转载来自51cto:https://blog.51cto.com/wutengfei/2667106

kubernetes-s3

k8s后端使用 AWS S3 作为持久性存储,本文详细介绍使用方法和步骤。

源码获取

tengfeiwu / kubernetes-s3

Kubernetes pod 中使用S3FS架构图

64FMEq.png

创建 AWS IAM账号与权限

登陆AWS控制台进入IAM,新创建个IAM账号给予S3读写权限,记下改账号的访问密钥ID和私有访问密钥。后面configmap文件中要使用~

创建命名空间

这里创建个open-falcon-monitoring命名空间用于后面的监控,内容如下:

# cat ns-open-falcon.yaml
apiVersion: v1
kind: Namespace
metadata:
  name: open-falcon-monitoring
# 创建namespace
kubectl apply -f ns-open-falcon.yaml

创建镜像仓库

这里你可以使用 AWS ECR 也可以其他公有云或自己私有仓库,我这里使用的阿里云镜像服务,如有需要自己可免费注册一个。

阿里云镜像仓库信息

# 阿里云Docker Registry
registry.cn-shanghai.aliyuncs.com
# 镜像仓库
open-falcon-s3

创建pull/push镜像secret

这里在open-falcon-monitoring命名空间下,创建名称是open-falcon-registry-secret的secret,内容如下:

kubectl create secret docker-registry open-falcon-registry-secret -n open-falcon-monitoring \
  --docker-server=registry.cn-shanghai.aliyuncs.com \
  --docker-username=<阿里云控制台账号> \
  --docker-password=<阿里云控制台密码> \
  --docker-email=2422123451@qq.com

创建 S3 持久性存储流程

创建存储桶

登陆 AWS 控制台,进入S3,创建bucket(存储桶)open-falcon-monitoring

配置configmap

cd yaml/ && cp configmap_secrets_template.yaml configmap_secrets.yaml
# cat configmap_secrets.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: s3-config
  namespace: open-falcon-monitoring
data:
  S3_BUCKET: open-falcon-monitoring
  AWS_KEY: <AWS IAM 访问密钥ID>
  AWS_SECRET_KEY: <AWS IAM 私有访问密钥>

构建和部署

修改build.sh文件

下面是完整文件,内容如下:

#!/usr/bin/env bash

########################################################################################################################
# PREREQUISTITS
########################################################################################################################
#
# - ensure that you have a valid Artifactory or other Docker registry account
# - Create your image pull secret in your namespace
#   kubectl create secret docker-registry artifactory --docker-server=<YOUR-REGISTRY>.docker.repositories.sap.ondemand.com --docker-username=<USERNAME> --docker-password=<PASSWORD> --docker-email=<EMAIL> -n <NAMESPACE>
# - change the settings below arcording your settings
#
# usage:
# Call this script with the version to build and push to the registry. After build/push the
# yaml/* files are deployed into your cluster
#
#  ./build.sh 1.0
#
VERSION=$1
PROJECT=open-falcon-s3 # 修改成自己的仓库名
REPOSITORY=registry.cn-shanghai.aliyuncs.com/ai-voice-test # 仓库地址,这里使用的是阿里云

# causes the shell to exit if any subcommand or pipeline returns a non-zero status.
set -e
# set debug mode
#set -x

########################################################################################################################
# build the new docker image
########################################################################################################################
#
echo '>>> Building new image'
# Due to a bug in Docker we need to analyse the log to find out if build passed (see https://github.com/dotcloud/docker/issues/1875)
docker build --no-cache=true -t $REPOSITORY/$PROJECT:$VERSION . | tee /tmp/docker_build_result.log
RESULT=$(cat /tmp/docker_build_result.log | tail -n 1)
if [[ "$RESULT" != *Successfully* ]];
then
  exit -1
fi

########################################################################################################################
# push the docker image to your registry
########################################################################################################################
#
echo '>>> Push new image'
docker push $REPOSITORY/$PROJECT:$VERSION

########################################################################################################################
# deploy your YAML files into your kubernetes cluster
########################################################################################################################
#
# (and replace some placeholder in the yaml files...
# It is recommended to use HELM for bigger projects and more dynamic deployments
#
kubectl apply -f ./yaml/configmap_secrets.yaml
# Apply the YAML passed into stdin and replace the version string first
#cat ./yaml/daemonset.yaml | sed "s/$REPOSITORY\/$PROJECT/$REPOSITORY\/$PROJECT:$VERSION/g" | kubectl apply -f -

