使用 Prometheus 和 Thanos 进行高可用性的 Kubernetes 监控
Table of Contents
1.首先
2.将Prometheus和Thanos集成的原因
3.Thanos概述
3.1 Thanos架构
3.2 Thanos Sidecar
3.3 Thanos存储
3.4 Thanos查询
3.5 Thanos Compact
3.6 Thanos Ruler
4. Thanos的实现
5.部署
6. Grafana仪表盘
7.总结
首先
在这篇文章中，我们将解释如何部署一个集群化的Prometheus设置来整合Thanos。这个设置具备对节点故障具有恢复能力，同时也保证了适当的数据存档，而且设置还是可伸缩的。您可以在同一个监控下跨越多个Kubernetes集群。最后，我们还将解释如何通过一个可视化并且易于访问的美观Grafana仪表盘来监控所有数据。
2. 将Prometheus和Thanos进行整合的原因
Prometheus可以使用联邦设置进行扩展，并且其部署使用持久性卷。不过，并非所有数据都可以通过联合机制进行集合。通常情况下，需要使用其他工具来管理Prometheus的配置。为了解决这些问题，可以使用Thanos。通过使用Thanos，可以创建多个Prometheus实例，消除数据重复，并将数据归档到长期存储介质如GCS或S3中。
3. 塔诺斯的简介 (Tǎ nuò sī de jiè)
3.1 塔诺斯架构
让我们来看一下，Thanos由侧车、存储器、查询器、压缩器和统治者这几个组件构成。每个组件都有各自的功能。
3.2 塔诺斯的侧边车
-
- Prometheusに従って機能するメインのコンポーネント
-
- オブジェクトストアのデータを読み込み、アーカイブ
-
- Prometheusの設定とライフサイクルの管理
-
- Prometheus の設定に外部ラベルを注入して、各Prometheusインスタンスを区別
-
- Prometheus サーバーのPromQLインターフェイス上でクエリを実行
- ThanosのgRPCプロトコルから、gRPCとREST間のクエリを変換
3.3 塔诺斯商店
-
- オブジェクトストレージバケット内の履歴データの上にStore APIをインプリメント
-
- 主にAPIゲートウェイとして動作するため、ローカルディスク容量を大幅に必要としない
-
- 起動時にThanosクラスタに参加し、アクセス可能なデータを宣伝
-
- ローカルディスク上のすべてのリモートブロックの情報をバケットと同期させ保持
- このデータは一般的に再起動時に削除しても安全ですが、起動時間が長くなる
3.4 塔诺斯查询
-
- HTTPをリッスンし、クエリをThanosのgRPC形式に変換
-
- 異なるソースからのクエリ結果を集約し、サイドカーとストアからデータを読み取る
- HA の設定では、Thanos Query は結果を重複排除
关于HA集团运行时的副本事项注意事项
Prometheus是一种面向状态的系统，不允许数据库复制。因此，运行多个Prometheus副本以提高可用性并不容易。
简单的负载均衡也无法正常工作。虽然复制品可能已经上线了，但是在执行查询时，仍然会出现小的时间差，这是在它们离线期间发生的。即使有第二个复制品，这个问题也无法修复。这是因为第二个复制品随时都有可能处于离线状态，例如在滚动重启时会离线。这些例子说明了负载均衡会如何失败。
Thanos Query 会从两个副本中提取数据，并消除它们的重复信号，如果有间隙就会填充并发送给 Querier 消费者。
3.5 塔诺斯紧凑型
普罗米修斯2.0将压缩步骤应用于对象存储的块数据。
通常与安全语义并行的，必须作为单例部署到存储桶上。
负责对数据进行下采样，40小时后进行5分钟下采样，10天后进行1小时下采样。
3.6 塔诺斯统治者
Thanos Ruler的基本功能与查询相同，但专为Prometheus规则而设计。唯一的区别是它可以与Thanos组件进行通信。
4. 灭霸的实施
前提条件：要完全理解本教程，需要具备以下要素。
-
- Kubernetes和kubectl的实际知识
在运行中的Kubernetes集群（使用GKE）中，需要了解以下内容：
1. 实施Ingress Controller和Ingress对象（使用Nginx Ingress Controller）。尽管不是必需的，但强烈推荐，以减少外部终端点的数量。
2. 创建用于Thanos组件访问对象存储（这里使用GCS存储桶）的凭据：
a. 创建两个GCS存储桶，并将其命名为prometheus-long-term和thanos-ruler。
b. 创建一个具有存储对象管理员角色的服务帐号。
c. 以json凭据的形式下载密钥文件，并将其命名为thanos-gcs-credentials.json。
d. 使用下面的代码片段，使用凭据创建Kubernetes的Secret。
kubectl create secret generic thanos-gcs-credentials --from-file=thanos-gcs-credentials.json -n monitoring
5部署
以下的清单将部署Prometheus所需的监控命名空间、服务账户、集群角色和集群角色绑定。
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: monitoring
namespace: monitoring
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRole
metadata:
name: monitoring
namespace: monitoring
rules:
- apiGroups: [""]
resources:
- nodes
- nodes/proxy
- services
- endpoints
- pods
verbs: ["get", "list", "watch"]
- apiGroups: [""]
resources:
- configmaps
verbs: ["get"]
- nonResourceURLs: ["/metrics"]
verbs: ["get"]
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRoleBinding
metadata:
name: monitoring
subjects:
- kind: ServiceAccount
name: monitoring
namespace: monitoring
roleRef:
kind: ClusterRole
name: monitoring
apiGroup: rbac.authorization.k8s.io
---
部署 Prometheus 配置文件的 configmap。
以下的配置映射是Thanos侧边车组件加载的Prometheus配置文件模板。该文件由运行在同一Pod中的Prometheus容器消费，非常重要的是将external_labels部分添加到配置文件中，以便查询可以基于此去除重复数据。
apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus-server-conf
labels:
name: prometheus-server-conf
namespace: monitoring
data:
prometheus.yaml.tmpl: |-
global:
scrape_interval: 5s
evaluation_interval: 5s
external_labels:
