Kubernetes中EFK怎么用

2023-06-04 11:06:05 493人浏览安东尼

摘要

这篇文章给大家分享的是有关kubernetes中EFK怎么用的内容。小编觉得挺实用的，因此分享给大家做个参考，一起跟随小编过来看看吧。一：前言1.在安装Kubernetes集群的时候我们有下载过压缩包https://dl.k8s.io/v1

这篇文章给大家分享的是有关kubernetes中EFK怎么用的内容。小编觉得挺实用的，因此分享给大家做个参考，一起跟随小编过来看看吧。

一：前言

1.在安装Kubernetes集群的时候我们有下载过压缩包https://dl.k8s.io/v1.8.5/kubernetes-client-linux-amd64.tar.gz
解压缩后在目录cluster\addons 下有各插件的yaml文件，大部分情况仅需少量改动即可使用。

2.在搭建Kubernetes的集群过程中，涉及到很多镜像的下载，建议可以在阿里云购买一个香港所在地的ECS服务器，镜像下载完成后通过Docker save -o 将镜像导出，在通过docker load 导入镜像或者上传镜像到个人镜像仓库。

3.Kubernetes从1.8版本开始，EFK的安装中，elasticsearch-logging采用StatefulSet类型，但存在bug,会导致elasticsearch-logging-0 POD 一直无法成功创建。所以建议还是采用1.8之前的版本采用ReplicationController。

4.要成功安装EFK，一定要先安装kube-dns前面的文章已有介绍。

5.EFK安装过程中elasticsearch和kibana版本要兼容。这里采用的镜像如下：
GCr.io/Google_containers/elasticsearch:v2.4.1-2

gcr.io/google_containers/fluentd-elasticsearch:1.22

gcr.io/google_containers/kibana:v4.6.1-1

二：yaml文件
Kubernetes中EFK怎么用

efk-rbac.yaml

点击(此处)折叠或打开

apiVersion: v1
kind: ServiceAccount
metadata:
name: efk
namespace: kube-system
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
name: efk
subjects:
- kind: ServiceAccount
name: efk
namespace: kube-system
roleRef:
kind: ClusterRole
name: cluster-admin
apiGroup: rbac.authorization.k8s.io

es-controller.yaml

点击(此处)折叠或打开

apiVersion: v1
kind: ReplicationController
metadata:
name: elasticsearch-logging-v1
namespace: kube-system
labels:
k8s-app: elasticsearch-logging
version: v1
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
spec:
replicas: 2
selector:
k8s-app: elasticsearch-logging
version: v1
template:
metadata:
labels:
k8s-app: elasticsearch-logging
version: v1
kubernetes.io/cluster-service: "true"
spec:
serviceAccountName: efk
containers:
- image: gcr.io/google_containers/elasticsearch:v2.4.1-2
name: elasticsearch-logging
resources:
# need more cpu upon initialization, therefore burstable class
limits:
cpu: 1000m
requests:
cpu: 100m
ports:
- containerPort: 9200
name: db
protocol: tcp
- containerPort: 9300
name: transport
protocol: TCP
volumeMounts:
- name: es-persistent-storage
mountPath: /data
env:
- name: "NAMESPACE"
valueFrom:
fieldRef:
fieldPath: metadata.namespace
volumes:
- name: es-persistent-storage
emptyDir: {}

es-service.yaml

点击(此处)折叠或打开

apiVersion: v1
kind: Service
metadata:
name: elasticsearch-logging
namespace: kube-system
labels:
k8s-app: elasticsearch-logging
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
kubernetes.io/name: "Elasticsearch"
spec:
ports:
- port: 9200
protocol: TCP
targetPort: db
selector:
k8s-app: elasticsearch-logging

