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自动扩展实例

Red Hat OpenStack Platform 17.1

在 Red Hat OpenStack Platform 中配置自动扩展

OpenStack Documentation Team

摘要

使用 Red Hat OpenStack Platform 遥测组件和 heat 模板为工作负载自动启动实例。

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在 JIRA 中提供文档反馈

使用 Create Issue 表单在 OpenShift (RHOSO)或更早版本的 Red Hat OpenStack Platform (RHOSP)上提供有关 Red Hat OpenStack Services 文档的反馈。当您为 RHOSO 或 RHOSP 文档创建问题时，这个问题将在 RHOSO Jira 项目中记录，您可以在其中跟踪您的反馈的进度。

要完成 Create Issue 表单，请确保您已登录到 JIRA。如果您没有红帽 JIRA 帐户，您可以在 https://issues.redhat.com 创建一个帐户。

  1. 点击以下链接打开 Create Issue 页面： Create Issue
  2. 完成 Summary 和 Description 字段。在 Description 字段中，包含文档 URL、章节或章节号以及问题的详细描述。不要修改表单中的任何其他字段。
  3. 点 Create。

第 1 章 自动扩展组件简介
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使用遥测组件收集有关 Red Hat OpenStack Platform (RHOSP)环境的数据，如 CPU、存储和内存用量。您可以启动和扩展实例，以响应工作负载需求和资源可用性。您可以定义遥测数据的上限和下限，以控制编排服务(heat)模板中的实例扩展。

使用以下遥测组件控制自动实例扩展：

  • 数据收集 ：Telemetry 使用数据收集服务(Ceilometer)来收集指标和事件数据。
  • 存储 ：Telemetry 将指标数据存储在时间序列数据库服务(gnocchi)中。
  • 警报 ：Telemetry 使用 Alarming 服务(aodh)根据规则针对 Ceilometer 收集的指标或事件数据触发操作。

1.1. 用于自动扩展的数据收集服务(Ceilometer)
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您可以使用 Ceilometer 收集 Red Hat OpenStack Platform (RHOSP)组件的计量和事件信息的数据。

Ceilometer 服务使用三个代理从 RHOSP 组件收集数据：

  • 计算代理(ceilometer-agent-compute) ：在每个 Compute 节点上运行并轮询资源使用统计数据。
  • 中央代理(ceilometer-agent-central) ：在 Controller 节点上运行轮询，以轮询资源使用不是由 Compute 节点提供的资源的统计数据。
  • 通知代理(ceilometer-agent-notification) ：在 Controller 节点上运行，并使用来自消息队列的消息来构建事件和计量数据。

Ceilometer 代理使用发布者将数据发送到对应的端点，如时间序列数据库服务(gnocchi)。

其他资源

1.1.1. Publishers
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在 Red Hat OpenStack Platform (RHOSP)中，您可以使用多种传输方法将收集的数据传送到存储或外部系统中，如 Service Telemetry Framework (STF)。

当您启用 gnocchi publisher 时，测量和资源信息会存储为时间序列数据。

Gnocchi 是一个时间序列数据库，可用于将指标存储在 SQL 中。警报服务(aodh)和编排服务(heat)使用存储在 gnocchi 中的数据进行自动扩展。

其他资源

1.3. 警报服务(aodh)
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您可以配置 Alarming 服务(aodh)，以基于针对 Ceilometer 收集的指标数据的规则触发操作，并存储在 gnocchi 中。警报可以处于以下状态之一：

  • OK ：指标或事件处于可接受的状态。
  • trigger ：指标或事件不在定义的 Ok 状态之外。
  • 数据不足 ：警报状态未知，例如，没有请求粒度的数据，或者检查尚未执行，以此类推。

1.4. 用于自动扩展的编排服务(heat)
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director 使用编排服务(heat)模板作为 overcloud 部署的模板格式。Heat 模板通常以 YAML 格式表示。模板的目的是定义和创建堆栈，这是 heat 创建的资源集合，以及资源的配置。资源是 Red Hat OpenStack Platform (RHOSP)中的对象，可以包含计算资源、网络配置、安全组、扩展规则和自定义资源。