cluster: prometheus-ha
# Each Prometheus has to have unique labels.
replica: $(POD_NAME)
rule_files:
- /etc/prometheus/rules/*rules.yaml
alerting:
# We want our alerts to be deduplicated
# from different replicas.
alert_relabel_configs:
- regex: replica
action: labeldrop
alertmanagers:
- scheme: http
path_prefix: /
static_configs:
- targets: ['alertmanager:9093']
scrape_configs:
- job_name: kubernetes-nodes-cadvisor
scrape_interval: 10s
scrape_timeout: 10s
scheme: https
tls_config:
ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
kubernetes_sd_configs:
- role: node
relabel_configs:
- action: labelmap
regex: __meta_kubernetes_node_label_(.+)
# Only for Kubernetes ^1.7.3.
# See: https://github.com/prometheus/prometheus/issues/2916
- target_label: __address__
replacement: kubernetes.default.svc:443
- source_labels: [__meta_kubernetes_node_name]
regex: (.+)
target_label: __metrics_path__
replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor
metric_relabel_configs:
- action: replace
source_labels: [id]
regex: '^/machine\.slice/machine-rkt\\x2d([^\\]+)\\.+/([^/]+)\.service$'
target_label: rkt_container_name
replacement: '${2}-${1}'
- action: replace
source_labels: [id]
regex: '^/system\.slice/(.+)\.service$'
target_label: systemd_service_name
replacement: '${1}'
- job_name: 'kubernetes-pods'
kubernetes_sd_configs:
- role: pod
relabel_configs:
- 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
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
action: keep
regex: true
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scheme]
action: replace
target_label: __scheme__
regex: (https?)
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
action: replace
target_label: __metrics_path__
regex: (.+)
- source_labels: [__address__, __meta_kubernetes_pod_prometheus_io_port]
action: replace
target_label: __address__
regex: ([^:]+)(?::\d+)?;(\d+)
replacement: $1:$2
- 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-service-endpoints'
kubernetes_sd_configs:
- role: endpoints
relabel_configs:
- 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
- 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:$2
Prometheus规则的展开配置映射：
请创建用于中继到Alertmanager的警报规则，以用于传输。
apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus-rules
labels:
name: prometheus-rules
namespace: monitoring
data:
alert-rules.yaml: |-
groups:
- name: Deployment
rules:
- alert: Deployment at 0 Replicas
annotations:
summary: Deployment {{$labels.deployment}} in {{$labels.namespace}} is currently having no pods running
expr: |
sum(kube_deployment_status_replicas{pod_template_hash=""}) by (deployment,namespace) < 1
for: 1m
labels:
team: devops
- alert: HPA Scaling Limited
annotations:
summary: HPA named {{$labels.hpa}} in {{$labels.namespace}} namespace has reached scaling limited state
expr: |
(sum(kube_hpa_status_condition{condition="ScalingLimited",status="true"}) by (hpa,namespace)) == 1
for: 1m
labels:
team: devops
- alert: HPA at MaxCapacity
annotations:
summary: HPA named {{$labels.hpa}} in {{$labels.namespace}} namespace is running at Max Capacity
expr: |
((sum(kube_hpa_spec_max_replicas) by (hpa,namespace)) - (sum(kube_hpa_status_current_replicas) by (hpa,namespace))) == 0
for: 1m
labels:
team: devops
- name: Pods
rules:
- alert: Container restarted
annotations:
summary: Container named {{$labels.container}} in {{$labels.pod}} in {{$labels.namespace}} was restarted
expr: |
sum(increase(kube_pod_container_status_restarts_total{namespace!="kube-system",pod_template_hash=""}[1m])) by (pod,namespace,container) > 0
for: 0m
labels:
team: dev
- alert: High Memory Usage of Container
annotations:
summary: Container named {{$labels.container}} in {{$labels.pod}} in {{$labels.namespace}} is using more than 75% of Memory Limit
expr: |
((( sum(container_memory_usage_bytes{image!="",container_name!="POD", namespace!="kube-system"}) by (namespace,container_name,pod_name) / sum(container_spec_memory_limit_bytes{image!="",container_name!="POD",namespace!="kube-system"}) by (namespace,container_name,pod_name) ) * 100 ) < +Inf ) > 75
