在Kubernetes上搭建EFK（Fluentd＋Elasticsearch＋Kibana）

2021-10-23 22:11:22

1. 前言

kubernetes 默认会将容器的stdout和stderr录入node(minion)的/var/log/containers目录下,而kubernetes 组件的日志默认放置在/var/log目录下。

如果你是用kube-up启动的kubernetes集群，那么恭喜你,你可 以方便的启动k8s的日志功能。参考:http://kubernetes.io/docs/getting-started-guides/logging-elasticsearch/ 或者在k8s安装包的解压目录kubernetes/cluster/addons/fluentd-elasticsearch中找到安装文件。

如果你是通过命令或者脚本启动的k8s集群,那么也恭喜你,折腾等着你。

2. 实现需求

将各个pod中容器的stdout和stderr中的日志集中展示。

3. 部署结构

待传。

4. Elasticsearch & Kibana

这两个使用官网的镜像。Elasticsearch如果需要集群化,参考:

https://hub.docker.com/r/fabric8/elasticsearch/tags/

https://github.com/fabric8io/elasticsearch-cloud-kubernetes

由于本人的k8s环境并不通外网,需要先从官网下载镜像，再打上私有仓库的标签。

docker pull elasticsearch:2.3

docker pull kibana:4.5

docker tag elasticsearch:2.3 10.10.50.161:5000/elasticsearch:2.3

docker tag kibana:4.5 10.10.50.161:5000/kibana:4.5

docker push 10.10.50.161:5000/elasticsearch:2.3

docker push 10.10.50.161:5000/kibana:4.5

生成rc和svc:

kubectl create -f elasticsearch-kibana-svc.yaml
kubectl create -f elasticsearch-kibana-rc.yaml

elasticsearch-kibana-rc.yaml:

apiVersion: v1
kind: ReplicationController
metadata:
 name: elasticsearch-kibana
 namespace: kube-system
 labels:
 k8s-app: elasticsearch-kibana
 version: v1
 kubernetes.io/cluster-service: "true"
spec:
 replicas: 1
 selector:
 k8s-app: elasticsearch-kibana
 version: v1
 template:
 metadata:
 labels:
 k8s-app: elasticsearch-kibana
 version: v1
 kubernetes.io/cluster-service: "true"
 spec:
 containers:
 - image: 10.10.50.161:5000/elasticsearch:2.3
 name: elasticsearch 
 resources:
 # keep request = limit to keep this container in guaranteed class
 limits:
 cpu: 100m
 requests:
 cpu: 100m
 ports:
 - containerPort: 9200
 name: http
 protocol: TCP
 - containerPort: 9300
 name: transport
 protocol: TCP
 volumeMounts:
 - name: es-persistent-storage
 mountPath: /usr/share/elasticsearch/data
 - image: 10.10.50.161:5000/kibana:4.5
 name: kibana
 resources:
 # keep request = limit to keep this container in guaranteed class
 limits:
 cpu: 100m
 requests:
 cpu: 100m
 ports:
 - containerPort: 5601
 name: ui
 protocol: TCP
 env:
 - name: ELASTICSEARCH_URL
 value: http://localhost:9200
 volumes:
 - name: es-persistent-storage
 emptyDir: {}

elasticsearch-kibana-svc.yaml:

apiVersion: v1
kind: Service
metadata:
 name: elasticsearch-kibana
 namespace: kube-system
 labels:
 k8s-app: elasticsearch-kibana
 kubernetes.io/cluster-service: "true"
 kubernetes.io/name: "elasticsearch-kibana"
spec:
 type: NodePort
 ports:
 - name: elasticsearch-http
 port: 9200
 protocol: TCP
 targetPort: http
 - name: elasticsearch-transport
 port: 9300
 protocol: TCP
 targetPort: transport
 - name: kibana
 port: 5601
 protocol: TCP
 targetPort: ui
 nodePort: 30016
 selector:
 k8s-app: elasticsearch-kibana

注意:这里我把elasticsearch的日志存储放在了pod的empty volumns里了，真正的运行环境应该使用nodeSelector选定一台node，并把日志存储放在node里的/usr/share/elasticsearch/data。