第 2 章 配置和部署 overcloud 进行自动扩展
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您必须为 overcloud 上的服务配置模板来启用自动扩展。

流程

  1. 在部署 overcloud 进行自动扩展前，为自动扩展服务创建环境模板和资源 registry。如需更多信息，请参阅 第 2.1 节 “配置 overcloud 进行自动扩展”。
  2. 部署 overcloud。如需更多信息，请参阅 第 2.2 节 “部署 overcloud 进行自动扩展”。

2.1. 配置 overcloud 进行自动扩展
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创建部署提供自动扩展的服务所需的环境模板和资源 registry。

流程

  1. 使用您的 overcloud 管理员凭据登录 undercloud 主机，如 overcloudrc。

  2. 为自动扩展配置文件创建目录： 

    $ mkdir -p $HOME/templates/autoscaling/
    Copy to Clipboard Toggle word wrap

  3. 为服务自动扩展所需的定义创建资源 registry 文件： 

    $ 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-pacemaker-puppet.yaml
EOF
    Copy to Clipboard Toggle word wrap

  4. 创建环境模板来配置自动扩展所需的服务： 

    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
    Copy to Clipboard Toggle word wrap

    如果您使用 Red Hat Ceph Storage 作为时间序列数据库服务的数据存储后端，请在 parameters-autoscaling.yaml 文件中添加以下参数： 

    parameter_defaults:
  GnocchiRbdPoolName: 'metrics'
  GnocchiBackend: 'rbd'
    Copy to Clipboard Toggle word wrap

    您必须先创建定义的归档策略 通用，然后才能存储指标。您可以在部署后定义此归档策略。如需更多信息，请参阅 第 3.1 节 “创建用于自动扩展的通用归档策略”。

  5. 设置 polling_interval 参数，例如 60 秒。polling_interval 参数的值必须与您在创建归档策略时定义的 gnocchi granularity 值匹配。如需更多信息，请参阅 第 3.1 节 “创建用于自动扩展的通用归档策略”。
  6. 部署 overcloud。如需更多信息，请参阅 第 2.2 节 “部署 overcloud 进行自动扩展”。

2.2. 部署 overcloud 进行自动扩展
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您可以使用 director 部署 overcloud 进行自动扩展。

先决条件

流程

2.2.1. 使用 director 部署 overcloud 进行自动扩展
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使用 director 部署 overcloud。

先决条件

流程

  1. 以 stack 用户身份登录 undercloud。

  2. 查找 stackrc undercloud 凭证文件： 

    [stack@director ~]$ source ~/stackrc
    Copy to Clipboard Toggle word wrap

  3. 使用其他环境文件将自动扩展环境文件添加到堆栈中，并部署 overcloud： 

    (undercloud)$ openstack overcloud deploy --templates \
  -e [your environment files] \
  -e $HOME/templates/autoscaling/parameters-autoscaling.yaml \
  -e $HOME/templates/autoscaling/resources-autoscaling.yaml
    Copy to Clipboard Toggle word wrap

2.3. 验证 overcloud 部署以进行自动扩展
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验证自动扩展服务是否已部署并已启用。验证输出示例可能与您的用例不同。

先决条件

流程

  1. 以 stack 用户身份登录您的环境。

  2. 对于 director 环境，提供 overcloudrc overcloud 凭据文件： 

    $ source ~/overcloudrc
    Copy to Clipboard Toggle word wrap

验证

  1. 验证部署是否成功，并确保自动扩展的服务 API 端点可用： 

    $ 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 |
+----------------------------------+-----------+--------------+--------------+---------+-----------+--------------------------+
    Copy to Clipboard Toggle word wrap 
    $ 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 |
+----------------------------------+-----------+--------------+--------------+---------+-----------+--------------------------+
    Copy to Clipboard Toggle word wrap

    使用 overcloud 凭证检查 heat 服务： 

    $ 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 |
+----------------------------------+-----------+--------------+---------------+---------+-----------+-------------------------------------------+
    Copy to Clipboard Toggle word wrap

  2. 验证服务是否在 overcloud 上运行： 

    $ 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
    Copy to Clipboard Toggle word wrap

  3. 验证时间序列数据库服务是否可用： 

    $ 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                                                                                                                  |
+-----------------------------------------------------+--------------------------------------------------------------------------------------------------------------------+
    Copy to Clipboard Toggle word wrap