for: 5m
labels:
team: dev
- alert: High CPU Usage of Container
annotations:
summary: Container named {{$labels.container}} in {{$labels.pod}} in {{$labels.namespace}} is using more than 75% of CPU Limit
expr: |
((sum(irate(container_cpu_usage_seconds_total{image!="",container_name!="POD", namespace!="kube-system"}[30s])) by (namespace,container_name,pod_name) / sum(container_spec_cpu_quota{image!="",container_name!="POD", namespace!="kube-system"} / container_spec_cpu_period{image!="",container_name!="POD", namespace!="kube-system"}) by (namespace,container_name,pod_name) ) * 100) > 75
for: 5m
labels:
team: dev
- name: Nodes
rules:
- alert: High Node Memory Usage
annotations:
summary: Node {{$labels.kubernetes_io_hostname}} has more than 80% memory used. Plan Capcity
expr: |
(sum (container_memory_working_set_bytes{id="/",container_name!="POD"}) by (kubernetes_io_hostname) / sum (machine_memory_bytes{}) by (kubernetes_io_hostname) * 100) > 80
for: 5m
labels:
team: devops
- alert: High Node CPU Usage
annotations:
summary: Node {{$labels.kubernetes_io_hostname}} has more than 80% allocatable cpu used. Plan Capacity.
expr: |
(sum(rate(container_cpu_usage_seconds_total{id="/", container_name!="POD"}[1m])) by (kubernetes_io_hostname) / sum(machine_cpu_cores) by (kubernetes_io_hostname) * 100) > 80
for: 5m
labels:
team: devops
- alert: High Node Disk Usage
annotations:
summary: Node {{$labels.kubernetes_io_hostname}} has more than 85% disk used. Plan Capacity.
expr: |
(sum(container_fs_usage_bytes{device=~"^/dev/[sv]d[a-z][1-9]$",id="/",container_name!="POD"}) by (kubernetes_io_hostname) / sum(container_fs_limit_bytes{container_name!="POD",device=~"^/dev/[sv]d[a-z][1-9]$",id="/"}) by (kubernetes_io_hostname)) * 100 > 85
for: 5m
labels:
team: devops
Prometheus的有状态设置的部署
apiVersion: storage.k8s.io/v1beta1
kind: StorageClass
metadata:
name: fast
namespace: monitoring
provisioner: kubernetes.io/gce-pd
allowVolumeExpansion: true
---
apiVersion: apps/v1beta1
kind: StatefulSet
metadata:
name: prometheus
namespace: monitoring
spec:
replicas: 3
serviceName: prometheus-service
template:
metadata:
labels:
app: prometheus
thanos-store-api: "true"
spec:
serviceAccountName: monitoring
containers:
- name: prometheus
image: prom/prometheus:v2.4.3
args:
- "--config.file=/etc/prometheus-shared/prometheus.yaml"
- "--storage.tsdb.path=/prometheus/"
- "--web.enable-lifecycle"
- "--storage.tsdb.no-lockfile"
- "--storage.tsdb.min-block-duration=2h"
- "--storage.tsdb.max-block-duration=2h"
ports:
- name: prometheus
containerPort: 9090
volumeMounts:
- name: prometheus-storage
mountPath: /prometheus/
- name: prometheus-config-shared
mountPath: /etc/prometheus-shared/
- name: prometheus-rules
mountPath: /etc/prometheus/rules
- name: thanos
image: quay.io/thanos/thanos:v0.8.0
args:
- "sidecar"
- "--log.level=debug"
- "--tsdb.path=/prometheus"
- "--prometheus.url=http://127.0.0.1:9090"
- "--objstore.config={type: GCS, config: {bucket: prometheus-long-term}}"
- "--reloader.config-file=/etc/prometheus/prometheus.yaml.tmpl"
- "--reloader.config-envsubst-file=/etc/prometheus-shared/prometheus.yaml"
- "--reloader.rule-dir=/etc/prometheus/rules/"
env:
- name: POD_NAME
valueFrom:
fieldRef:
fieldPath: metadata.name
- name : GOOGLE_APPLICATION_CREDENTIALS
value: /etc/secret/thanos-gcs-credentials.json
ports:
- name: http-sidecar
containerPort: 10902
- name: grpc
containerPort: 10901
livenessProbe:
httpGet:
port: 10902
path: /-/healthy
readinessProbe:
httpGet:
port: 10902
path: /-/ready
volumeMounts:
- name: prometheus-storage
mountPath: /prometheus
- name: prometheus-config-shared
mountPath: /etc/prometheus-shared/
- name: prometheus-config
mountPath: /etc/prometheus
- name: prometheus-rules
mountPath: /etc/prometheus/rules
- name: thanos-gcs-credentials
mountPath: /etc/secret
readOnly: false
securityContext:
fsGroup: 2000
runAsNonRoot: true
runAsUser: 1000
volumes:
- name: prometheus-config
configMap:
defaultMode: 420
name: prometheus-server-conf
