前言
快速配置請直接跳轉(zhuǎn)至匯總配置
K8s + SpringBoot實(shí)現(xiàn)零宕機(jī)發(fā)布：健康檢查+滾動更新+優(yōu)雅停機(jī)+彈性伸縮+Prometheus監(jiān)控+配置分離（鏡像復(fù)用）
配置
健康檢查
健康檢查類型：就緒探針（readiness）+ 存活探針（liveness）
探針類型：exec（進(jìn)入容器執(zhí)行腳本）、tcpSocket（探測端口）、httpGet（調(diào)用接口）
業(yè)務(wù)層面
項目依賴 pom.xml
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
定義訪問端口、路徑及權(quán)限 application.yaml
management:
server:
port: 50000 # 啟用獨(dú)立運(yùn)維端口
endpoint: # 開啟health端點(diǎn)
health:
probes:
enabled: true
endpoints:
web:
exposure:
base-path: /actuator # 指定上下文路徑，啟用相應(yīng)端點(diǎn)
include: health
將暴露/actuator/health/readiness和/actuator/health/liveness兩個接口，訪問方式如下：
http://127.0.0.1:50000/actuator/health/readiness
http://127.0.0.1:50000/actuator/health/liveness
運(yùn)維層面
k8s部署模版deployment.yaml
apiVersion: apps/v1
kind: Deployment
spec:
template:
spec:
containers:
- name: {APP_NAME}
image: {IMAGE_URL}
imagePullPolicy: Always
ports:
- containerPort: {APP_PORT}
- name: management-port
containerPort: 50000 # 應(yīng)用管理端口
readinessProbe: # 就緒探針
httpGet:
path: /actuator/health/readiness
port: management-port
initialDelaySeconds: 30 # 延遲加載時間
periodSeconds: 10 # 重試時間間隔
timeoutSeconds: 1 # 超時時間設(shè)置
successThreshold: 1 # 健康閾值
failureThreshold: 6 # 不健康閾值
livenessProbe: # 存活探針
httpGet:
path: /actuator/health/liveness
port: management-port
initialDelaySeconds: 30 # 延遲加載時間
periodSeconds: 10 # 重試時間間隔
timeoutSeconds: 1 # 超時時間設(shè)置
successThreshold: 1 # 健康閾值
failureThreshold: 6 # 不健康閾值
滾動更新
k8s資源調(diào)度之滾動更新策略，若要實(shí)現(xiàn)零宕機(jī)發(fā)布，需支持健康檢查
apiVersion: apps/v1
kind: Deployment
metadata:
name: {APP_NAME}
labels:
app: {APP_NAME}
spec:
selector:
matchLabels:
app: {APP_NAME}
replicas: {REPLICAS} # Pod副本數(shù)
strategy:
type: RollingUpdate # 滾動更新策略
rollingUpdate:
maxSurge: 1 # 升級過程中最多可以比原先設(shè)置的副本數(shù)多出的數(shù)量
maxUnavailable: 1 # 升級過程中最多有多少個POD處于無法提供服務(wù)的狀態(tài)
優(yōu)雅停機(jī)
在K8s中，當(dāng)我們實(shí)現(xiàn)滾動升級之前，務(wù)必要實(shí)現(xiàn)應(yīng)用級別的優(yōu)雅停機(jī)。否則滾動升級時，還是會影響到業(yè)務(wù)。使應(yīng)用關(guān)閉線程、釋放連接資源后再停止服務(wù)
業(yè)務(wù)層面
項目依賴 pom.xml
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
定義訪問端口、路徑及權(quán)限 application.yaml
spring:
application:
name: <xxx>
profiles:
active: @profileActive@
lifecycle:
timeout-per-shutdown-phase: 30s # 停機(jī)過程超時時長設(shè)置30s，超過30s，直接停機(jī)
server:
port: 8080
shutdown: graceful # 默認(rèn)為IMMEDIATE，表示立即關(guān)機(jī)；GRACEFUL表示優(yōu)雅關(guān)機(jī)
management:
server:
port: 50000 # 啟用獨(dú)立運(yùn)維端口
endpoint: # 開啟shutdown和health端點(diǎn)
shutdown:
enabled: true
health:
probes:
enabled: true
endpoints:
web:
exposure:
base-path: /actuator # 指定上下文路徑，啟用相應(yīng)端點(diǎn)
include: health,shutdown
將暴露/actuator/shutdown接口，調(diào)用方式如下：
curl -X POST 127.0.0.1:50000/actuator/shutdown
運(yùn)維層面
確保dockerfile模版集成curl工具，否則無法使用curl命令
FROM openjdk:8-jdk-alpine
#構(gòu)建參數(shù)
ARG JAR_FILE
ARG WORK_PATH="/app"
ARG EXPOSE_PORT=8080
#環(huán)境變量
ENV JAVA_OPTS=""\
JAR_FILE=${JAR_FILE}
#設(shè)置時區(qū)
RUN ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
RUN sed -i 's/dl-cdn.alpinelinux.org/mirrors.ustc.edu.cn/g' /etc/apk/repositories \
&& apk add --no-cache curl
#將maven目錄的jar包拷貝到docker中，并命名為for_docker.jar
COPY target/$JAR_FILE $WORK_PATH/
#設(shè)置工作目錄
WORKDIR $WORK_PATH
指定于外界交互的端口
EXPOSE $EXPOSE_PORT
