目录
1、在k8s中安装EFK组件
1.1 安装elasticsearch组件
1.2 安装kibana组件
1.3 安装fluentd组件
文档中的YAML文件配置直接复制粘贴可能存在格式错误，故实验中所需要的YAML文件以及本地包均打包至网盘
链接：https://pan.baidu.com/s/15Ryaoa0_9ABQElLw9y28DA
提取码：xdbm
基于 K8S kubernetes 的常见日志收集方案:
https://chenyun.blog.csdn.net/article/details/142336441
https://chenyun.blog.csdn.net/article/details/142336441
https://registry.hub.docker.com/_/elasticsearch?tab=tags&page=1&ordering=last_updated
Kibana版本，目前官方docker hub更新到7.12.1
https://registry.hub.docker.com/_/kibana?tab=tags&page=1&ordering=last_updated
Fluentd版本，目前官方docker hub更新到1.9.2
https://registry.hub.docker.com/_/fluentd?tab=tags&page=1&ordering=last_updated
1、在k8s中安装EFK组件
把elasticsearch-7-12-1.tar.gz和 fluentd-v1-9-1.tar.gz和 kibana-7-12-1.tar.gz上传到xianchaomaster1和xianchaonode1机器上，手动解压
docker load -i elasticsearch-7-12-1.tar.gz
docker load -i kibana-7-12-1.tar.gz
docker load -i fluentd-v1-9-1.tar.gz
安装nfs供应商
#安装nfs服务，选择k8s集群的xianchaomaster1节点，k8s集群的xianchaomaster1节点的ip是192.168.40.180
[root@xianchaomaster1 ~]# yum install nfs-utils -y
[root@xianchaonode1 ~]# yum install nfs-utils -y
#启动nfs服务
[root@xianchaomaster1 ~]# systemctl start nfs
[root@xianchaonode1 ~]# systemctl start nfs
#设置nfs开机自启动
[root@xianchaomaster1 ~]# systemctl enable nfs.service
[root@xianchaonode1 ~]# systemctl enable nfs.service
#在xianchaomaster1上创建一个nfs共享目录
[root@xianchaomaster1 ~]# mkdir /data/v1 -p
#编辑/etc/exports文件
- [root@xianchaomaster1 ~]# vim /etc/exports
/data/v1 *(rw,no_root_squash)
#加载配置，使配置生效
[root@xianchaomaster1 ~]# exportfs -arv
[root@xianchaomaster1 ~]# systemctl restart nfs
#创建nfs作为存储的供应商
[root@xianchaomaster1 nfs]# cat serviceaccount.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
name: nfs-provisioner
[root@xianchaomaster1 nfs]# kubectl apply -f serviceaccount.yaml
serviceaccount/nfs-provisioner created
sa的全称是serviceaccount。
serviceaccount是为了方便Pod里面的进程调用Kubernetes API或其他外部服务而设计的。
指定了serviceaccount之后，我们把pod创建出来了，我们在使用这个pod时，这个pod就有了我们指定的账户的权限了。
[root@xianchaomaster1]# kubectl create clusterrolebinding nfs-provisioner-clusterrolebinding --clusterrole=cluster-admin --serviceaccount=default:nfs-provisioner
#把nfs-subdir-external-provisioner.tar.gz上传到xianchaonode1上，手动解压。
[root@xianchaonode1 ~]# docker load -i nfs-subdir-external-provisioner.tar.gz
#通过deployment创建pod用来运行nfs-provisioner
[root@xianchaomaster1]# kubectl apply -f deployment.yaml
deployment.yaml文件解释说明：
kind: Deployment
apiVersion: apps/v1
metadata:
name: nfs-provisioner
spec:
selector:
matchLabels:
app: nfs-provisioner
replicas: 1
strategy:
type: Recreate
template:
metadata:
labels:
app: nfs-provisioner
spec:
serviceAccount: nfs-provisioner
containers:
- name: nfs-provisioner
image: registry.cn-beijing.aliyuncs.com/mydlq/nfs-subdir-external-provisioner:v4.0.0
imagePullPolicy: IfNotPresent
volumeMounts:
- name: nfs-client-root
mountPath: /persistentvolumes
env:
- name: PROVISIONER_NAME
value: example.com/nfs
- name: NFS_SERVER
value: 192.168.40.180
#这个需要写nfs服务端所在的ip地址，大家需要写自己安装了nfs服务的机器ip
- name: NFS_PATH
value: /data/v1
#这个是nfs服务端共享的目录
volumes:
- name: nfs-client-root
nfs:
server: 192.168.40.180
path: /data/v1
#验证nfs是否创建成功
[root@xianchaomaster1]# kubectl get pods | grep nfs
#显示如下说明创建成功：
nfs-provisioner-5975849bb4-92dhq 1/1 Running 3 11h
#创建stoorageclass
[root@xianchaomaster1]# kubectl apply -f class.yaml
class.yaml文件内容如下：
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
name: do-block-storage
provisioner: example.com/nfs
注：
provisioner: example.com/nfs
#该值需要和nfs provisioner配置的PROVISIONER_NAME处的value值保持一致
1.1 安装elasticsearch组件
[root@xianchaomaster1 efk]# cat kube-logging.yaml
kind: Namespace
apiVersion: v1
metadata:
name: kube-logging