5. Fluentd

重点就是fluentd,addons里的依赖kube.up里引用的make ca制作认证。而我的环境进行认证时，使用了前面一同事部署heapster+influxdb+grafana时用的单域名认证,之后再进行多域名认证时,搞得乱七八糟，索性决定绕过k8s内部环境。

多域名认证参考:

https://coreos.com/kubernetes/docs/latest/openssl.html

http://www.linuxidc.com/Linux/2014-10/108222.htm

http://apetec.com/support/GenerateSAN-CSR.htm

https://certificates.heanet.ie/node/17

这里使用fabric8的fabric8/fluentd-kubernetes镜像,但需要重新制作镜像。

fabric8/fluentd-kubernetes本身不依赖https和认证,但里面的fluentd插件fluent-plugin-kubernetes_metadata_filter依赖了https和认证,这也是比较蛋疼的事。

首先pull官网的镜像

docker pull fabric8/fluentd-kubernetes:v1.14
docker tag fabric8/fluentd-kubernetes:v1.14 10.10.50.161:5000/fabric8/fluentd-kubernetes:v1.14

制作镜像:

mkdir myfluent
cd fluent-plugin
touch Dockerfile
touch start-fluentd

Dockerfile:

FROM 10.10.50.161:5000/fabric8/fluentd-kubernetes:v1.14

MAINTAINER miaobainian <miaobainian36@163.com>

ADD start-fluentd /start-fluentd

start-fluentd:

#!/bin/sh

ELASTICSEARCH_HOST=${ELASTICSEARCH_HOST:-es-logging.default.svc}
ELASTICSEARCH_PORT=${ELASTICSEARCH_PORT:-9200}
ELASTICSEARCH_SCHEME=${ELASTICSEARCH_SCHEME:-http}

FLUENTD_FLUSH_INTERVAL=${FLUENTD_FLUSH_INTERVAL:-10s}
FLUENTD_FLUSH_THREADS=${FLUENTD_FLUSH_THREADS:-1}
FLUENTD_RETRY_LIMIT=${FLUENTD_RETRY_LIMIT:-10}
FLUENTD_DISABLE_RETRY_LIMIT=${FLUENTD_DISABLE_RETRY_LIMIT:-true}
FLUENTD_RETRY_WAIT=${FLUENTD_RETRY_WAIT:-1s}
FLUENTD_MAX_RETRY_WAIT=${FLUENTD_MAX_RETRY_WAIT:-60s}
FLUENTD_BUFFER_CHUNK_LIMIT=${FLUENTD_BUFFER_CHUNK_LIMIT:-8m}
FLUENTD_BUFFER_QUEUE_LIMIT=${FLUENTD_BUFFER_QUEUE_LIMIT:-8192}
FLUENTD_BUFFER_TYPE=${FLUENTD_BUFFER_TYPE:-memory}
FLUENTD_BUFFER_PATH=${FLUENTD_BUFFER_PATH:-/var/fluentd/buffer}
FLUENTD_LOGSTASH_FORMAT=${FLUENTD_LOGSTASH_FORMAT:-true}

KUBERNETES_PRESERVE_JSON_LOG=${KUBERNETES_PRESERVE_JSON_LOG:-true}


mkdir /etc/fluent

cat << EOF >> /etc/fluent/fluent.conf
<source>
 type tail
 path /var/log/containers/*.log
 pos_file /var/log/es-containers.log.pos
 time_format %Y-%m-%dT%H:%M:%S.%N
 tag kubernetes.*
 format json
 read_from_head true
 keep_time_key true
</source>

<filter kubernetes.**>
 type kubernetes_metadata
 preserve_json_log ${KUBERNETES_PRESERVE_JSON_LOG}
 kubernetes_url ${KUBERNETES_URL}
 verify_ssl ${VERIFY_SSL}
</filter>

