ openstack server list
   +--------------------------------------+-------------------------------------------------------+--------+------------+-------------+---------------------------------------+
   | ID                                   | Name                                                  | Status | Task State | Power State | Networks                              |
   +--------------------------------------+-------------------------------------------------------+--------+------------+-------------+---------------------------------------+
   | 477ee1af-096c-477c-9a3f-b95b0e2d4ab5 | ex-3gax-4urpikl5koff-yrxk3zxzfmpf-server-2hde4tp4trnk | ACTIVE | -          | Running     | internal1=10.10.10.13, 192.168.122.17 |
   | e1524f65-5be6-49e4-8501-e5e5d812c612 | ex-3gax-5f3a4og5cwn2-png47w3u2vjd-server-vaajhuv4mj3j | ACTIVE | -          | Running     | internal1=10.10.10.9, 192.168.122.8   |
   +--------------------------------------+-------------------------------------------------------+--------+------------+-------------+---------------------------------------+

8. 또 다른 짧은 기간 후에 오케스트레이션 서비스가 세 개의 인스턴스로 자동 스케일링되었는지 확인합니다. 구성은 최대 3개의 인스턴스로 설정됩니다. 세 개의 인스턴스가 있는지 확인합니다.

   $ openstack server list
   +--------------------------------------+-------------------------------------------------------+--------+------------+-------------+---------------------------------------+
   | ID                                   | Name                                                  | Status | Task State | Power State | Networks                              |
   +--------------------------------------+-------------------------------------------------------+--------+------------+-------------+---------------------------------------+
   | 477ee1af-096c-477c-9a3f-b95b0e2d4ab5 | ex-3gax-4urpikl5koff-yrxk3zxzfmpf-server-2hde4tp4trnk | ACTIVE | -          | Running     | internal1=10.10.10.13, 192.168.122.17 |
   | e1524f65-5be6-49e4-8501-e5e5d812c612 | ex-3gax-5f3a4og5cwn2-png47w3u2vjd-server-vaajhuv4mj3j | ACTIVE | -          | Running     | internal1=10.10.10.9, 192.168.122.8   |
   | 6c88179e-c368-453d-a01a-555eae8cd77a | ex-3gax-fvxz3tr63j4o-36fhftuja3bw-server-rhl4sqkjuy5p | ACTIVE | -          | Running     | internal1=10.10.10.5, 192.168.122.5   |
   +--------------------------------------+-------------------------------------------------------+--------+------------+-------------+---------------------------------------+

프로세스

1. 워크로드 인스턴스 내에서 실행 중인 dd 프로세스를 종료하고 오케스트레이션이 인스턴스를 다시 축소하기 시작하는 것을 관찰합니다.

   $ killall dd

2. stack 사용자로 호스트 환경에 로그인합니다.

3. director 환경의 경우 stackrc 파일을 소싱합니다.

   [stack@undercloud ~]$ source ~/stackrc

4. dd 프로세스를 중지하면 cpu_alarm_low 이벤트 경고가 트리거됩니다. 결과적으로 오케스트레이션은 자동으로 축소되고 인스턴스를 제거하기 시작합니다. 해당 알람이 트리거되었는지 확인합니다.

   $ openstack alarm list
   +--------------------------------------+--------------------------------------------+-------------------------------------+-------+----------+---------+
   | alarm_id                             | type                                       | name                                | state | severity | enabled |
   +--------------------------------------+--------------------------------------------+-------------------------------------+-------+----------+---------+
   | 022f707d-46cc-4d39-a0b2-afd2fc7ab86a | gnocchi_aggregation_by_resources_threshold | example-cpu_alarm_high-odj77qpbld7j | ok    | low      | True    |
   | 46ed2c50-e05a-44d8-b6f6-f1ebd83af913 | gnocchi_aggregation_by_resources_threshold | example-cpu_alarm_low-m37jvnm56x2t  | alarm | low      | True    |
   +--------------------------------------+--------------------------------------------+-------------------------------------+-------+----------+---------+

   몇 분 후에 오케스트레이션은 인스턴스 수를 scaleup_group 정의의 min_size 매개변수에 정의된 최소 값으로 지속적으로 줄입니다. 이 시나리오에서는 min_size 매개변수가 1 로 설정됩니다.

프로세스

1. stack 사용자로 호스트 환경에 로그인합니다.

2. director 환경의 경우 stackrc 파일을 소싱합니다.

   [stack@undercloud ~]$ source ~/stackrc

3. 상태 전환에 대한 정보를 검색하려면 스택 이벤트 레코드를 나열합니다.