第 3 章 使用 heat 服务进行自动扩展
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在部署 overcloud 中提供自动扩展所需的服务后，您必须配置 overcloud 环境，以便编排服务(heat)可以管理实例以进行自动扩展。

先决条件

流程

3.1. 创建用于自动扩展的通用归档策略
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在 overcloud 中部署用于自动扩展的服务后，您必须配置 overcloud 环境，以便编排服务(heat)能够管理用于自动扩展的实例。

先决条件

流程

  1. 以 stack 用户身份登录您的环境。

  2. 对于 director 环境，提供 overcloudrc overcloud 凭据文件： 

    $ source ~/overcloudrc
    Copy to Clipboard Toggle word wrap

  3. 创建 $HOME/templates/autoscaling/parameters-autoscaling.yaml 中定义的归档策略： 

    $ 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'
    Copy to Clipboard Toggle word wrap

验证

  • 验证是否已创建归档策略： 

    $ openstack metric archive-policy show generic
+---------------------+--------------------------------------------------------+
| Field               | Value                                                  |
+---------------------+--------------------------------------------------------+
| aggregation_methods | mean, rate:mean                                        |
| back_window         | 0                                                      |
| definition          | - timespan: 4:00:00, granularity: 0:01:00, points: 240 |
| name                | generic                                                |
+---------------------+--------------------------------------------------------+
    Copy to Clipboard Toggle word wrap

3.2. 为自动扩展实例配置 heat 模板
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您可以配置编排服务(heat)模板来创建实例，并配置在触发时创建和扩展实例的警报。

注意

此流程使用示例值，您必须更改为适合您的环境。

先决条件

流程

  1. 以 stack 用户身份登录您的环境。 

    $ source ~/overcloudrc
    Copy to Clipboard Toggle word wrap

  2. 创建存放自动扩展组实例配置的目录： 

    $ mkdir -p $HOME/templates/autoscaling/vnf/
    Copy to Clipboard Toggle word wrap
  3. 创建实例配置模板，如 $HOME/templates/autoscaling/vnf/instance.yaml。

  4. 在 instance.yaml 文件中添加以下配置： 

    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
    Copy to Clipboard Toggle word wrap
    • parameters 参数为此新资源定义自定义参数。
    • resources 参数的 vnf 子参数定义了在 OS::Heat::AutoScalingGroup 中引用的自定义子资源的名称，例如 OS::Nova::Server::VNF。

  5. 创建要在 heat 模板中引用的资源： 

    $ cat <<EOF > $HOME/templates/autoscaling/vnf/resources.yaml
resource_registry:
  "OS::Nova::Server::VNF": $HOME/templates/autoscaling/vnf/instance.yaml
EOF
    Copy to Clipboard Toggle word wrap

  6. 为 heat 创建部署模板以控制实例扩展： 

    $ 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
    Copy to Clipboard Toggle word wrap
    注意

    堆栈上的输出是信息性的，在 ScalingPolicy 或 AutoScalingGroup 中不引用。要查看输出，请使用 openstack stack show <stack_name> 命令。

3.3. 创建用于自动扩展的堆栈部署
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为工作的 VNF 自动扩展示例创建堆栈部署。

先决条件

流程

  1. 使用您的 overcloud 管理员凭证登录 undercloud 主机，如 overcloudrc ： 

    (undercloud)$ source ~/overcloudrc
    Copy to Clipboard Toggle word wrap

  2. 您必须首先启动临时 Heat 进程才能使用 openstack stack 命令： 

    (undercloud)$ openstack tripleo launch heat --heat-dir /home/stack/overcloud-deploy/overcloud/heat-launcher --restore-db
(undercloud)$ export OS_CLOUD=heat
    Copy to Clipboard Toggle word wrap

  3. 创建堆栈： 

    $ openstack stack create \
  -t $HOME/templates/autoscaling/vnf/template.yaml \
  -e $HOME/templates/autoscaling/vnf/resources.yaml \
  vnf
    Copy to Clipboard Toggle word wrap