修改Dockerfile

添加国内源,否则你会哭的,完整内容如下:

###############################################################################
# The FUSE driver needs elevated privileges, run Docker with --privileged=true
###############################################################################

FROM alpine:latest

ENV MNT_POINT /var/s3
ENV IAM_ROLE=none  # 我这里并没创建 IAM 角色,所以写none
ENV S3_REGION 'ap-southeast-1'

VOLUME /var/s3

ARG S3FS_VERSION=v1.89

RUN sed -i 's/dl-cdn.alpinelinux.org/mirrors.aliyun.com/g' /etc/apk/repositories

RUN apk --update add bash fuse libcurl libxml2 libstdc++ libgcc alpine-sdk automake autoconf libxml2-dev fuse-dev curl-dev git; \
    git clone https://github.com/s3fs-fuse/s3fs-fuse.git; \
    cd s3fs-fuse; \
    git checkout tags/${S3FS_VERSION}; \
    ./autogen.sh; \
    ./configure --prefix=/usr ; \
    make; \
    make install; \
    make clean; \
    rm -rf /var/cache/apk/*; \
    apk del git automake autoconf;

RUN sed -i s/"#user_allow_other"/"user_allow_other"/g /etc/fuse.conf

COPY docker-entrypoint.sh /
RUN chmod 777 /docker-entrypoint.sh
CMD /docker-entrypoint.sh

构建镜像

# 运行如下命令
./build.sh 2.0

发布daemon

cat yaml/daemonset.yaml
apiVersion: apps/v1
kind: DaemonSet
metadata:
  labels:
    app: s3-provider
  name: s3-provider
  namespace: open-falcon-monitoring
spec:
  selector:
    matchLabels:
      app: s3-provider
  template:
    metadata:
      labels:
        app: s3-provider
    spec:
      containers:
      - name: s3fuse
        # 修改成自己镜像名称
        image: registry.cn-shanghai.aliyuncs.com/ai-voice-test/open-falcon-s3:2.0 
        lifecycle:
          preStop:
            exec:
              command: ["/bin/sh","-c","umount -f /var/s3"]
        securityContext:
          privileged: true
          capabilities:
            add:
            - SYS_ADMIN
        # use ALL  entries in the config map as environment variables
        envFrom:
        - configMapRef:
            name: s3-config
        volumeMounts:
        - name: devfuse
          mountPath: /dev/fuse
        - name: mntdatas3fs
          mountPath: /var/s3:shared
      volumes:
      - name: devfuse
        hostPath:
          path: /dev/fuse
      - name: mntdatas3fs
        hostPath:
          path: /mnt/data-s3-fs
# 部署
kubectl apply -f yaml/daemonset.yaml
# 查看
kubectl get pod -n open-falcon-monitoring
NAME                READY   STATUS    RESTARTS   AGE
s3-provider-2j6pw   1/1     Running   2          18s

测试

cd yaml && cat example_pod.yaml 
apiVersion: v1
kind: Pod
metadata:
  name: test-pd
  namespace: open-falcon-monitoring
spec:
  containers:
  - image: nginx
    name: s3-test-container
    securityContext:
      privileged: true
    volumeMounts:
    - name: mntdatas3fs
      mountPath: /var/s3:shared
    livenessProbe:
      exec:
        command: ["ls", "/var/s3"]
      failureThreshold: 3
      initialDelaySeconds: 10
      periodSeconds: 5
      successThreshold: 1
      timeoutSeconds: 1
  volumes:
  - name: mntdatas3fs
    hostPath:
      path: /mnt/data-s3-fs
# 查看
# kubectl get pod -n open-falcon-monitoring
NAME                READY   STATUS    RESTARTS   AGE
s3-provider-2j6pw   1/1     Running   2          3m44s
test-pd             1/1     Running   0          73s
# 查看系统
df -h 
s3fs                     256T     0  256T    0% /mnt/data-s3-fs
# 创建文件
kubectl exec -ti test-pd -n open-falcon-monitoring sh
echo "this is a ok!" > /var/s3/ceshi.txt
# 在/mnt/data-s3-fs上
cd /mnt/data-s3-fs/ && cat ceshi.txt
this is a ok!
# 在 AWS S3 上,如下图:

64mrTJ.png

参考文档