<match **>
 type elasticsearch$([ "${ELASTICSEARCH_DYNAMIC}" == "true" ] && echo _dynamic)
 log_level info
 include_tag_key true
 time_key time
 host ${ELASTICSEARCH_HOST}
 port ${ELASTICSEARCH_PORT}
 scheme ${ELASTICSEARCH_SCHEME}
 $([ -n "${ELASTICSEARCH_USER}" ] && echo user ${ELASTICSEARCH_USER})
 $([ -n "${ELASTICSEARCH_PASSWORD}" ] && echo password ${ELASTICSEARCH_PASSWORD})
 buffer_type ${FLUENTD_BUFFER_TYPE}
 $([ "${FLUENTD_BUFFER_TYPE}" == "file" ] && echo buffer_path ${FLUENTD_BUFFER_PATH})
 buffer_chunk_limit ${FLUENTD_BUFFER_CHUNK_LIMIT}
 buffer_queue_limit ${FLUENTD_BUFFER_QUEUE_LIMIT}
 flush_interval ${FLUENTD_FLUSH_INTERVAL}
 retry_limit ${FLUENTD_RETRY_LIMIT}
 $([ "${FLUENTD_DISABLE_RETRY_LIMIT}" == "true" ] && echo disable_retry_limit)
 retry_wait ${FLUENTD_RETRY_WAIT}
 max_retry_wait ${FLUENTD_MAX_RETRY_WAIT}
 num_threads ${FLUENTD_FLUSH_THREADS}
 logstash_format ${FLUENTD_LOGSTASH_FORMAT}
 $([ -n "${FLUENTD_LOGSTASH_PREFIX}" ] && echo logstash_prefix ${FLUENTD_LOGSTASH_PREFIX})
 reload_connections false
EOF

cat << 'EOF' >> /etc/fluent/fluent.conf
</match>
EOF

exec je fluentd

注意这里比官方的start-fluentd增加关键的两行:

kubernetes_url ${KUBERNETES_URL}
verify_ssl ${VERIFY_SSL}

目的是绕过https://clusterIp:443的验证。

docker build -t 10.10.50.161:5000/fabric8/fluentd-kubernetes:v1.15 .
docker push 10.10.50.161:5000/fabric8/fluentd-kubernetes:v1.15

ok,fluentd的镜像定义好了之后，就可以生成pod了，可以使用static pod,但是推荐使用daemon sets

touch fluentd-daemon.yaml

fluentd-daemon.yaml :

apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
 name: fluentd-elasticsearch
 namespace: kube-system
 labels:
 k8s-app: fluentd-logging
spec:
 template:
 metadata:
 labels:
 k8s-app: fluentd-logging
 spec:
 containers:
 - name: fluentd-elasticsearch
 image: 10.10.50.161:5000/fabric8/fluentd-kubernetes:v1.16
 resources:
 limits:
 cpu: 100m
 volumeMounts:
 - name: varlog
 mountPath: /var/log
 - name: varlibdockercontainers
 mountPath: /var/lib/docker/containers
 readOnly: true
 env:
 - name: KUBERNETES_URL
 value: "http://10.10.50.156:8080/api"
 - name: VERIFY_SSL
 value: "false"
 - name: ELASTICSEARCH_HOST
 value: elasticsearch-kibana
 - name: ELASTICSEARCH_PORT
 value: "9200"
 - name: FLUENTD_FLUSH_INTERVAL
 value: "300s"
 volumes:
 - name: varlog
 hostPath:
 path: /var/log
 - name: varlibdockercontainers
 hostPath:
 path: /var/lib/docker/containers
kubectl create -f fluentd-daemon.yaml

注意这里的环境变量:

KUBERNETES_URL使用的是k8s master node的master api。

VERIFY_SSL为false表示不验证ca。

ELASTICSEARCH_HOST是前面部署的elasticsearch-kibana服务名,依赖于dns(服务名即dns名),如果没有装dns，你也可以使用kubectl get svc --namespace=kube-system找到elasticsearch-kibana的集群ip,配置集群ip也可以。但集群ip是可变的,这个要注意。

ELASTICSEARCH_PORT是elasticsearch-kibana中elasticsearch的服务内部端口。
FLUENTD_FLUSH_INTERVAL用于标识收集时间间隔,设置为300s是因为第一次收集时，花费的时间较长，时间间隔不够会导致elasticsearch不停的重新连接。

ok,现在all is already。

在浏览器打开:

http://10.10.50.155:30016/

10.10.50.155是我的k8s集群中的一个node,30016是elasticsearch-kibana服务的node port。

进行kibana的界面。

默认进入Settings的indices界面。

将Index contains time-based events的打勾去掉。点击下面的create。

ok，喝杯coffee or tea,等待k8s的日志出现就可以了。

本文转移开源中国-在Kubernetes上搭建EFK（Fluentd＋Elasticsearch＋Kibana）

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