- name: prometheus-config-shared
emptyDir: {}
- name: prometheus-rules
configMap:
name: prometheus-rules
- name: thanos-gcs-credentials
secret:
secretName: thanos-gcs-credentials
volumeClaimTemplates:
- metadata:
name: prometheus-storage
namespace: monitoring
spec:
accessModes: [ "ReadWriteOnce" ]
storageClassName: fast
resources:
requests:
storage: 20Gi
重要的是要理解上述宣言中的以下内容。
Prometheus会以三个具有状态的副本集的形式部署，并动态地为每个副本集分配独立的持久化卷。
通过Thanos Sidecar容器使用上述创建的模板文件生成Prometheus的配置。
由于Thanos负责处理数据压缩，所以需要设置–storage.tsdb.min-block-duration=2h和–storage.tsdb.max-block-duration=2h。
Prometheus的有状态副本集带有一个名为thanos-store-api的标签，被标记为“true”，因此每个Pod将通过无头服务进行发现（稍后将介绍如何发现）。这个无头服务用于Thanos Query查询跨所有Prometheus实例的数据。
同样，将相同的标签应用于Thanos Store和Thanos Ruler组件，以便它们能够被查询发现，并可用于指标查询。
GCS存储桶的凭据路径通过使用GOOGLE_APPLICATION_CREDENTIALS环境变量提供。设置文件从作为前提条件创建的秘钥中挂载。
Prometheus服务的部署
apiVersion: v1
kind: Service
metadata:
name: prometheus-0-service
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "9090"
namespace: monitoring
labels:
name: prometheus
spec:
selector:
statefulset.kubernetes.io/pod-name: prometheus-0
ports:
- name: prometheus
port: 8080
targetPort: prometheus
---
apiVersion: v1
kind: Service
metadata:
name: prometheus-1-service
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "9090"
namespace: monitoring
labels:
name: prometheus
spec:
selector:
statefulset.kubernetes.io/pod-name: prometheus-1
ports:
- name: prometheus
port: 8080
targetPort: prometheus
---
apiVersion: v1
kind: Service
metadata:
name: prometheus-2-service
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "9090"
namespace: monitoring
labels:
name: prometheus
spec:
selector:
statefulset.kubernetes.io/pod-name: prometheus-2
ports:
- name: prometheus
port: 8080
targetPort: prometheus
---
#This service creates a srv record for querier to find about store-api's
apiVersion: v1
kind: Service
metadata:
name: thanos-store-gateway
namespace: monitoring
spec:
type: ClusterIP
clusterIP: None
ports:
- name: grpc
port: 10901
targetPort: grpc
selector:
thanos-store-api: "true"
在StatefulSet中，为每个Prometheus pod创建不同的服务。这些服务不是必需的，只是为了调试目的而创建的。thanos-store-gateway无头服务的目的已在上述说明中解释过。接下来，使用ingress对象公开Prometheus服务。
Thanos Query的部署：这是Thanos部署的主要组件之一，请注意以下几点。
容器参数–store=dnssrv+thanos-store-gateway:10901有助于发现应查询所有组件的指标数据。
thanos-querier服务提供了用于执行PromQL查询的Web接口，并且还提供了在不同的Prometheus集群之间去除重复数据的选项。
从这里，将Grafana作为所有仪表板的数据源提供。
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: thanos-querier
namespace: monitoring
labels:
app: thanos-querier
spec:
replicas: 1
selector:
matchLabels:
app: thanos-querier
template:
metadata:
labels:
app: thanos-querier
spec:
containers:
- name: thanos
image: quay.io/thanos/thanos:v0.8.0
args:
- query
- --log.level=debug
- --query.replica-label=replica
- --store=dnssrv+thanos-store-gateway:10901
ports:
- name: http
containerPort: 10902
- name: grpc
containerPort: 10901
livenessProbe:
httpGet:
port: http
path: /-/healthy
readinessProbe:
httpGet:
port: http
path: /-/ready
---
apiVersion: v1
kind: Service
metadata:
labels:
app: thanos-querier
name: thanos-querier
namespace: monitoring
spec:
ports:
- port: 9090
protocol: TCP
targetPort: http
name: http
selector:
app: thanos-querier
灭霸引入了“Thanos Store Gateway”。
将会创建一个存储组件，该组件可以从对象存储中提供查询的指标。
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
---
apiVersion: apps/v1beta1
kind: StatefulSet
metadata:
name: thanos-store-gateway
namespace: monitoring
labels:
app: thanos-store-gateway
spec:
replicas: 1
selector:
matchLabels:
app: thanos-store-gateway
serviceName: thanos-store-gateway
template:
metadata:
labels:
app: thanos-store-gateway
thanos-store-api: "true"
spec:
containers:
- name: thanos
image: quay.io/thanos/thanos:v0.8.0
args:
- "store"
- "--log.level=debug"
- "--data-dir=/data"
- "--objstore.config={type: GCS, config: {bucket: prometheus-long-term}}"
- "--index-cache-size=500MB"
- "--chunk-pool-size=500MB"
env:
- name : GOOGLE_APPLICATION_CREDENTIALS
value: /etc/secret/thanos-gcs-credentials.json
ports:
- name: http
containerPort: 10902
- name: grpc
containerPort: 10901
livenessProbe:
httpGet:
port: 10902
path: /-/healthy
readinessProbe:
httpGet:
port: 10902
path: /-/ready
volumeMounts:
- name: thanos-gcs-credentials
mountPath: /etc/secret
readOnly: false
volumes:
- name: thanos-gcs-credentials
secret:
secretName: thanos-gcs-credentials
---
灭霸压缩部署
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
---
apiVersion: apps/v1beta1
kind: StatefulSet
metadata:
name: thanos-compactor
namespace: monitoring
labels:
app: thanos-compactor
spec:
replicas: 1
selector:
matchLabels:
app: thanos-compactor
serviceName: thanos-compactor
template:
metadata:
labels:
app: thanos-compactor
spec:
containers:
- name: thanos
image: quay.io/thanos/thanos:v0.8.0
args:
- "compact"
- "--log.level=debug"
- "--data-dir=/data"
- "--objstore.config={type: GCS, config: {bucket: prometheus-long-term}}"
- "--wait"
env:
- name : GOOGLE_APPLICATION_CREDENTIALS
value: /etc/secret/thanos-gcs-credentials.json
ports:
- name: http
containerPort: 10902
livenessProbe:
httpGet:
port: 10902
path: /-/healthy
readinessProbe:
httpGet:
port: 10902
path: /-/ready
volumeMounts:
- name: thanos-gcs-credentials
mountPath: /etc/secret
readOnly: false
volumes:
- name: thanos-gcs-credentials
secret:
secretName: thanos-gcs-credentials
灭霸统治者的部署
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
---
apiVersion: v1
kind: ConfigMap
metadata:
name: thanos-ruler-rules
namespace: monitoring
data:
alert_down_services.rules.yaml: |
groups:
- name: metamonitoring
rules:
- alert: PrometheusReplicaDown
annotations:
message: Prometheus replica in cluster {{$labels.cluster}} has disappeared from Prometheus target discovery.
expr: |
sum(up{cluster="prometheus-ha", instance=~".*:9090", job="kubernetes-service-endpoints"}) by (job,cluster) < 3
for: 15s
labels:
severity: critical
---
apiVersion: apps/v1beta1
kind: StatefulSet
metadata:
labels:
app: thanos-ruler
name: thanos-ruler
namespace: monitoring
spec:
replicas: 1
selector:
matchLabels:
app: thanos-ruler
serviceName: thanos-ruler
template:
metadata:
labels:
app: thanos-ruler
thanos-store-api: "true"
spec:
containers:
- name: thanos
image: quay.io/thanos/thanos:v0.8.0
args:
- rule
- --log.level=debug
- --data-dir=/data
- --eval-interval=15s
- --rule-file=/etc/thanos-ruler/*.rules.yaml
- --alertmanagers.url=http://alertmanager:9093
- --query=thanos-querier:9090
- "--objstore.config={type: GCS, config: {bucket: thanos-ruler}}"
- --label=ruler_cluster="prometheus-ha"
- --label=replica="$(POD_NAME)"
env:
- name : GOOGLE_APPLICATION_CREDENTIALS
value: /etc/secret/thanos-gcs-credentials.json
- name: POD_NAME
valueFrom:
fieldRef:
fieldPath: metadata.name
ports:
- name: http
containerPort: 10902
- name: grpc
containerPort: 10901
livenessProbe:
httpGet:
port: http
path: /-/healthy
readinessProbe:
httpGet:
port: http
path: /-/ready
volumeMounts:
- mountPath: /etc/thanos-ruler
name: config
- name: thanos-gcs-credentials
mountPath: /etc/secret
readOnly: false
volumes:
- configMap:
name: thanos-ruler-rules
name: config
- name: thanos-gcs-credentials
secret:
secretName: thanos-gcs-credentials
---
apiVersion: v1
kind: Service
metadata:
labels:
app: thanos-ruler
name: thanos-ruler
namespace: monitoring
spec:
ports:
- port: 9090
protocol: TCP
targetPort: http
name: http
selector:
app: thanos-ruler
访问与工作负载同一命名空间的交互式 shell，然后检查哪些 pods 被 thanos-store-gateway 解析。结果如下所示。
root@my-shell-95cb5df57-4q6w8:/# nslookup thanos-store-gateway
Server: 10.63.240.10
Address: 10.63.240.10#53
Name: thanos-store-gateway.monitoring.svc.cluster.local
Address: 10.60.25.2
Name: thanos-store-gateway.monitoring.svc.cluster.local
Address: 10.60.25.4
Name: thanos-store-gateway.monitoring.svc.cluster.local
Address: 10.60.30.2
Name: thanos-store-gateway.monitoring.svc.cluster.local
Address: 10.60.30.8
Name: thanos-store-gateway.monitoring.svc.cluster.local
Address: 10.60.31.2
root@my-shell-95cb5df57-4q6w8:/# exit
被返回的IP对应于Prometheus的Pod，即thatos-store和thatos-ruler。可以通过以下方式进行验证。
$ kubectl get pods -o wide -l thanos-store-api="true"
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