验证

  1. 验证堆栈是否已成功创建： 

    $ openstack stack show vnf -c id -c stack_status
+--------------+--------------------------------------+
| Field        | Value                                |
+--------------+--------------------------------------+
| id           | cb082cbd-535e-4779-84b0-98925e103f5e |
| stack_status | CREATE_COMPLETE                      |
+--------------+--------------------------------------+
    Copy to Clipboard Toggle word wrap

  2. 验证堆栈资源是否已创建，包括警报、扩展策略和自动扩展组： 

    $ export STACK_ID=$(openstack stack show vnf -c id -f value)
    Copy to Clipboard Toggle word wrap 
    $ 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 |
+------------------+--------------------------------------+----------------------------------------------+-----------------+----------------------+
    Copy to Clipboard Toggle word wrap

  3. 通过堆栈创建验证实例是否已启动： 

    $ 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' |
    Copy to Clipboard Toggle word wrap

  4. 验证是否为堆栈创建了警报：

    1. 列出警报 ID。在一段时间内，警报的状态可能位于 数据不足 的状态。最短的时间是数据收集和数据存储粒度设置的轮询间隔： 

      $ 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    |
+--------------------------------------+--------------------------------------------+---------------------------------+-------+----------+---------+
      Copy to Clipboard Toggle word wrap

    2. 列出堆栈的资源，并记录下 cpu_alarm_high 和 cpu_alarm_low 资源的 physical_resource_id 值。 

      $ 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 |
+------------------+--------------------------------------+----------------------------------------------+-----------------+----------------------+
      Copy to Clipboard Toggle word wrap

      physical_resource_id 的值必须与 openstack alarm list 命令的输出中的 alarm_id 匹配。

  5. 验证堆栈是否存在指标资源。将 server_group 查询的值设置为堆栈 ID： 

    $ 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       |
+--------------------------------------+-------------------------------------------------------+----------------------------------+------------+
    Copy to Clipboard Toggle word wrap

  6. 验证通过堆栈创建的实例资源是否存在测量： 

    $ 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 |
+----------------------------------------------------+---------------------------+-------------+---------------+
    Copy to Clipboard Toggle word wrap

  7. 从 undercloud 中删除临时 Heat 进程： 

    (undercloud)$ openstack tripleo launch heat --kill
    Copy to Clipboard Toggle word wrap

第 4 章 测试和故障排除自动扩展
复制链接

使用编排服务(heat)根据阈值定义自动扩展实例。要排除您的环境，您可以在日志文件和历史记录记录中查找错误。

4.1. 测试自动扩展实例
复制链接

您可以使用编排服务(heat)根据 cpu_ alarm_high 阈值定义自动扩展实例。当 CPU 使用达到 threshold 参数中定义的值时，另一个实例会启动以平衡负载。template.yaml 文件中的 阈值 设置为 80%。

流程

  1. 以 stack 用户身份登录主机环境。

  2. 对于 director 环境，提供 overcloudrc 文件： 

    $ source ~/overcloudrc
    Copy to Clipboard Toggle word wrap

  3. 登录到实例： 

    $ ssh -i ~/mykey.pem cirros@192.168.122.8
    Copy to Clipboard Toggle word wrap

  4. 运行多个 dd 命令来生成负载： 

    [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 &
    Copy to Clipboard Toggle word wrap
  5. 从正在运行的实例退出，再返回到主机。

  6. 运行 dd 命令后，您可以预期在实例中使用 100% CPU。验证警报是否已触发： 

    $ 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    |
+--------------------------------------+--------------------------------------------+-------------------------------------+-------+----------+---------+
    Copy to Clipboard Toggle word wrap

  7. 大约 60 秒后，编排将启动另一个实例并将它添加到组中。要验证实例是否已创建，请输入以下命令： 

    $ 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   |
+--------------------------------------+-------------------------------------------------------+--------+------------+-------------+---------------------------------------+
    Copy to Clipboard Toggle word wrap

  8. 在另一个短时间内，观察编排服务已自动缩放到三个实例。该配置设置为最多三个实例。验证有三个实例： 

    $ 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   |
+--------------------------------------+-------------------------------------------------------+--------+------------+-------------+---------------------------------------+
    Copy to Clipboard Toggle word wrap

