查看插件Releases版本 (https://github.com/huaweicloud/cloudeye-exporter/releases) ，获取cloudeye-exporter下载地址，下载解压安装。

mkdir cloudeye-exporter & cd cloudeye-exporter

wget https://github.com/huaweicloud/cloudeye-exporter/releases/download/v2.0.6/cloudeye-exporter.v2.0.6.tar.gz

3.2 制作容器镜像

1、需要编写Dockerfile文件 这里使用centos用作基础镜像

FROM centos COPY cloudeye-exporter logs.yml metric.yml /root/ WORKDIR /root CMD ["/root/cloudeye-exporter"]

2、构建容器镜像

docker build -t swr.cn-north-4.myhuaweicloud.com/k8s-solution/cloudeye-exporter:v2.0.6 --platform=linux/amd64 .

 

3、推送至镜像仓库

建议使用华为云SWR镜像仓库

3.3 配置cloudeye-exporter的访问鉴权

1、编辑clouds.yml文件配置公有云信息

cloudeye-exporter 启动时需要使用该配置文件进行云服务的访问鉴权

global: port: ":8087" # 监听端口 :8087代表在全部网络接口上开启监听8087端口，限定内部访问也可以指定IP例如：192.168.1.100:8087 scrape_batch_size: 300 auth: auth_url: "https://iam.cn-north-4.myhuaweicloud.com/v3" project_name: "cn-north-4" # 华为云项目名称，可以在“华为云->统一身份认证服务->项目”中查看 access_key: "" # IAM用户访问密钥 您可参考3.1章节使用命令行输入加密后的ak sk，避免在配置文件中明文配置AK SK secret_key: "" region: "cn-north-4" # 区域ID

2、基于该配置文件创建kubernetes secrets

kubectl create secret generic clouds-exporter --from-file=clouds.yml -n monitoring
容器化部署需要将该配置以secrets形式挂载给cloudeye-exporter

3.4 CCE集群(k8s集群)部署cloudeye-exporter

1、首先部署负载和service

apiVersion: apps/v1 kind: Deployment metadata: name: cloudeye-exporter namespace: monitoring labels: app: cloudeye-exporter spec: replicas: 1 selector: matchLabels: app: cloudeye-exporter template: metadata: labels: app: cloudeye-exporter spec: volumes: - name: cloudeye secret: secretName: clouds-exporter imagePullSecrets: - name: default-secret containers: - name: cloudeye-exporter image: swr.cn-north-4.myhuaweicloud.com/k8s-solution/cloudeye-exporter:v2.0.6 ports: - containerPort: 8087 resources: limits: cpu: 500m memory: 1Gi requests: cpu: 100m memory: 500Mi volumeMounts: - name: cloudeye mountPath: "/root/clouds.yml" subPath: clouds.yml --- apiVersion: v1 kind: Service metadata: name: cloudeye-exporter namespace: monitoring labels: app: cloudeye-exporter spec: selector: app: cloudeye-exporter ports: - name: ces targetPort: 8087 #业务监听端口 port: 8087 protocol: TCP type: ClusterIP

部署成功，查看Pod信息。访问pod指标端点，确认指标源是否能暴露指标。

curl http://podIP:8087/metrics?services='SYS.VPC'

cloudeye-exporter Pod实例作为Prometheus抓取指标的源端，可以暴露监控数据。

查看Service，确认访问Service能否获取数据

2、注意

需要注意: 由于cloudeye-exporter需要访问公网端点:   iam.huaweicloud.com。如果您使用的kuberntes平台是CCE turbo集群，需要对容器网段配置公网snat。否则指标数据抓取会失败。

3.5 Prometheus对接cloudeye-exporter获取指标

修改prometheus中的prometheus.yml文件配置。由于现在k8s集群中都会采用prometheus-operator形态部署Prometheus。所以我们需要编写ServiceMonitor进行指标的获取。

1、以监控华为云VPC,ELB服务为例

抓取规则cloudeye-exporter-servicemonitor.yaml 如下:

apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: cloudeye-exporter namespace: monitoring labels: app: cloudeye-exporter spec: endpoints: - interval: 1m scrapeTimeout: 1m port: ces scheme: http params: services: ['SYS.VPC,SYS.ELB'] namespaceSelector: matchNames: - monitoring selector: matchLabels: app: cloudeye-exporter

2、将上述抓取规则于集群中创建。等待片刻可观察到Prometheus已经成功抓取

3、至此，cloudeye-exporter成功接入Prometheus。

3.6 接入Grafana大盘

华为云社区提供了若干个云服务现成的dashborad。我们可以拿来使用。

https://github.com/huaweicloud/cloudeye-exporter/tree/v2.0.6/grafana_dashboard/templates

例如: 使用VPC云服务的dashboard。

1、将该dashboard的json文件上传到grafana中

2、发现异常

会发现dashboard并未产生数据

apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: cloudeye-exporter namespace: monitoring labels: app: cloudeye-exporter spec: endpoints: - interval: 1m scrapeTimeout: 1m port: ces scheme: http params: services: ['SYS.VPC,SYS.ELB'] # 配置该任务获取企业项目信息，用于华为云云服务的dashboard - interval: 1m scrapeTimeout: 1m port: ces path: "/eps-info" scheme: http namespaceSelector: matchNames: - monitoring selector: matchLabels: app: cloudeye-exporter

在集群中将上述指标抓取规则更新后，等待片刻后。

4、前往Prometheus页面可查看到，新的抓取任务已成功运行

5、再次观察Grafana

此时再前往Grafana前端查看dashboard: 华为云VPC云服务dashboard已成功展示

6、导入ELB grafana dashboard

华为云ELB监控信息也成功展示

四 、延伸扩展

目前已支持的Grafana Dashboard有:

• 云搜索服务 CSS
• 云专线 DCAAS
• 分布式缓存服务 DCS
• 弹性云服务器 ECS
• 弹性负载均衡 ELB
• 关系型数据库 RDS
• Web应用防火墙 WAF
• 弹性公网IP和带宽 VPC

点击关注，第一时间了解华为云新鲜技术~