prometheus-0 2/2 Running 0 100m 10.60.31.2 gke-demo-1-pool-1-649cbe02-jdnv <none> <none>
prometheus-1 2/2 Running 0 14h 10.60.30.2 gke-demo-1-pool-1-7533d618-kxkd <none> <none>
prometheus-2 2/2 Running 0 31h 10.60.25.2 gke-demo-1-pool-1-4e9889dd-27gc <none> <none>
thanos-ruler-0 1/1 Running 0 100m 10.60.30.8 gke-demo-1-pool-1-7533d618-kxkd <none> <none>
thanos-store-gateway-0 1/1 Running 0 14h 10.60.25.4 gke-demo-1-pool-1-4e9889dd-27gc <none> <none>
Alert Manager 的部署
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
---
kind: ConfigMap
apiVersion: v1
metadata:
name: alertmanager
namespace: monitoring
data:
config.yml: |-
global:
resolve_timeout: 5m
slack_api_url: "<your_slack_hook>"
victorops_api_url: "<your_victorops_hook>"
templates:
- '/etc/alertmanager-templates/*.tmpl'
route:
group_by: ['alertname', 'cluster', 'service']
group_wait: 10s
group_interval: 1m
repeat_interval: 5m
receiver: default
routes:
- match:
team: devops
receiver: devops
continue: true
- match:
team: dev
receiver: dev
continue: true
receivers:
- name: 'default'
- name: 'devops'
victorops_configs:
- api_key: '<YOUR_API_KEY>'
routing_key: 'devops'
message_type: 'CRITICAL'
entity_display_name: '{{ .CommonLabels.alertname }}'
state_message: 'Alert: {{ .CommonLabels.alertname }}. Summary:{{ .CommonAnnotations.summary }}. RawData: {{ .CommonLabels }}'
slack_configs:
- channel: '#k8-alerts'
send_resolved: true
- name: 'dev'
victorops_configs:
- api_key: '<YOUR_API_KEY>'
routing_key: 'dev'
message_type: 'CRITICAL'
entity_display_name: '{{ .CommonLabels.alertname }}'
state_message: 'Alert: {{ .CommonLabels.alertname }}. Summary:{{ .CommonAnnotations.summary }}. RawData: {{ .CommonLabels }}'
slack_configs:
- channel: '#k8-alerts'
send_resolved: true
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: alertmanager
namespace: monitoring
spec:
replicas: 1
selector:
matchLabels:
app: alertmanager
template:
metadata:
name: alertmanager
labels:
app: alertmanager
spec:
containers:
- name: alertmanager
image: prom/alertmanager:v0.15.3
args:
- '--config.file=/etc/alertmanager/config.yml'
- '--storage.path=/alertmanager'
ports:
- name: alertmanager
containerPort: 9093
volumeMounts:
- name: config-volume
mountPath: /etc/alertmanager
- name: alertmanager
mountPath: /alertmanager
volumes:
- name: config-volume
configMap:
name: alertmanager
- name: alertmanager
emptyDir: {}
---
apiVersion: v1
kind: Service
metadata:
annotations:
prometheus.io/scrape: 'true'
prometheus.io/path: '/metrics'
labels:
name: alertmanager
name: alertmanager
namespace: monitoring
spec:
selector:
app: alertmanager
ports:
- name: alertmanager
protocol: TCP
port: 9093
targetPort: 9093
Kubestate指标的部署
需要部署 Kubestate 指标以传递一些重要的容器指标。这些指标由 kubelet 原生不公开，无法直接在 Prometheus 中使用。
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
---
apiVersion: rbac.authorization.k8s.io/v1
# kubernetes versions before 1.8.0 should use rbac.authorization.k8s.io/v1beta1
kind: ClusterRoleBinding
metadata:
name: kube-state-metrics
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: kube-state-metrics
subjects:
- kind: ServiceAccount
name: kube-state-metrics
namespace: monitoring
---
apiVersion: rbac.authorization.k8s.io/v1
# kubernetes versions before 1.8.0 should use rbac.authorization.k8s.io/v1beta1
kind: ClusterRole
metadata:
name: kube-state-metrics
rules:
- apiGroups: [""]
resources:
- configmaps
- secrets
- nodes
- pods
- services
- resourcequotas
- replicationcontrollers
- limitranges
- persistentvolumeclaims
- persistentvolumes
- namespaces
- endpoints
verbs: ["list", "watch"]
- apiGroups: ["extensions"]
resources:
- daemonsets
- deployments
- replicasets
verbs: ["list", "watch"]
- apiGroups: ["apps"]
resources:
- statefulsets
verbs: ["list", "watch"]
- apiGroups: ["batch"]
resources:
- cronjobs
- jobs
verbs: ["list", "watch"]
- apiGroups: ["autoscaling"]
resources:
- horizontalpodautoscalers
verbs: ["list", "watch"]
---
apiVersion: rbac.authorization.k8s.io/v1
# kubernetes versions before 1.8.0 should use rbac.authorization.k8s.io/v1beta1
kind: RoleBinding