4.2. 测试自动缩减实例
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您可以使用编排服务(heat)根据 cpu_ alarm_low 阈值自动扩展实例。在本例中，当 CPU 使用率低于 5% 时，实例将缩减。

流程

  1. 从工作负载实例中，终止正在运行的 dd 进程，并观察编排开始缩减实例。 

    $ killall dd
    Copy to Clipboard Toggle word wrap
  2. 以 stack 用户身份登录主机环境。

  3. 对于 director 环境，提供 overcloudrc 文件： 

    $ source ~/overcloudrc
    Copy to Clipboard Toggle word wrap

  4. 当您停止 dd 进程时，这将触发 cpu_alarm_low 事件 警报。因此，编排开始缩减和删除实例。验证对应的警报是否已触发： 

    $ 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    |
+--------------------------------------+--------------------------------------------+-------------------------------------+-------+----------+---------+
    Copy to Clipboard Toggle word wrap

    几分钟后，编排持续将实例数量减少到 scaleup_group 定义的 min_size 参数中定义的最小值。在这种情况下，min_size 参数设置为 1。

4.3. 自动扩展故障排除
复制链接

如果您的环境无法正常工作，您可以在日志文件和历史记录记录中查找错误。

流程

  1. 以 stack 用户身份登录主机环境。

  2. 对于 director 环境，提供 overcloudrc 文件： 

    $ source ~/overcloudrc
    Copy to Clipboard Toggle word wrap

  3. 您必须首先启动临时 Heat 进程才能使用 openstack stack 命令： 

    (undercloud)$ openstack tripleo launch heat --heat-dir /home/stack/overcloud-deploy/overcloud/heat-launcher --restore-db
(undercloud)$ export OS_CLOUD=heat
    Copy to Clipboard Toggle word wrap

  4. 要检索有关状态转换的信息，请列出堆栈事件记录： 

    $ 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)
    Copy to Clipboard Toggle word wrap

  5. 读取警报历史记录日志： 

    $ 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"}                                    |                                      |
+----------------------------+------------------+-----------------------------------------------------------------------------------------------------+-------------------------------------
    Copy to Clipboard Toggle word wrap

  6. 要查看 heat 为现有堆栈收集的横向扩展或缩减操作的记录，您可以使用 awk 命令解析 heat-engine.log ： 

    $ awk '/Stack UPDATE started/,/Stack CREATE completed successfully/ {print $0}' /var/log/containers/heat/heat-engine.log
    Copy to Clipboard Toggle word wrap

  7. 要查看 aodh 相关信息，请检查 aodh-evaluator.log ： 

    $ sudo grep -i alarm /var/log/containers/aodh/aodh-evaluator.log | grep -i transition
    Copy to Clipboard Toggle word wrap

  8. 从 undercloud 中删除临时 Heat 进程： 

    (undercloud)$ openstack tripleo launch heat --kill
    Copy to Clipboard Toggle word wrap

当使用 OS::Heat::Autoscaling heat 编配模板 (HOT) 并为 CPU 设置阈值时，其代表以纳秒为单位的 CPU 时间，它是一个基于分配给实例工作负载虚拟 CPU 数量的动态值。在本参考指南中，我们将探索如何在使用 Gnocchi rate:mean aggregration 方法时，将如何计算和表达 CPU 纳秒值作为百分比。

4.4.1. 计算 CPU 遥测值的百分比
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CPU 遥测存储在 Gnocchi (OpenStack 时间序列数据存储中)，以纳秒为单位的 CPU 使用率。当使用 CPU 遥测来定义自动扩展阈值时，将值表示为 CPU 使用率百分比，因为定义阈值时更自然。当定义用作自动扩展组的扩展策略时，我们可以取所需的阈值定义为百分比，并在策略定义中计算所需的阈值（以纳秒为单位）。

Expand
value (ns)粒度(s)百分比

60000000000

60

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54000000000

60

90

48000000000

60

80

42000000000

60

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36000000000

60

60

30000000000

60

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24000000000

60

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18000000000

60

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12000000000

60

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6000000000

60

10

4.4.2. 以百分比的形式显示实例工作负载 vCPU
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您可以使用 openstack metric aggregates 命令显示 gnocchi-stored CPU 遥测数据作为百分比而不是实例的 nanosecond 值。

