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本文转自 Rancher Labs
介 绍
Prometheus 高可用的必要性
在过来的几年里，Kubernetes 的采纳量增长了数倍。很显著，Kubernetes 是容器编排的不二抉择。与此同时，Prometheus 也被认为是监控容器化和非容器化工作负载的绝佳抉择。监控是任何基础设施的一个重要关注点，咱们应该确保咱们的监控设置具备高可用性和高可扩展性，以满足一直增长的基础设施的需要，特地是在采纳 Kubernetes 的状况下。
因而，明天咱们将部署一个集群化的 Prometheus 设置，它不仅可能弹性应答节点故障，还能保障适合的数据存档，供当前参考。咱们的设置还具备很强的可扩展性，以至于咱们能够在同一个监控保护伞下逾越多个 Kubernetes 集群。
以后计划
大部分的 Prometheus 部署都是应用长久卷的 pod，而 Prometheus 则是应用联邦机制进行扩大。然而并不是所有的数据都能够应用联邦机制进行聚合，在这里，当你减少额定的服务器时，你往往须要一个机制来治理 Prometheus 配置。
解决办法
Thanos 旨在解决上述问题。在 Thanos 的帮忙下，咱们不仅能够对 Prometheus 的实例进行多重复制，并在它们之间进行数据去重，还能够将数据归档到 GCS 或 S3 等长期存储中。
施行过程
Thanos 架构
图片起源: https://thanos.io/quick-tutor…
Thanos 由以下组件形成：
- Thanos sidecar：这是运行在 Prometheus 上的次要组件。它读取和归档对象存储上的数据。此外，它还治理着 Prometheus 的配置和生命周期。为了辨别每个 Prometheus 实例，sidecar 组件将内部标签注入到 Prometheus 配置中。该组件可能在 Prometheus 服务器的 PromQL 接口上运行查问。Sidecar 组件还能监听 Thanos gRPC 协定，并在 gRPC 和 REST 之间翻译查问。
- Thanos 存储：该组件在对象 storage bucket 中的历史数据之上实现了 Store API，它次要作为 API 网关，因而不须要大量的本地磁盘空间。它在启动时退出一个 Thanos 集群，并颁布它能够拜访的数据。它在本地磁盘上保留了大量对于所有近程区块的信息，并使其与 bucket 放弃同步。通常状况下，在重新启动时能够平安地删除此数据，但会减少启动工夫。
- Thanos 查问：查问组件在 HTTP 上监听并将查问翻译成 Thanos gRPC 格局。它从不同的源头汇总查问后果，并能从 Sidecar 和 Store 读取数据。在 HA 设置中，它甚至会对查问后果进行反复数据删除。
HA 组的运行时反复数据删除
Prometheus 是有状态的，不容许复制其数据库。这意味着通过运行多个 Prometheus 副原本进步高可用性并不易于应用。简略的负载平衡是行不通的，比方在产生某些解体之后，一个正本可能会启动，然而查问这样的正本会导致它在敞开期间呈现一个小的缺口（gap）。你有第二个正本可能正在启动，但它可能在另一个时刻（如滚动重启）敞开，因而在这些正本下面的负载平衡将无奈失常工作。
- Thanos Querier 则从两个正本中提取数据，并对这些信号进行反复数据删除，从而为 Querier 使用者填补了缺口（gap）。
- Thanos Compact 组件将 Prometheus 2.0 存储引擎的压实程序利用于对象存储中的块数据存储。它通常不是语义上的并发平安，必须针对 bucket 进行单例部署。它还负责数据的下采样——40 小时后执行 5m 下采样，10 天后执行 1h 下采样。
- Thanos Ruler 基本上和 Prometheus 的规定具备雷同作用，惟一区别是它能够与 Thanos 组件进行通信。
配 置
后期筹备
要齐全了解这个教程，须要筹备以下货色：
- 对 Kubernetes 和应用 kubectl 有肯定的理解。
- 运行中的 Kubernetes 集群至多有 3 个节点（在本 demo 中，应用 GKE 集群）
- 实现 Ingress Controller 和 Ingress 对象（在本 demo 中应用 Nginx Ingress Controller）。尽管这不是强制性的，但为了缩小创立内部端点的数量，强烈建议应用。
- 创立用于 Thanos 组件拜访对象存储的凭证（在本例中为 GCS bucket）。
- 创立 2 个 GCS bucket，并将其命名为 Prometheus-long-term 和 thanos-ruler。
- 创立一个服务账户，角色为 Storage Object Admin。
- 下载密钥文件作为 json 证书，并命名为 thanos-gcs-credentials.json。
- 应用凭证创立 Kubernetes sercret
kubectl create secret generic thanos-gcs-credentials --from-file=thanos-gcs-credentials.json
部署各类组件
部署 Prometheus 服务账户、Clusterroler和Clusterrolebinding
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
---以上 manifest 创立了 Prometheus 所需的监控命名空间以及服务账户、clusterrole以及clusterrolebinding。
部署 Prometheues 配置 configmap
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:$2上述 Configmap 创立了 Prometheus 配置文件模板。这个配置文件模板将被 Thanos sidecar 组件读取，它将生成理论的配置文件，而这个配置文件又将被运行在同一个 pod 中的 Prometheus 容器所耗费。在配置文件中增加 external_labels 局部是极其重要的，这样 Querier 就能够依据这个来反复删除数据。
部署 Prometheus Rules configmap
这将创立咱们的告警规定，这些规定将被转发到 alertmanager，以便发送。
apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus-rules
labels:
name: prometheus-rules
namespace: monitoring
data:
alert-rules.yaml: |-
groups:
- name: Deployment
rules:
- alert: Deployment at 0 Replicas
annotations:
summary: Deployment {{$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部署 Prometheus Stateful Set
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对于下面提供的 manifest，了解以下内容很重要：