metadata:
name: kube-state-metrics
namespace: monitoring
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: kube-state-metrics-resizer
subjects:
- kind: ServiceAccount
name: kube-state-metrics
namespace: monitoring
---
apiVersion: rbac.authorization.k8s.io/v1
# kubernetes versions before 1.8.0 should use rbac.authorization.k8s.io/v1beta1
kind: Role
metadata:
namespace: monitoring
name: kube-state-metrics-resizer
rules:
- apiGroups: [""]
resources:
- pods
verbs: ["get"]
- apiGroups: ["extensions"]
resources:
- deployments
resourceNames: ["kube-state-metrics"]
verbs: ["get", "update"]
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: kube-state-metrics
namespace: monitoring
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: kube-state-metrics
namespace: monitoring
spec:
selector:
matchLabels:
k8s-app: kube-state-metrics
replicas: 1
template:
metadata:
labels:
k8s-app: kube-state-metrics
spec:
serviceAccountName: kube-state-metrics
containers:
- name: kube-state-metrics
image: quay.io/mxinden/kube-state-metrics:v1.4.0-gzip.3
ports:
- name: http-metrics
containerPort: 8080
- name: telemetry
containerPort: 8081
readinessProbe:
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 5
timeoutSeconds: 5
- name: addon-resizer
image: k8s.gcr.io/addon-resizer:1.8.3
resources:
limits:
cpu: 150m
memory: 50Mi
requests:
cpu: 150m
memory: 50Mi
env:
- name: MY_POD_NAME
valueFrom:
fieldRef:
fieldPath: metadata.name
- name: MY_POD_NAMESPACE
valueFrom:
fieldRef:
fieldPath: metadata.namespace
command:
- /pod_nanny
- --container=kube-state-metrics
- --cpu=100m
- --extra-cpu=1m
- --memory=100Mi
- --extra-memory=2Mi
- --threshold=5
- --deployment=kube-state-metrics
---
apiVersion: v1
kind: Service
metadata:
name: kube-state-metrics
namespace: monitoring
labels:
k8s-app: kube-state-metrics
annotations:
prometheus.io/scrape: 'true'
spec:
ports:
- name: http-metrics
port: 8080
targetPort: http-metrics
protocol: TCP
- name: telemetry
port: 8081
targetPort: telemetry
protocol: TCP
selector:
k8s-app: kube-state-metrics
部署 Node-exporter Daemonset。
Node-exporter Daemonset在每个节点上运行Node-exporter pod。它公开了Prometheus实例可以提取的非常重要的节点指标。
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
---
apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
name: node-exporter
namespace: monitoring
labels:
name: node-exporter
spec:
template:
metadata:
labels:
name: node-exporter
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "9100"
spec:
hostPID: true
hostIPC: true
hostNetwork: true
containers:
- name: node-exporter
image: prom/node-exporter:v0.16.0
securityContext:
privileged: true
args:
- --path.procfs=/host/proc
- --path.sysfs=/host/sys
ports:
- containerPort: 9100
protocol: TCP
resources:
limits:
cpu: 100m
memory: 100Mi
requests:
cpu: 10m
memory: 100Mi
volumeMounts:
- name: dev
mountPath: /host/dev
- name: proc
mountPath: /host/proc
- name: sys
mountPath: /host/sys
- name: rootfs
mountPath: /rootfs
volumes:
- name: proc
hostPath:
path: /proc
- name: dev
hostPath:
path: /dev
- name: sys
hostPath:
path: /sys
- name: rootfs
hostPath:
path: /
Grafana的设置
在这里，我们将创建Grafana的配置和服务，并使用ingress对象进行公开。我们将添加thanos-querier作为Grafana部署的数据源。要实现这一点，请按照以下步骤进行。
-
- 点击“添加数据源”
-
- 名称：DS_PROMETHEUS
-
- 设置类型：Prometheus
-
- 设置URL：http://thanos-querier:9090
保存并测试。通过这样做，您可以构建自定义仪表板，或者从grafana.net导入仪表板。仪表板＃315和＃1471是开始的好地方。
apiVersion: v1
kind: Namespace
metadata:
name: monitoring
---
apiVersion: storage.k8s.io/v1beta1
kind: StorageClass
metadata:
name: fast
namespace: monitoring
provisioner: kubernetes.io/gce-pd
allowVolumeExpansion: true
---
apiVersion: apps/v1beta1
kind: StatefulSet
metadata:
name: grafana
namespace: monitoring
spec:
replicas: 1
serviceName: grafana
template:
metadata:
labels:
task: monitoring
k8s-app: grafana
spec:
containers:
- name: grafana
image: k8s.gcr.io/heapster-grafana-amd64:v5.0.4
ports:
- containerPort: 3000
protocol: TCP
volumeMounts:
- mountPath: /etc/ssl/certs
name: ca-certificates
readOnly: true
- mountPath: /var
name: grafana-storage
env:
- name: GF_SERVER_HTTP_PORT
value: "3000"