先决条件

  • 使用自动扩展组资源创建 heat 堆栈，导致实例工作负载。

流程

  1. 以云管理员身份登录到您的 OpenStack 环境。

  2. 检索自动扩展组 heat 堆栈的 ID： 

    $ openstack stack show vnf -c id -c stack_status
+--------------+--------------------------------------+
| Field        | Value                                |
+--------------+--------------------------------------+
| id           | e0a15cee-34d1-418a-ac79-74ad07585730 |
| stack_status | CREATE_COMPLETE                      |
+--------------+--------------------------------------+
    Copy to Clipboard Toggle word wrap

  3. 将堆栈 ID 的值设置为环境变量： 

    $ export STACK_ID=$(openstack stack show vnf -c id -f value)
    Copy to Clipboard Toggle word wrap

  4. 按资源类型实例（服务器 ID）将指标返回为聚合，其值计算为百分比。聚合返回为 CPU 时间的纳秒值。我们将该数量除以 1000000000，以获得以秒为单位的值。然后，我们按我们的粒度来划分值，本例中为 60 秒。然后，该值将通过 100 乘以一个百分比。最后，我们将总值除以分配给实例的类别提供的 vCPU 数量，在本示例中，值为 2 vCPU，从而以 CPU 时间百分比表示的值： 

    $ openstack metric aggregates --resource-type instance --sort-column timestamp --sort-descending '(/ (* (/ (/ (metric cpu rate:mean) 1000000000) 60) 100) 2)' server_group="$STACK_ID"
+----------------------------------------------------+---------------------------+-------------+--------------------+
| name                                               | timestamp                 | granularity |              value |
+----------------------------------------------------+---------------------------+-------------+--------------------+
| 61bfb555-9efb-46f1-8559-08dec90f94ed/cpu/rate:mean | 2022-11-07T21:03:00+00:00 |        60.0 |  3.158333333333333 |
| 61bfb555-9efb-46f1-8559-08dec90f94ed/cpu/rate:mean | 2022-11-07T21:02:00+00:00 |        60.0 | 2.6333333333333333 |
| 199b0cb9-6ed6-4410-9073-0fb2e7842b65/cpu/rate:mean | 2022-11-07T21:02:00+00:00 |        60.0 |  2.533333333333333 |
| 61bfb555-9efb-46f1-8559-08dec90f94ed/cpu/rate:mean | 2022-11-07T21:01:00+00:00 |        60.0 |  2.833333333333333 |
| 199b0cb9-6ed6-4410-9073-0fb2e7842b65/cpu/rate:mean | 2022-11-07T21:01:00+00:00 |        60.0 | 3.0833333333333335 |
| 61bfb555-9efb-46f1-8559-08dec90f94ed/cpu/rate:mean | 2022-11-07T21:00:00+00:00 |        60.0 | 13.450000000000001 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T21:00:00+00:00 |        60.0 |               2.45 |
| 199b0cb9-6ed6-4410-9073-0fb2e7842b65/cpu/rate:mean | 2022-11-07T21:00:00+00:00 |        60.0 | 2.6166666666666667 |
| 61bfb555-9efb-46f1-8559-08dec90f94ed/cpu/rate:mean | 2022-11-07T20:59:00+00:00 |        60.0 | 60.583333333333336 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T20:59:00+00:00 |        60.0 |               2.35 |
| 199b0cb9-6ed6-4410-9073-0fb2e7842b65/cpu/rate:mean | 2022-11-07T20:59:00+00:00 |        60.0 |              2.525 |
| 61bfb555-9efb-46f1-8559-08dec90f94ed/cpu/rate:mean | 2022-11-07T20:58:00+00:00 |        60.0 |  71.35833333333333 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T20:58:00+00:00 |        60.0 |              3.025 |
| 199b0cb9-6ed6-4410-9073-0fb2e7842b65/cpu/rate:mean | 2022-11-07T20:58:00+00:00 |        60.0 |                9.3 |
| 61bfb555-9efb-46f1-8559-08dec90f94ed/cpu/rate:mean | 2022-11-07T20:57:00+00:00 |        60.0 |  66.19166666666668 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T20:57:00+00:00 |        60.0 |              2.275 |
| 199b0cb9-6ed6-4410-9073-0fb2e7842b65/cpu/rate:mean | 2022-11-07T20:57:00+00:00 |        60.0 |  56.31666666666667 |
| 61bfb555-9efb-46f1-8559-08dec90f94ed/cpu/rate:mean | 2022-11-07T20:56:00+00:00 |        60.0 |  59.50833333333333 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T20:56:00+00:00 |        60.0 |              2.375 |
| 199b0cb9-6ed6-4410-9073-0fb2e7842b65/cpu/rate:mean | 2022-11-07T20:56:00+00:00 |        60.0 | 63.949999999999996 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T20:55:00+00:00 |        60.0 | 15.558333333333335 |
| 199b0cb9-6ed6-4410-9073-0fb2e7842b65/cpu/rate:mean | 2022-11-07T20:55:00+00:00 |        60.0 |              93.85 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T20:54:00+00:00 |        60.0 |  59.54999999999999 |
| 199b0cb9-6ed6-4410-9073-0fb2e7842b65/cpu/rate:mean | 2022-11-07T20:54:00+00:00 |        60.0 |  61.23333333333334 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T20:53:00+00:00 |        60.0 |  74.73333333333333 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T20:52:00+00:00 |        60.0 |  57.86666666666667 |
| a95ab818-fbe8-4acd-9f7b-58e24ade6393/cpu/rate:mean | 2022-11-07T20:51:00+00:00 |        60.0 | 60.416666666666664 |
+----------------------------------------------------+---------------------------+-------------+--------------------+
    Copy to Clipboard Toggle word wrap