配置容器，使其可執(zhí)行化
ENTRYPOINT exec java $JAVA_OPTS -jar $JAR_FILE
k8s部署模版deployment.yaml
注：經(jīng)驗證，java項目可省略結(jié)束回調(diào)鉤子的配置
此外，若需使用回調(diào)鉤子，需保證鏡像中包含curl工具，且需注意應(yīng)用管理端口（50000）不能暴露到公網(wǎng)
apiVersion: apps/v1
kind: Deployment
spec:
template:
spec:
containers:
- name: {APP_NAME}
image: {IMAGE_URL}
imagePullPolicy: Always
ports:
- containerPort: {APP_PORT}
- containerPort: 50000
lifecycle:
preStop: # 結(jié)束回調(diào)鉤子
exec:
command: ["curl", "-XPOST", "127.0.0.1:50000/actuator/shutdown"]
彈性伸縮
為pod設(shè)置資源限制后，創(chuàng)建HPA
apiVersion: apps/v1
kind: Deployment
metadata:
name: {APP_NAME}
labels:
app: {APP_NAME}
spec:
template:
spec:
containers:
- name: {APP_NAME}
image: {IMAGE_URL}
imagePullPolicy: Always
resources: # 容器資源管理
limits: # 資源限制（監(jiān)控使用情況）
cpu: 0.5
memory: 1Gi
requests: # 最小可用資源（靈活調(diào)度）
cpu: 0.15
memory: 300Mi
kind: HorizontalPodAutoscaler # 彈性伸縮控制器
apiVersion: autoscaling/v2beta2
metadata:
name: {APP_NAME}
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: {APP_NAME}
minReplicas: {REPLICAS} # 縮放范圍
maxReplicas: 6
metrics:
- type: Resource
resource:
name: cpu # 指定資源指標(biāo)
target:
type: Utilization
averageUtilization: 50
Prometheus集成
業(yè)務(wù)層面
項目依賴 pom.xml
<!-- 引入Spring boot的監(jiān)控機(jī)制-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
<groupId>io.micrometer</groupId>
<artifactId>micrometer-registry-prometheus</artifactId>
</dependency>
定義訪問端口、路徑及權(quán)限 application.yaml
management:
server:
port: 50000 # 啟用獨(dú)立運(yùn)維端口
metrics:
tags:
application: ${spring.application.name}
endpoints:
web:
exposure:
base-path: /actuator # 指定上下文路徑，啟
用相應(yīng)端點(diǎn)
include: metrics,prometheus
將暴露/actuator/metric和/actuator/prometheus接口，訪問方式如下：
http://127.0.0.1:50000/actuator/metric
http://127.0.0.1:50000/actuator/prometheus
運(yùn)維層面 deployment.yaml
apiVersion: apps/v1
kind: Deployment
spec:
template:
metadata:
annotations:
prometheus:io/port: "50000"
prometheus.io/path: /actuator/prometheus # 在流水線中賦值
prometheus.io/scrape: "true" # 基于pod的服務(wù)發(fā)現(xiàn)
配置分離
方案：通過configmap掛載外部配置文件，并指定激活環(huán)境運(yùn)行
作用：配置分離，避免敏感信息泄露；鏡像復(fù)用，提高交付效率
通過文件生成configmap
通過dry-run的方式生成yaml文件
kubectl create cm -n <APP_NAME> --from-file=application-test.yaml --dry-run=1 -oyaml > configmap.yaml
更新
kubectl apply -f configmap.yaml
掛載configmap并指定激活環(huán)境
apiVersion: apps/v1
kind: Deployment
metadata:
name: {APP_NAME}
labels:
app: {APP_NAME}
spec:
template:
spec:
containers:
- name: {APP_NAME}
image: {IMAGE_URL}
imagePullPolicy: Always
env:
- name: SPRING_PROFILES_ACTIVE # 指定激活環(huán)境
value: test
volumeMounts: # 掛載configmap
- name: conf
mountPath: "/app/config" # 與Dockerfile中工作目錄一致
readOnly: true
volumes:
- name: conf
configMap:
name: {APP_NAME}
匯總配置
業(yè)務(wù)層面文章來源：http://www.zghlxwxcb.cn/news/detail-626034.html
項目依賴 pom.xml
<!-- 引入Spring boot的監(jiān)控機(jī)制-->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
<groupId>io.micrometer</groupId>
<artifactId>micrometer-registry-prometheus</artifactId>
</dependency>
定義訪問端口、路徑及權(quán)限 application.yaml
spring:
application:
name: project-sample
profiles:
active: @profileActive@
lifecycle:
timeout-per-shutdown-phase: 30s # 停機(jī)過程超時時長設(shè)置30s，超過30s，直接停機(jī)
server:
port: 8080
