本文轉自Rancher Labs
介 紹
Prometheus高可用的必要性
在過去的幾年裡，Kubernetes的採用量增長了數倍。很明顯，Kubernetes是容器編排的不二選擇。與此同時，Prometheus也被認為是監控容器化和非容器化工作負載的絕佳選擇。監控是任何基礎設施的一個重要關注點，我們應該確保我們的監控設定具有高可用性和高可擴充套件性，以滿足不斷增長的基礎設施的需求，特別是在採用Kubernetes的情況下。
因此，今天我們將部署一個叢集化的Prometheus設定，它不僅能夠彈性應對節點故障，還能保證合適的資料存檔，供以後參考。我們的設定還具有很強的可擴充套件性，以至於我們可以在同一個監控保護傘下跨越多個Kubernetes叢集。
當前方案
大部分的Prometheus部署都是使用持久卷的pod，而Prometheus則是使用聯邦機制進行擴充套件。但是並不是所有的資料都可以使用聯邦機制進行聚合，在這裡，當你增加額外的伺服器時，你往往需要一個機制來管理Prometheus配置。
解決方法
Thanos旨在解決上述問題。在Thanos的幫助下，我們不僅可以對Prometheus的例項進行多重複制，並在它們之間進行資料去重，還可以將資料歸檔到GCS或S3等長期儲存中。
實施過程
Thanos 架構
圖片來源: https://thanos.io/quick-tutorial.md/
Thanos由以下元件構成：
-
Thanos sidecar：這是執行在Prometheus上的主要元件。它讀取和歸檔物件儲存上的資料。此外，它還管理著Prometheus的配置和生命週期。為了區分每個Prometheus例項，sidecar元件將外部標籤注入到Prometheus配置中。該元件能夠在 Prometheus 伺服器的 PromQL 介面上執行查詢。Sidecar元件還能監聽Thanos gRPC協議，並在gRPC和REST之間翻譯查詢。
-
Thanos 儲存：該元件在物件storage bucket中的歷史資料之上實現了Store API，它主要作為API閘道器，因此不需要大量的本地磁碟空間。它在啟動時加入一個Thanos叢集，並公佈它可以訪問的資料。它在本地磁碟上儲存了少量關於所有遠端區塊的資訊，並使其與 bucket 保持同步。通常情況下，在重新啟動時可以安全地刪除此資料，但會增加啟動時間。
-
Thanos查詢：查詢元件在HTTP上監聽並將查詢翻譯成Thanos gRPC格式。它從不同的源頭彙總查詢結果，並能從Sidecar和Store讀取資料。在HA設定中，它甚至會對查詢結果進行重複資料刪除。
HA組的執行時重複資料刪除
Prometheus是有狀態的，不允許複製其資料庫。這意味著通過執行多個Prometheus副本來提高高可用性並不易於使用。簡單的負載均衡是行不通的，比如在發生某些崩潰之後，一個副本可能會啟動，但是查詢這樣的副本會導致它在關閉期間出現一個小的缺口（gap）。你有第二個副本可能正在啟動，但它可能在另一個時刻（如滾動重啟）關閉，因此在這些副本上面的負載均衡將無法正常工作。
-
Thanos Querier則從兩個副本中提取資料，並對這些訊號進行重複資料刪除，從而為Querier使用者填補了缺口（gap）。
-
Thanos Compact元件將Prometheus 2.0儲存引擎的壓實程式應用於物件儲存中的塊資料儲存。它通常不是語義上的併發安全，必須針對bucket 進行單例部署。它還負責資料的下采樣——40小時後執行5m下采樣，10天后執行1h下采樣。
-
Thanos Ruler基本上和Prometheus的規則具有相同作用，唯一區別是它可以與Thanos元件進行通訊。
配 置
前期準備
要完全理解這個教程，需要準備以下東西：
-
對Kubernetes和使用kubectl有一定的瞭解。
-
執行中的Kubernetes叢集至少有3個節點（在本demo中，使用GKE叢集）
-
實現Ingress Controller和Ingress物件（在本demo中使用Nginx Ingress Controller）。雖然這不是強制性的，但為了減少建立外部端點的數量，強烈建議使用。
-
建立用於Thanos元件訪問物件儲存的憑證（在本例中為GCS bucket）。
-
建立2個GCS bucket，並將其命名為Prometheus-long-term和thanos-ruler。
-
建立一個服務賬戶，角色為Storage Object Admin。
-
下載金鑰檔案作為json證書，並命名為thanos-gcs-credentials.json。
-
使用憑證建立Kubernetes sercret
kubectl create secret generic thanos-gcs-credentials --from-file=thanos-gcs-credentials.json
部署各類元件
部署Prometheus服務賬戶、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建立了Prometheus所需的監控名稱空間以及服務賬戶、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:$2
上述Configmap建立了Prometheus配置檔案模板。這個配置檔案模板將被Thanos sidecar元件讀取，它將生成實際的配置檔案，而這個配置檔案又將被執行在同一個pod中的Prometheus容器所消耗。在配置檔案中新增external_labels部分是極其重要的，這樣Querier就可以根據這個來重複刪除資料。
部署Prometheus Rules configmap
這將建立我們的告警規則，這些規則將被轉發到alertmanager，以便傳送。
apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus-rules
labels:
name: prometheus-rules
namespace: monitoring
data:
alert-rules.yaml: |-
groups:
- name: Deployment
rules:
- alert: Deployment at 0 Replicas
annotations:
summary: Deployment {{$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
