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Kubernetes 系列(六):Kubernetes部署Prometheus监控

2019-03-31 00:53 513 查看

1.创建命名空间

新建一个yaml文件命名为monitor-namespace.yaml,写入如下内容:

apiVersion: v1
kind: Namespace
metadata:
name: monitoring

执行如下命令创建monitoring命名空间:

kubectl create -f monitor-namespace.yaml

2.创建ClusterRole

你需要对上面创建的命名空间分配集群的读取权限,以便Prometheus可以通过Kubernetes的API获取集群的资源目标。

新建一个yaml文件命名为cluster-role.yaml,写入如下内容:

apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRole
metadata:
name: prometheus
rules:
- apiGroups: [""]
resources:
- nodes
- nodes/proxy
- services
- endpoints
- pods
verbs: ["get", "list", "watch"]
- apiGroups:
- extensions
resources:
- ingresses
verbs: ["get", "list", "watch"]
- nonResourceURLs: ["/metrics"]
verbs: ["get"]
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRoleBinding
metadata:
name: prometheus
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: prometheus
subjects:
- kind: ServiceAccount
name: default
namespace: monitoring

执行如下命令创建:

kubectl create -f cluster-role.yaml

 

3.创建Config Map

我们需要创建一个Config Map保存后面创建Prometheus容器用到的一些配置,这些配置包含了从Kubernetes集群中动态发现pods和运行中的服务。
新建一个yaml文件命名为config-map.yaml,写入如下内容:

apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus-server-conf
labels:
name: prometheus-server-conf
namespace: monitoring
data:
prometheus.yml: |-
global:
scrape_interval: 5s
evaluation_interval: 5s
scrape_configs:
- job_name: 'kubernetes-apiservers'
kubernetes_sd_configs:
- role: endpoints
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
relabel_configs:
- source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
action: keep
regex: default;kubernetes;https

- job_name: 'kubernetes-nodes'
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
kubernetes_sd_configs:
- role: node
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- target_label: __address__
replacement: kubernetes.default.svc:443
- source_labels: [__meta_kubernetes_node_name]
regex: (.+)
target_label: __metrics_path__
replacement: /api/v1/nodes/${1}/proxy/metrics

- job_name: 'kubernetes-pods'
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
action: keep
regex: true
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
action: replace
target_label: __metrics_path__
regex: (.+)
- source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
action: replace
regex: ([^:]+)(?::\d+)?;(\d+)
replacement: $1:$2
target_label: __address__
- action: labelmap
regex: __meta_kubernetes_pod_label_(.+)
- source_labels: [__meta_kubernetes_namespace]
action: replace
target_label: kubernetes_namespace
- source_labels: [__meta_kubernetes_pod_name]
action: replace
target_label: kubernetes_pod_name

- job_name: 'kubernetes-cadvisor'
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
kubernetes_sd_configs:
- role: node
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
- target_label: __address__
replacement: kubernetes.default.svc:443
- source_labels: [__meta_kubernetes_node_name]
regex: (.+)
target_label: __metrics_path__
replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor

- job_name: 'kubernetes-service-endpoints'
kubernetes_sd_configs:
- role: endpoints
relabel_configs:
- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
action: keep
regex: true
- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]
action: replace
target_label: __scheme__
regex: (https?)
- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]
action: replace
target_label: __metrics_path__
regex: (.+)
- source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]
action: replace
target_label: __address__
regex: ([^:]+)(?::\d+)?;(\d+)
replacement: $1:$2
- action: labelmap
regex: __meta_kubernetes_service_label_(.+)
- source_labels: [__meta_kubernetes_namespace]
action: replace
target_label: kubernetes_namespace
- source_labels: [__meta_kubernetes_service_name]
action: replace
target_label: kubernetes_name

执行如下命令进行创建:

kubectl create -f config-map.yaml -n monitoring

 