   $ openstack stack event list example
   2017-03-06 11:12:43Z [example]: CREATE_IN_PROGRESS  Stack CREATE started
   2017-03-06 11:12:43Z [example.scaleup_group]: CREATE_IN_PROGRESS  state changed
   2017-03-06 11:13:04Z [example.scaleup_group]: CREATE_COMPLETE  state changed
   2017-03-06 11:13:04Z [example.scaledown_policy]: CREATE_IN_PROGRESS  state changed
   2017-03-06 11:13:05Z [example.scaleup_policy]: CREATE_IN_PROGRESS  state changed
   2017-03-06 11:13:05Z [example.scaledown_policy]: CREATE_COMPLETE  state changed
   2017-03-06 11:13:05Z [example.scaleup_policy]: CREATE_COMPLETE  state changed
   2017-03-06 11:13:05Z [example.cpu_alarm_low]: CREATE_IN_PROGRESS  state changed
   2017-03-06 11:13:05Z [example.cpu_alarm_high]: CREATE_IN_PROGRESS  state changed
   2017-03-06 11:13:06Z [example.cpu_alarm_low]: CREATE_COMPLETE  state changed
   2017-03-06 11:13:07Z [example.cpu_alarm_high]: CREATE_COMPLETE  state changed
   2017-03-06 11:13:07Z [example]: CREATE_COMPLETE  Stack CREATE completed successfully
   2017-03-06 11:19:34Z [example.scaleup_policy]: SIGNAL_COMPLETE  alarm state changed from alarm to alarm (Remaining as alarm due to 1 samples outside threshold, most recent: 95.4080102993)
   2017-03-06 11:25:43Z [example.scaleup_policy]: SIGNAL_COMPLETE  alarm state changed from alarm to alarm (Remaining as alarm due to 1 samples outside threshold, most recent: 95.8869217299)
   2017-03-06 11:33:25Z [example.scaledown_policy]: SIGNAL_COMPLETE  alarm state changed from ok to alarm (Transition to alarm due to 1 samples outside threshold, most recent: 2.73931707966)
   2017-03-06 11:39:15Z [example.scaledown_policy]: SIGNAL_COMPLETE  alarm state changed from alarm to alarm (Remaining as alarm due to 1 samples outside threshold, most recent: 2.78110858552)

4. 알람 기록 로그를 읽습니다.

   $ openstack alarm-history show 022f707d-46cc-4d39-a0b2-afd2fc7ab86a
   +----------------------------+------------------+-----------------------------------------------------------------------------------------------------+--------------------------------------+
   | timestamp                  | type             | detail                                                                                              | event_id                             |
   +----------------------------+------------------+-----------------------------------------------------------------------------------------------------+--------------------------------------+
   | 2017-03-06T11:32:35.510000 | state transition | {"transition_reason": "Transition to ok due to 1 samples inside threshold, most recent:             | 25e0e70b-3eda-466e-abac-42d9cf67e704 |
   |                            |                  | 2.73931707966", "state": "ok"}                                                                      |                                      |
   | 2017-03-06T11:17:35.403000 | state transition | {"transition_reason": "Transition to alarm due to 1 samples outside threshold, most recent:         | 8322f62c-0d0a-4dc0-9279-435510f81039 |
   |                            |                  | 95.0964497325", "state": "alarm"}                                                                   |                                      |
   | 2017-03-06T11:15:35.723000 | state transition | {"transition_reason": "Transition to ok due to 1 samples inside threshold, most recent:             | 1503bd81-7eba-474e-b74e-ded8a7b630a1 |
   |                            |                  | 3.59330523447", "state": "ok"}                                                                      |                                      |
   | 2017-03-06T11:13:06.413000 | creation         | {"alarm_actions": ["trust+http://fca6e27e3d524ed68abdc0fd576aa848:delete@192.168.122.126:8004/v1/fd | 224f15c0-b6f1-4690-9a22-0c1d236e65f6 |
   |                            |                  | 1c345135be4ee587fef424c241719d/stacks/example/d9ef59ed-b8f8-4e90-bd9b-                              |                                      |
   |                            |                  | ae87e73ef6e2/resources/scaleup_policy/signal"], "user_id": "a85f83b7f7784025b6acdc06ef0a8fd8",      |                                      |
   |                            |                  | "name": "example-cpu_alarm_high-odj77qpbld7j", "state": "insufficient data", "timestamp":           |                                      |
   |                            |                  | "2017-03-06T11:13:06.413455", "description": "Scale up if CPU > 80%", "enabled": true,              |                                      |
   |                            |                  | "state_timestamp": "2017-03-06T11:13:06.413455", "rule": {"evaluation_periods": 1, "metric":        |                                      |
   |                            |                  | "cpu_util", "aggregation_method": "mean", "granularity": 300, "threshold": 80.0, "query": "{\"=\":   |                                      |
   |                            |                  | {\"server_group\": \"d9ef59ed-b8f8-4e90-bd9b-ae87e73ef6e2\"}}", "comparison_operator": "gt",        |                                      |
   |                            |                  | "resource_type": "instance"}, "alarm_id": "022f707d-46cc-4d39-a0b2-afd2fc7ab86a",                   |                                      |
   |                            |                  | "time_constraints": [], "insufficient_data_actions": null, "repeat_actions": true, "ok_actions":    |                                      |
   |                            |                  | null, "project_id": "fd1c345135be4ee587fef424c241719d", "type":                                     |                                      |
   |                            |                  | "gnocchi_aggregation_by_resources_threshold", "severity": "low"}                                    |                                      |
   +----------------------------+------------------+-----------------------------------------------------------------------------------------------------+-------------------------------------

5. heat가 기존 스택에 대해 수집하는 스케일 아웃 또는 스케일 다운 작업의 레코드를 보려면 awk 명령을 사용하여 heat-engine.log 를 구문 분석할 수 있습니다.

   $ awk '/Stack UPDATE started/,/Stack CREATE completed successfully/ {print $0}' /var/log/containers/heat/heat-engine.log

6. aodh 관련 정보를 보려면 aodh-evaluator.log 를 검사합니다.

   $ sudo grep -i alarm /var/log/containers/aodh/aodh-evaluator.log | grep -i transition