4.4.3. 为实例工作负载检索可用的遥测
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检索实例工作负载的可用遥测，并以百分比表示 vCPU 使用率。

先决条件

  • 使用自动扩展组资源创建 heat 堆栈，导致实例工作负载。

流程

  1. 以云管理员身份登录到您的 OpenStack 环境。

  2. 检索自动扩展组 heat 堆栈的 ID： 

    $ openstack stack show vnf -c id -c stack_status
+--------------+--------------------------------------+
| Field        | Value                                |
+--------------+--------------------------------------+
| id           | e0a15cee-34d1-418a-ac79-74ad07585730 |
| stack_status | CREATE_COMPLETE                      |
+--------------+--------------------------------------+
    Copy to Clipboard Toggle word wrap

  3. 将堆栈 ID 的值设置为环境变量： 

    $ export STACK_ID=$(openstack stack show vnf -c id -f value)
    Copy to Clipboard Toggle word wrap

  4. 检索您要返回数据的工作负载实例的 ID。我们使用服务器列表长表单和过滤属于自动扩展组的实例： 

    $ openstack server list --long --fit-width | grep "metering.server_group='$STACK_ID'"
| bc1811de-48ed-44c1-ae22-c01f36d6cb02 | vn-xlfb4jb-yhbq6fkk2kec-qsu2lr47zigs-vnf-y27wuo25ce4e | ACTIVE | None       | Running     | private=192.168.100.139, 192.168.25.179 | fedora36   | d21f1aaa-0077-4313-8a46-266c39b705c1 | m1.small    | 692533fe-0912-417e-b706-5d085449db53 | nova              | host.localdomain | metering.server_group='e0a15cee-34d1-418a-ac79-74ad07585730' |
    Copy to Clipboard Toggle word wrap

  5. 为返回的实例工作负载名称设置实例 ID： 

    $ INSTANCE_NAME='vn-xlfb4jb-yhbq6fkk2kec-qsu2lr47zigs-vnf-y27wuo25ce4e' ; export INSTANCE_ID=$(openstack server list --name $INSTANCE_NAME -c ID -f value)
    Copy to Clipboard Toggle word wrap

  6. 验证已经为实例资源 ID 存储了指标。如果没有可用的指标，则自实例创建后，可能没有足够的时间。如果有足够的时间，您可以检查 /var/log/containers/ceilometer/ 中数据收集服务的日志，并在 /var/log/containers/gnocchi/ 中检查时间序列数据库服务 gnocchi 的日志： 