[root@xianchaomaster1 efk]# kubectl apply -f kube-logging.yaml
kubectl get namespaces | grep kube-logging
显示如下，说明创建成功
kube-logging Active 1m
3.安装elasticsearch组件
#创建headless service
[root@xianchaomaster1 efk]# cat elasticsearch_svc.yaml
kind: Service
apiVersion: v1
metadata:
name: elasticsearch
namespace: kube-logging
labels:
app: elasticsearch
spec:
selector:
app: elasticsearch
clusterIP: None
ports:
- port: 9200
name: rest
- port: 9300
name: inter-node
[root@xianchaomaster1 efk]# kubectl apply -f elasticsearch_svc.yaml
查看elasticsearch的service是否创建成功
[root@xianchaomaster1 efk]# kubectl get services --namespace=kube-logging
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S)
elasticsearch ClusterIP None <none> 9200/TCP,9300/TCP
#创建storageclass
[root@xianchaomaster1 efk]# cat es_class.yaml
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
name: do-block-storage
provisioner: example.com/nfs
[root@xianchaomaster1 efk]# kubectl apply -f es_class.yaml
[root@xianchaomaster1 efk]# cat elasticsearch-statefulset.yaml
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: es-cluster
namespace: kube-logging
spec:
serviceName: elasticsearch
replicas: 3
selector:
matchLabels:
app: elasticsearch
template:
metadata:
labels:
app: elasticsearch
spec:
containers:
- name: elasticsearch
image: elasticsearch:7.12.1
imagePullPolicy: IfNotPresent
resources:
limits:
cpu: 1000m
requests:
cpu: 100m
ports:
- containerPort: 9200
name: rest
protocol: TCP
- containerPort: 9300
name: inter-node
protocol: TCP
volumeMounts:
- name: data
mountPath: /usr/share/elasticsearch/data
env:
- name: cluster.name
value: k8s-logs
- name: node.name
valueFrom:
fieldRef:
fieldPath: metadata.name
- name: discovery.seed_hosts
value: "es-cluster-0.elasticsearch,es-cluster-1.elasticsearch,es-cluster-2.elasticsearch"
- name: cluster.initial_master_nodes
value: "es-cluster-0,es-cluster-1,es-cluster-2"
- name: ES_JAVA_OPTS
value: "-Xms512m -Xmx512m"
initContainers:
- name: fix-permissions
image: busybox
imagePullPolicy: IfNotPresent
command: ["sh", "-c", "chown -R 1000:1000 /usr/share/elasticsearch/data"]
securityContext:
privileged: true
volumeMounts:
- name: data
mountPath: /usr/share/elasticsearch/data
- name: increase-vm-max-map
image: busybox
imagePullPolicy: IfNotPresent
command: ["sysctl", "-w", "vm.max_map_count=262144"]
securityContext:
privileged: true
- name: increase-fd-ulimit
image: busybox
imagePullPolicy: IfNotPresent
command: ["sh", "-c", "ulimit -n 65536"]
securityContext:
privileged: true
volumeClaimTemplates:
- metadata:
name: data
labels:
app: elasticsearch
spec:
accessModes: [ "ReadWriteOnce" ]
storageClassName: do-block-storage
resources:
requests:
storage: 10Gi
[root@xianchaomaster1 efk]# kubectl apply -f elasticsearch-statefulset.yaml
[root@xianchaomaster1 efk]# kubectl get pods -n kube-logging
NAME READY STATUS RESTARTS AGE
es-cluster-0 1/1 Running 6 11h
es-cluster-1 1/1 Running 2 11h
es-cluster-2 1/1 Running 2 11h
[root@xianchaomaster1 efk]# kubectl get svc -n kube-logging
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S)
elasticsearch ClusterIP None <none> 9200/TCP,9300/TCP
1.2 安装kibana组件
[root@xianchaomaster1 efk]# cat kibana.yaml
apiVersion: v1
kind: Service
metadata:
name: kibana
namespace: kube-logging
labels:
app: kibana
spec:
ports:
- port: 5601
selector:
app: kibana
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: kibana
namespace: kube-logging
labels:
app: kibana
spec:
replicas: 1
selector:
matchLabels:
app: kibana
template:
metadata:
labels:
app: kibana
spec:
containers:
- name: kibana
image: kibana:7.12.1
imagePullPolicy: IfNotPresent
resources:
limits:
cpu: 1000m
requests:
cpu: 100m
env:
- name: ELASTICSEARCH_URL
value: http://elasticsearch:9200
ports:
- containerPort: 5601
配置完成后，直接使用 kubectl 工具创建：
[root@xianchaomaster1 efk]# kubectl apply -f kibana.yaml
[root@xianchaomaster1 efk]# kubectl get pods -n kube-logging
NAME READY STATUS RESTARTS AGE
es-cluster-0 1/1 Running 6 11h
es-cluster-1 1/1 Running 2 11h
es-cluster-2 1/1 Running 2 11h
kibana-84cf7f59c-vvm6q 1/1 Running 2 11h
[root@xianchaomaster1 efk]# kubectl get svc -n kube-logging
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S)
elasticsearch ClusterIP None <none> 9200/TCP,9300/TCP
kibana NodePort 10.108.195.109 <none> 5601:32329/TCP
修改service的type类型为NodePort：
kubectl edit svc kibana -n kube-logging
把type: ClusterIP变成type: NodePort
保存退出之后
[root@xianchaomaster1 efk]# kubectl get svc -n kube-logging
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S)
elasticsearch ClusterIP None <none> 9200/TCP,9300/TCP
kibana NodePort 10.108.195.109 <none> 5601:32329/TCP
在浏览器中打开http://<k8s集群任意节点IP>:32462即可，如果看到如下欢迎界面证明 Kibana 已经成功部署到了Kubernetes集群之中。
1.3 安装fluentd组件
我们使用daemonset控制器部署fluentd组件，这样可以保证集群中的每个节点都可以运行同样fluentd的pod副本，这样就可以收集k8s集群中每个节点的日志，在k8s集群中，容器应用程序的输入输出日志会重定向到node节点里的json文件中
，fluentd可以tail和过滤以及把日志转换成指定的格式发送到elasticsearch集群中。除了容器日志，fluentd也可以采集kubelet、kube-proxy、docker的日志。
[root@xianchaomaster1 efk]# cat fluentd.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
name: fluentd
namespace: kube-logging
labels:
app: fluentd
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: fluentd
labels:
app: fluentd
rules:
- apiGroups:
- ""
resources:
- pods
- namespaces
verbs:
- get
- list
- watch
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
name: fluentd
roleRef:
kind: ClusterRole
name: fluentd
apiGroup: rbac.authorization.k8s.io
subjects:
- kind: ServiceAccount
name: fluentd
namespace: kube-logging
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
name: fluentd
namespace: kube-logging
labels:
app: fluentd
spec:
selector:
matchLabels:
app: fluentd
template:
metadata:
labels:
app: fluentd
spec:
serviceAccount: fluentd
serviceAccountName: fluentd
tolerations:
- key: node-role.kubernetes.io/master
effect: NoSchedule
containers:
- name: fluentd
image: fluentd:v1.9.1-debian-1.0
imagePullPolicy: IfNotPresent
env:
- name: FLUENT_ELASTICSEARCH_HOST
value: "elasticsearch.kube-logging.svc.cluster.local"
- name: FLUENT_ELASTICSEARCH_PORT
value: "9200"
- name: FLUENT_ELASTICSEARCH_SCHEME
value: "http"
- name: FLUENTD_SYSTEMD_CONF
value: disable
resources:
limits:
memory: 512Mi
requests:
cpu: 100m
memory: 200Mi
volumeMounts:
- name: varlog
mountPath: /var/log
- name: varlibdockercontainers
mountPath: /var/lib/docker/containers
readOnly: true
terminationGracePeriodSeconds: 30
volumes:
- name: varlog
hostPath:
path: /var/log
- name: varlibdockercontainers
hostPath:
path: /var/lib/docker/containers
[root@xianchaomaster1 efk]# kubectl apply -f fluentd.yaml
[root@xianchaomaster1 efk]# kubectl get pods -n kube-logging
NAME READY STATUS RESTARTS AGE
es-cluster-0 1/1 Running 6 11h
es-cluster-1 1/1 Running 2 11h
es-cluster-2 1/1 Running 2 11h
fluentd-m8rgp 1/1 Running 3 11h
fluentd-wbl4z 1/1 Running 0 11h
kibana-84cf7f59c-vvm6q 1/1 Running 2 11h
Fluentd 启动成功后，我们可以前往 Kibana 的 Dashboard 页面中，点击左侧的Discover，可以看到如下配置页面：
在这里可以配置我们需要的 Elasticsearch 索引，前面 Fluentd 配置文件中我们采集的日志使用的是 logstash 格式，这里只需要在文本框中输入logstash-*即可匹配到 Elasticsearch 集群中的所有日志数据，然后点击下一步，进入以下页面：
点击next step，出现如下
选择@timestamp，创建索引
点击左侧的discover，可看到如下：
Kibana Query Language | Kibana Guide [7.12] | Elastic
Kibana Query Language | Kibana Guide [7.12] | Elastic
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