# The following env variables are required to make Grafana accessible via
# the kubernetes api-server proxy. On production clusters, we recommend
# removing these env variables, setup auth for grafana, and expose the grafana
# service using a LoadBalancer or a public IP.
- name: GF_AUTH_BASIC_ENABLED
value: "false"
- name: GF_AUTH_ANONYMOUS_ENABLED
value: "true"
- name: GF_AUTH_ANONYMOUS_ORG_ROLE
value: Admin
- name: GF_SERVER_ROOT_URL
# If you're only using the API Server proxy, set this value instead:
# value: /api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
value: /
volumes:
- name: ca-certificates
hostPath:
path: /etc/ssl/certs
volumeClaimTemplates:
- metadata:
name: grafana-storage
namespace: monitoring
spec:
accessModes: [ "ReadWriteOnce" ]
storageClassName: fast
resources:
requests:
storage: 5Gi
---
apiVersion: v1
kind: Service
metadata:
labels:
kubernetes.io/cluster-service: 'true'
kubernetes.io/name: grafana
name: grafana
namespace: monitoring
spec:
ports:
- port: 3000
targetPort: 3000
selector:
k8s-app: grafana
Ingress对象的布置
这是拼图的最后一块。它帮助将所有服务公开在Kubernetes集群外部，并且便于访问它们。
请将其替换为您自己的域名。它可以指向ingress-controller的服务。
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: monitoring-ingress
namespace: monitoring
annotations:
kubernetes.io/ingress.class: "nginx"
spec:
rules:
- host: grafana.<yourdomain>.com
http:
paths:
- path: /
backend:
serviceName: grafana
servicePort: 3000
- host: prometheus-0.<yourdomain>.com
http:
paths:
- path: /
backend:
serviceName: prometheus-0-service
servicePort: 8080
- host: prometheus-1.<yourdomain>.com
http:
paths:
- path: /
backend:
serviceName: prometheus-1-service
servicePort: 8080
- host: prometheus-2.<yourdomain>.com
http:
paths:
- path: /
backend:
serviceName: prometheus-2-service
servicePort: 8080
- host: alertmanager.<yourdomain>.com
http:
paths:
- path: /
backend:
serviceName: alertmanager
servicePort: 9093
- host: thanos-querier.<yourdomain>.com
http:
paths:
- path: /
backend:
serviceName: thanos-querier
servicePort: 9090
- host: thanos-ruler.<yourdomain>.com
http:
paths:
- path: /
backend:
serviceName: thanos-ruler
servicePort: 9090
现在，您可以从 http://thanos-querier..com 访问Thanos Querier，并且结果如下所示。
确认已选择排除重复选项。
点击“Stores”按钮，会显示在thatos-store-gateway中找到的所有活动的端点。
Grafana 的仪表盘
最后，我们将Thanos调用器作为Grafana的数据源添加进去，开始创建仪表盘。
Kubenetes集群监控仪表板
Kubernetes节点监控仪表盘
总结
通过合并Thanos和Prometheus，可以横向扩展Prometheus。Thanos Querier能够从其他Querier实例中提取指标，因此可以在集群间提取指标，并在Grafana仪表板上进行可视化。此外，Thanos还可以将指标数据存档到对象存储中，为监控系统提供无限的存储，并从对象存储本身提供指标。这个设置的主要运营成本是由于对象存储(S3或GCS)，通过应用适当的保留策略可以减少成本。
今天的安装将需要相当数量的设置。以上的清单已经在生产环境中进行了测试，应该能够简化流程。如果对此有任何疑问，请随时与我们联系。如果您不想自己进行设置，可以使用MetricFire提供的托管Prometheus服务。您可以尝试免费试用或预订演示，也可以直接联系我们。
下次再见。