    $ openstack metric resource show --column metrics $INSTANCE_ID
+---------+---------------------------------------------------------------------+
| Field   | Value                                                               |
+---------+---------------------------------------------------------------------+
| metrics | compute.instance.booting.time: 57ca241d-764b-4c58-aa32-35760d720b08 |
|         | cpu: d7767d7f-b10c-4124-8893-679b2e5d2ccd                           |
|         | disk.ephemeral.size: 038b11db-0598-4cfd-9f8d-4ba6b725375b           |
|         | disk.root.size: 843f8998-e644-41f6-8635-e7c99e28859e                |
|         | memory.usage: 1e554370-05ac-4107-98d8-9330265db750                  |
|         | memory: fbd50c0e-90fa-4ad9-b0df-f7361ceb4e38                        |
|         | vcpus: 0629743e-6baa-4e22-ae93-512dc16bac85                         |
+---------+---------------------------------------------------------------------+
    Copy to Clipboard Toggle word wrap

  7. 验证资源指标是否有可用的测量结果，并记录粒度值，因为我们在运行 openstack metric aggregates 命令时使用它： 

    $ openstack metric measures show --resource-id $INSTANCE_ID --aggregation rate:mean cpu
+---------------------------+-------------+---------------+
| timestamp                 | granularity |         value |
+---------------------------+-------------+---------------+
| 2022-11-08T14:12:00+00:00 |        60.0 | 71920000000.0 |
| 2022-11-08T14:13:00+00:00 |        60.0 | 88920000000.0 |
| 2022-11-08T14:14:00+00:00 |        60.0 | 76130000000.0 |
| 2022-11-08T14:15:00+00:00 |        60.0 | 17640000000.0 |
| 2022-11-08T14:16:00+00:00 |        60.0 |  3330000000.0 |
| 2022-11-08T14:17:00+00:00 |        60.0 |  2450000000.0 |
...
    Copy to Clipboard Toggle word wrap

  8. 通过查看实例工作负载的配置类别来检索应用到工作负载实例的 vCPU 内核数： 

    $ openstack server show $INSTANCE_ID -cflavor -f value
m1.small (692533fe-0912-417e-b706-5d085449db53)

$ openstack flavor show 692533fe-0912-417e-b706-5d085449db53 -c vcpus -f value
2
    Copy to Clipboard Toggle word wrap

  9. 按资源类型实例（服务器 ID）将指标返回为聚合，其值计算为百分比。聚合返回为 CPU 时间的纳秒值。我们将该数量除以 1000000000，以获得以秒为单位的值。然后，我们按我们的粒度划分值，本例中为 60 秒（之前使用 openstack metric measures show 命令检索）。然后，该值将通过 100 乘以一个百分比。最后，我们将总值除以分配给实例的类别提供的 vCPU 数量，在本示例中，值为 2 vCPU，从而以 CPU 时间百分比表示的值： 

    $ openstack metric aggregates --resource-type instance --sort-column timestamp --sort-descending '(/ (* (/ (/ (metric cpu rate:mean) 1000000000) 60) 100) 2)' id=$INSTANCE_ID
+----------------------------------------------------+---------------------------+-------------+--------------------+
| name                                               | timestamp                 | granularity |              value |
+----------------------------------------------------+---------------------------+-------------+--------------------+
| bc1811de-48ed-44c1-ae22-c01f36d6cb02/cpu/rate:mean | 2022-11-08T14:26:00+00:00 |        60.0 |               2.45 |
| bc1811de-48ed-44c1-ae22-c01f36d6cb02/cpu/rate:mean | 2022-11-08T14:25:00+00:00 |        60.0 |             11.075 |
| bc1811de-48ed-44c1-ae22-c01f36d6cb02/cpu/rate:mean | 2022-11-08T14:24:00+00:00 |        60.0 |               61.3 |
| bc1811de-48ed-44c1-ae22-c01f36d6cb02/cpu/rate:mean | 2022-11-08T14:23:00+00:00 |        60.0 |  74.78333333333332 |
| bc1811de-48ed-44c1-ae22-c01f36d6cb02/cpu/rate:mean | 2022-11-08T14:22:00+00:00 |        60.0 | 55.383333333333326 |
...
    Copy to Clipboard Toggle word wrap

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