fluentd-es-ds.yaml

点击(此处)折叠或打开

apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
name: fluentd-es-v1.22
namespace: kube-system
labels:
k8s-app: fluentd-es
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
version: v1.22
spec:
template:
metadata:
labels:
k8s-app: fluentd-es
kubernetes.io/cluster-service: "true"
version: v1.22
# This annotation ensures that fluentd does not get evicted if the node
# supports critical pod annotation based priority scheme.
# Note that this does not guarantee admission on the nodes (#40573).
annotations:
scheduler.alpha.kubernetes.io/critical-pod: ''
spec:
serviceAccountName: efk
containers:
- name: fluentd-es
image: gcr.io/google_containers/fluentd-elasticsearch:1.22
command:
- '/bin/sh'
- '-c'
- '/usr/sbin/td-agent 2>&1 >> /var/log/fluentd.log'
resources:
limits:
memory: 200Mi
requests:
cpu: 100m
memory: 200Mi
volumeMounts:
- name: varlog
mountPath: /var/log
- name: varlibdockercontainers
mountPath: /var/lib/docker/containers
readOnly: true
nodeSelector:
beta.kubernetes.io/fluentd-ds-ready: "true"
tolerations:
- key : "node.alpha.kubernetes.io/ismaster"
effect: "NoSchedule"
terminationGracePeriodSeconds: 30
volumes:
- name: varlog
hostPath:
path: /var/log
- name: varlibdockercontainers
hostPath:
path: /var/lib/docker/containers

kibana-controller.yaml 此处需要特殊说明，绿色标识的部分KIBANA_BASE_URL 的value要设置为空，默认值会导致Kibana访问出现问题。

点击(此处)折叠或打开

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: kibana-logging
namespace: kube-system
labels:
k8s-app: kibana-logging
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
spec:
replicas: 1
selector:
matchLabels:
k8s-app: kibana-logging
template:
metadata:
labels:
k8s-app: kibana-logging
spec:
serviceAccountName: efk
containers:
- name: kibana-logging
image: gcr.io/google_containers/kibana:v4.6.1-1
resources:
# keep request = limit to keep this container in guaranteed class
limits:
cpu: 100m
requests:
cpu: 100m
env:
- name: "ELASTICSEARCH_URL"
value: "Http://elasticsearch-logging:9200"
- name: "KIBANA_BASE_URL"
value: ""
ports:
- containerPort: 5601
name: ui
protocol: TCP

kibana-service.yaml

点击(此处)折叠或打开

apiVersion: v1
kind: Service
metadata:
name: kibana-logging
namespace: kube-system
labels:
k8s-app: kibana-logging
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
kubernetes.io/name: "Kibana"
spec:
ports:
- port: 5601
protocol: TCP
targetPort: ui
selector:
k8s-app: kibana-logging

三：启动与验证

1. 创建资源
kubectl create -f .
Kubernetes中EFK怎么用

2.通过 kubectl logs -f 查看相关pod的日志，确认是否正常启动。其中kibana-logging-* POD 启动需要一定的时间。

3.elasticsearch验证（可以通过kube proxy创建代理）
http://IP：PORT/_cat/nodes?v

点击(此处)折叠或打开

host ip heap.percent ram.percent load node.role master name
1.88.4 10.1.88.4 9 87 0.45 d m elasticsearch-logging-v1-hnfv2
1.67.4 10.1.67.4 6 91 0.03 d * elasticsearch-logging-v1-zmtdl

http://IP：PORT/_cat/indices?v

点击(此处)折叠或打开

health status index pri rep docs.count docs.deleted store.size pri.store.size
green open logstash-2018.04.07 5 1 515 0 1.1mb 584.4kb
green open .kibana 1 1 2 0 22.2kb 9.7kb
green open logstash-2018.04.06 5 1 15364 0 7.3mb 3.6mb

kibana验证
http://IP：PORT/app/kibana#/discover?_g
Kubernetes中EFK怎么用

四：备注
要成功搭建EFK，需要注意一下几点：
1.确保已经成功安装了kube-dns
2.当前版本elasticsearch-logging采用ReplicationController
3.elasticsearch和kibana的版本要兼容
4.KIBANA_BASE_URL value设置为“”