- Prometheus 是作为一个有状态集部署的，有 3 个正本，每个正本动静地提供本人的长久化卷。
- Prometheus 配置是由 Thanos sidecar 容器应用咱们下面创立的模板文件生成的。
- Thanos 解决数据压缩，因而咱们须要设置 –storage.tsdb.min-block-duration=2h 和 –storage.tsdb.max-block-duration=2h。
- Prometheus 有状态集被标记为 thanos-store-api: true，这样每个 pod 就会被咱们接下来创立的 headless service 发现。正是这个 headless service 将被 Thanos Querier 用来查问所有 Prometheus 实例的数据。咱们还将雷同的标签利用于 Thanos Store 和 Thanos Ruler 组件，这样它们也会被 Querier 发现，并可用于查问指标。
- GCS bucket credentials 门路是应用 GOOGLE_APPLICATION_CREDENTIALS 环境变量提供的，配置文件是由咱们作为后期筹备中创立的 secret 挂载到它下面的。
部署 Prometheus 服务
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"除了上述办法外，你还能够点击这篇文章理解如何在 Rancher 上疾速部署和配置 Prometheus 服务。
咱们为 stateful set 中的每个 Prometheus pod 创立了不同的服务，只管这并不是必要的。这些服务的创立只是为了调试。上文曾经解释了 thanos-store-gateway headless service 的目标。咱们稍后将应用一个 ingress 对象来裸露 Prometheus 服务。
部署 Prometheus Querier
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这是 Thanos 部署的次要内容之一。请留神以下几点：
- 容器参数
-store=dnssrv+thanos-store-gateway:10901有助于发现所有应查问的指标数据的组件。 - thanos-querier 服务提供了一个 Web 接口来运行 PromQL 查问。它还能够抉择在不同的 Prometheus 集群中去反复删除数据。
- 这是咱们提供 Grafana 作为所有 dashboard 的数据源的起点（end point）。
部署 Thanos 存储网关
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
---这将创立存储组件，它将从对象存储中向 Querier 提供指标。
部署 Thanos Ruler
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当初，如果你在与咱们的工作负载雷同的命名空间中启动交互式 shell，并尝试查看咱们的 thanos-store-gateway 解析到哪些 pods，你会看到以下内容：
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下面返回的 IP 对应的是咱们的 Prometheus Pod、thanos-store和thanos-ruler。这能够被验证为：
$ 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>部署 Alertmanager
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这将创立咱们的 Alertmanager 部署，它将依据 Prometheus 规定生成所有告警。
部署 Kubestate 指标
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-metricsKubestate 指标部署须要转发一些重要的容器指标，这些指标不是 kubelet 原生裸露的，因而不能间接提供给 Prometheus。
部署 Node-Exporter Daemonset
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: /Node-Exporter daemonset 在每个节点上运行一个 node-exporter 的 pod，并暴露出十分重要的节点相干指标，这些指标能够被 Prometheus 实例拉取。
部署 Grafana
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这将创立咱们的 Grafana 部署和服务，它将应用咱们的 Ingress 对象裸露。为了做到这一点，咱们应该增加 Thanos-Querier 作为咱们 Grafana 部署的数据源：
- 点击增加数据源
- 设置 Name: DS_PROMETHEUS
- 设置 Type: Prometheus
- 设置 URL: http://thanos-querier:9090
- 保留并测试。当初你能够构建你的自定义 dashboard 或从 grafana.net 简略导入 dashboard。Dashboard #315 和 #1471 都非常适合入门。
部署 Ingress 对象
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这是拼图的最初一块。有助于将咱们的所有服务裸露在 Kubernetes 集群之外，并帮忙咱们拜访它们。确保将 <yourdomain> 替换为一个你能够拜访的域名，并且你能够将 Ingress-Controller 的服务指向这个域名。
当初你应该能够拜访 Thanos Querier，网址是：http://thanos-querier.<yourdomain>.com。它如下所示：
确保选中反复数据删除（deduplication）。
如果你点击 Store，能够看到所有由 thanos-store-gateway 服务发现的流动端点。
当初你能够在 Grafana 中增加 Thanos Querier 作为数据源，并开始创立 dashboard。
Kubernetes 集群监控 dashboard
Kubernetes 节点监控 dashboard
总 结
将 Thanos 与 Prometheus 集成在一起，无疑提供了横向扩大 Prometheus 的能力，而且因为 Thanos-Querier 可能从其余 querier 实例中提取指标数据，因而实际上你能够跨集群提取指标数据，并在一个繁多的仪表板中可视化。
咱们还可能将指标数据归档在对象存储中，为咱们的监控零碎提供有限的存储空间，同时从对象存储自身提供指标数据。这种设置的次要老本局部能够归结为对象存储（S3 或 GCS）。如果咱们对它们利用适当的保留策略，能够进一步降低成本。
然而，实现这所有须要你进行大量的配置。下面提供的 manifest 曾经在生产环境中进行了测试，你能够大胆进行尝试。
正文完