關於上面提供的manifest，理解以下內容很重要：
-
Prometheus是作為一個有狀態集部署的，有3個副本，每個副本動態地提供自己的持久化卷。
-
Prometheus配置是由Thanos sidecar容器使用我們上面建立的模板檔案生成的。
-
Thanos處理資料壓縮，因此我們需要設定--storage.tsdb.min-block-duration=2h和--storage.tsdb.max-block-duration=2h。
-
Prometheus有狀態集被標記為thanos-store-api: true，這樣每個pod就會被我們接下來建立的headless service發現。正是這個headless service將被Thanos Querier用來查詢所有Prometheus例項的資料。我們還將相同的標籤應用於Thanos Store和Thanos Ruler元件，這樣它們也會被Querier發現，並可用於查詢指標。
-
GCS bucket credentials路徑是使用GOOGLE_APPLICATION_CREDENTIALS環境變數提供的，配置檔案是由我們作為前期準備中建立的secret掛載到它上面的。
部署Prometheus服務
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"
除了上述方法外，你還可以點選這篇文章瞭解如何在Rancher上快速部署和配置Prometheus服務。
我們為stateful set中的每個Prometheus pod建立了不同的服務，儘管這並不是必要的。這些服務的建立只是為了除錯。上文已經解釋了 thanos-store-gateway headless service的目的。我們稍後將使用一個 ingress 物件來暴露 Prometheus 服務。
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
這是Thanos部署的主要內容之一。請注意以下幾點：
-
容器引數
-store=dnssrv+thanos-store-gateway:10901有助於發現所有應查詢的指標資料的元件。 -
thanos-querier服務提供了一個Web介面來執行PromQL查詢。它還可以選擇在不同的Prometheus叢集中去重複刪除資料。
-
這是我們提供Grafana作為所有dashboard的資料來源的終點（end point）。
部署Thanos儲存閘道器
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
---
這將建立儲存元件，它將從物件儲存中向Querier提供指標。
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
現在，如果你在與我們的工作負載相同的名稱空間中啟動互動式shell，並嘗試檢視我們的thanos-store-gateway解析到哪些pods，你會看到以下內容：
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
上面返回的IP對應的是我們的Prometheus Pod、thanos-store和thanos-ruler。這可以被驗證為：
$ 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
這將建立我們的Alertmanager部署，它將根據Prometheus規則生成所有告警。
部署Kubestate指標
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
Kubestate指標部署需要轉發一些重要的容器指標，這些指標不是kubelet原生暴露的，因此不能直接提供給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在每個節點上執行一個node-exporter的pod，並暴露出非常重要的節點相關指標，這些指標可以被Prometheus例項拉取。
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
這將建立我們的Grafana部署和服務，它將使用我們的Ingress物件暴露。為了做到這一點，我們應該新增Thanos-Querier作為我們Grafana部署的資料來源：
-
點選新增資料來源
-
設定Name: DS_PROMETHEUS
-
設定Type: Prometheus
-
設定URL: http://thanos-querier:9090
-
儲存並測試。現在你可以構建你的自定義dashboard或從grafana.net簡單匯入dashboard。Dashboard #315和#1471都非常適合入門。
部署Ingress物件
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
這是拼圖的最後一塊。有助於將我們的所有服務暴露在Kubernetes叢集之外，並幫助我們訪問它們。確保將
現在你應該可以訪問Thanos Querier，網址是：http://thanos-querier.
確保選中重複資料刪除（deduplication）。
如果你點選Store，可以看到所有由thanos-store-gateway服務發現的活動端點。
現在你可以在Grafana中新增Thanos Querier作為資料來源，並開始建立dashboard。
Kubernetes叢集監控dashboard
Kubernetes節點監控dashboard
總 結
將Thanos與Prometheus整合在一起，無疑提供了橫向擴充套件Prometheus的能力，而且由於Thanos-Querier能夠從其他querier例項中提取指標資料，因此實際上你可以跨叢集提取指標資料，並在一個單一的儀表板中視覺化。
我們還能夠將指標資料歸檔在物件儲存中，為我們的監控系統提供無限的儲存空間，同時從物件儲存本身提供指標資料。這種設定的主要成本部分可以歸結為物件儲存（S3或GCS）。如果我們對它們應用適當的保留策略，可以進一步降低成本。
然而，實現這一切需要你進行大量的配置。上面提供的manifest已經在生產環境中進行了測試，你可以大膽進行嘗試。