shutdown: graceful # 默認(rèn)為IMMEDIATE，表示立即關(guān)機(jī)；GRACEFUL表示優(yōu)雅關(guān)機(jī)
management:
server:
port: 50000 # 啟用獨(dú)立運(yùn)維端口
metrics:
tags:
application: ${spring.application.name}
endpoint: # 開啟shutdown和health端點(diǎn)
shutdown:
enabled: true
health:
probes:
enabled: true
endpoints:
web:
exposure:
base-path: /actuator # 指定上下文路徑，啟用相應(yīng)端點(diǎn)
include: health,shutdown,metrics,prometheus
運(yùn)維層面
確保dockerfile模版集成curl工具，否則無法使用curl命令文章來源地址http://www.zghlxwxcb.cn/news/detail-626034.html
FROM openjdk:8-jdk-alpine
#構(gòu)建參數(shù)
ARG JAR_FILE
ARG WORK_PATH="/app"
ARG EXPOSE_PORT=8080
#環(huán)境變量
ENV JAVA_OPTS=""\
JAR_FILE=${JAR_FILE}
#設(shè)置時區(qū)
RUN ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && echo 'Asia/Shanghai' >/etc/timezone
RUN sed -i 's/dl-cdn.alpinelinux.org/mirrors.ustc.edu.cn/g' /etc/apk/repositories \
&& apk add --no-cache curl
#將maven目錄的jar包拷貝到docker中，并命名為for_docker.jar
COPY target/$JAR_FILE $WORK_PATH/
#設(shè)置工作目錄
WORKDIR $WORK_PATH
# 指定于外界交互的端口
EXPOSE $EXPOSE_PORT
# 配置容器，使其可執(zhí)行化
ENTRYPOINT exec java $JAVA_OPTS -jar $JAR_FILE
k8s部署模版deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: {APP_NAME}
labels:
app: {APP_NAME}
spec:
selector:
matchLabels:
app: {APP_NAME}
replicas: {REPLICAS} # Pod副本數(shù)
strategy:
type: RollingUpdate # 滾動更新策略
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
template:
metadata:
name: {APP_NAME}
labels:
app: {APP_NAME}
annotations:
timestamp: {TIMESTAMP}
prometheus.io/port: "50000" # 不能動態(tài)賦值
prometheus.io/path: /actuator/prometheus
prometheus.io/scrape: "true" # 基于pod的服務(wù)發(fā)現(xiàn)
spec:
affinity: # 設(shè)置調(diào)度策略，采取多主機(jī)/多可用區(qū)部署
podAntiAffinity:
preferredDuringSchedulingIgnoredDuringExecution:
- weight: 100
podAffinityTerm:
labelSelector:
matchExpressions:
- key: app
operator: In
values:
- {APP_NAME}
topologyKey: "kubernetes.io/hostname" # 多可用區(qū)為"topology.kubernetes.io/zone"
terminationGracePeriodSeconds: 30 # 優(yōu)雅終止寬限期
containers:
- name: {APP_NAME}
image: {IMAGE_URL}
imagePullPolicy: Always
ports:
- containerPort: {APP_PORT}
- name: management-port
containerPort: 50000 # 應(yīng)用管理端口
readinessProbe: # 就緒探針
httpGet:
path: /actuator/health/readiness
port: management-port
initialDelaySeconds: 30 # 延遲加載時間
periodSeconds: 10 # 重試時間間隔
timeoutSeconds: 1 # 超時時間設(shè)置
successThreshold: 1 # 健康閾值
failureThreshold: 9 # 不健康閾值
livenessProbe: # 存活探針
httpGet:
path: /actuator/health/liveness
port: management-port
initialDelaySeconds: 30 # 延遲加載時間
periodSeconds: 10 # 重試時間間隔
timeoutSeconds: 1 # 超時時間設(shè)置
successThreshold: 1 # 健康閾值
failureThreshold: 6 # 不健康閾值
resources: # 容器資源管理
limits: # 資源限制（監(jiān)控使用情況）
cpu: 0.5
memory: 1Gi
requests: # 最小可用資源（靈活調(diào)度）
cpu: 0.1
memory: 200Mi
env:
- name: TZ
value: Asia/Shanghai
---
kind: HorizontalPodAutoscaler # 彈性伸縮控制器
apiVersion: autoscaling/v2beta2
metadata:
name: {APP_NAME}
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: {APP_NAME}
minReplicas: {REPLICAS} # 縮放范圍
maxReplicas: 6
metrics:
- type: Resource
resource:
name: cpu # 指定資源指標(biāo)
target:
type: Utilization
averageUtilization: 50
到了這里，關(guān)于K8s(健康檢查+滾動更新+優(yōu)雅停機(jī)+彈性伸縮+Prometheus監(jiān)控+配置分離)的文章就介紹完了。如果您還想了解更多內(nèi)容，請在右上角搜索TOY模板網(wǎng)以前的文章或繼續(xù)瀏覽下面的相關(guān)文章，希望大家以后多多支持TOY模板網(wǎng)！