4.创建Deployment模式的Prometheus

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: prometheus-deployment
namespace: monitoring
spec:
replicas: 1
template:
metadata:
labels:
app: prometheus-server
spec:
containers:
- name: prometheus
image: prom/prometheus:v2.3.2
args:
- "--config.file=/etc/prometheus/prometheus.yml"
- "--storage.tsdb.path=/prometheus/"
ports:
- containerPort: 9090
volumeMounts:
- name: prometheus-config-volume
mountPath: /etc/prometheus/
- name: prometheus-storage-volume
mountPath: /prometheus/
volumes:
- name: prometheus-config-volume
configMap:
defaultMode: 420
name: prometheus-server-conf
- name: prometheus-storage-volume
emptyDir: {}

使用如下命令部署:

kubectl create -f prometheus-deployment.yaml --namespace=monitoring

部署完成后通过dashboard能够看到如下的界面:

5.连接Prometheus

这里有两种方式

1.通过kubectl命令进行端口代理

2.针对Prometheus的POD暴露一个服务,推荐此种方式
首先新建一个yaml文件命名为prometheus-service.yaml,写入如下内容:

apiVersion: v1
kind: Service
metadata:
name: prometheus-service
spec:
selector:
app: prometheus-server
type: NodePort
ports:
- port: 9090
targetPort: 9090
nodePort: 30909

执行如下命令创建服务:

kubectl create -f prometheus-service.yaml --namespace=monitoring

通过以下命令查看Service的状态,我们可以看到暴露的端口是30909:

kubectl get svc -n monitoring
NAME                 TYPE       CLUSTER-IP       EXTERNAL-IP   PORT(S)          AGE
prometheus-service   NodePort   10.101.186.82    <none>        9090:30909/TCP   100m

现在可以通过浏览器访问【http://虚拟机IP:30909】,看到如下界面,现在可以点击 status –> Targets,马上就可以看到所有Kubernetes集群上的Endpoint通过服务发现的方式自动连接到了Prometheus。:

我们还可以通过图形化界面查看内存:

OK,到这里Prometheus部署就算完成了,但是数据的统计明显不够直观,所以我们需要使用Grafana来构建更加友好的监控页面。

 

6.搭建Grafana

新建以下yaml文件:grafana-dashboard-provider.yaml

apiVersion: v1
kind: ConfigMap
metadata:
name: grafana-dashboard-provider
namespace: monitoring
data:
default-dashboard.yaml: |
- name: 'default'
org_id: 1
folder: ''
type: file
options:
folder: /var/lib/grafana/dashboards

grafana.yaml:

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: grafana
namespace: monitoring
labels:
app: grafana
component: core
spec:
replicas: 1
template:
metadata:
labels:
app: grafana
component: core
spec:
containers:
- image: grafana/grafana:5.0.0
name: grafana
ports:
- containerPort: 3000
resources:
limits:
cpu: 100m
memory: 100Mi
requests:
cpu: 100m
memory: 100Mi
volumeMounts:
- name: grafana-persistent-storage
mountPath: /var
- name: grafana-dashboard-provider
mountPath: /etc/grafana/provisioning/dashboards
volumes:
- name: grafana-dashboard-provider
configMap:
name: grafana-dashboard-provider
- name: grafana-persistent-storage
emptyDir: {}

grafana-service.yaml:

apiVersion: v1
kind: Service
metadata:
labels:
name: grafana
name: grafana
namespace: monitoring
spec:
type: NodePort
selector:
app: grafana
ports:
- protocol: TCP
port: 3000
targetPort: 3000
nodePort: 30300

执行如下命令进行创建:

kubectl apply -f grafana-dashboard-provider.yaml
kubectl apply -f grafana.yaml
kubectl apply -f grafana-service.yaml

部署完成后通过Kubernetes Dashboard可以看到:

 

 根据服务暴露出来的端口30300通过浏览器访问【http://虚拟机IP:30300】看到如下界面:

输入用户名和密码(admin/admin)即可登录。

接着我们配置数据源:

 

 然后导入Dashboards:

将JSON文件上传

grafana-dashboard.json (百度云链接 https://pan.baidu.com/s/1YtfD3s1U_d6Yon67qjihmw   密码:n25f)

然后点击导入:

然后就可以看到Kubernetes集群的监控数据了:

 

还有一个资源统计的Dashboards:

kubernetes-resources-usage-dashboard.json

 

OK,Prometheus的监控搭建到此结束。

 

参考资料:https://www.jianshu.com/p/c2e549480c50

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