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Kubernetes 0-1 K8s部署EFK #
写在前面 #
本篇目标是在K8s集群中搭建EFK。
EFK是由ElasticSearch，Fluentd，Kibane组成的一套目前比较主流的日志监控系统，使用EFK监控应用日志，可以让开发人员在一个统一的入口查看日志然后分析应用运行情况。
EFK简单的工作原理可以参考下图。通过fluentd的agent收集日志数据，写入es，kibana从es中读取日志数据展示到ui。
部署ElasticSearch #
最好选择部署一个ES集群，这样你的ES可用性更高一点。
采用StatefulSet部署ES。
编写es-statefulSet.yaml文件如下：
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: es-cluster
namespace: dev
spec:
serviceName: elasticsearch
replicas: 3
selector:
matchLabels:
app: elasticsearch
template:
metadata:
labels:
app: elasticsearch
spec:
containers:
- name: elasticsearch
image: docker.elastic.co/elasticsearch/elasticsearch:7.7.0
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
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
command: ["sysctl", "-w", "vm.max_map_count=262144"]
securityContext:
privileged: true
- name: increase-fd-ulimit
image: busybox
command: ["sh", "-c", "ulimit -n 65536"]
securityContext:
privileged: true
volumeClaimTemplates:
- metadata:
name: data
labels:
app: elasticsearch
spec:
accessModes: ["ReadWriteOnce"]
storageClassName: gp2
resources:
requests:
storage: 40Gi
编写es.service.yaml文件如下：
kind: Service
apiVersion: v1
metadata:
name: elasticsearch
namespace: dev
spec:
selector:
app: elasticsearch
type: NodePort
ports:
- name: elasticsearch-http
port: 9200
targetPort: 9200
部署Kibana #
编写kibana-deployment.yaml文件如下：
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: kibana
namespace: dev
labels:
name: kibana
spec:
strategy:
rollingUpdate:
maxSurge: 1
maxUnavailable: 1
type: RollingUpdate
template:
metadata:
labels:
name: kibana
spec:
containers:
- image: docker.elastic.co/kibana/kibana:7.7.0
imagePullPolicy: Always
name: kibana
resources:
requests:
cpu: "1000m"
memory: "256M"
limits:
cpu: "1000m"
memory: "1024M"
# livenessProbe:
# httpGet:
# path: /_status/healthz
# port: 5000
# initialDelaySeconds: 90
# timeoutSeconds: 10
# readinessProbe:
# httpGet:
# path: /_status/healthz
# port: 5000
# initialDelaySeconds: 30
# timeoutSeconds: 10
env:
- name: ELASTICSEARCH_URL
value: http://elasticsearch:9200
- name: SERVER_BASEPATH
value: /kibana
- name: SERVER_REWRITEBASEPATH
value: "true"
# args:
# - server.rewriteBasePath=true
# - server.basePath=/kibana
ports:
- containerPort: 5601
name: kibana-port
# volumeMounts:
# - mountPath: /etc/kibana/config
# name: grafana-data
# volumes:
# - name: grafana-data
# configMap:
# name: grafana-config
restartPolicy: Always
编写kibana-service.yaml文件如下：
kind: Service
apiVersion: v1
metadata:
name: kibana
namespace: dev
spec:
selector:
name: kibana
type: NodePort
ports:
- name: kibana-http
port: 5601
targetPort: 5601
部署Fluentd #
Fluentd是一个开源的数据收集器，可以做数据的集中收集，便于做数据使用和分析，常用于日志收集。
我们部署Fluentd来收集部署在k8s Pod中的程序的话，首先需要集群赋予它访问Pod的权限，因为我们需要为fluentd分配一个带有Pod相关权限的serviceAccount。
编写fluentd-serviceAccount.yaml文件如下：
apiVersion: v1
kind: ServiceAccount
metadata:
name: fluentd
namespace: dev
labels:
app: fluentd
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: fluentd
namespace: dev
labels:
app: fluentd
rules:
- apiGroups:
- ""
resources:
- pods
- namespaces
verbs:
- get
- list
- watch
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
name: fluentd
namespace: dev
roleRef:
kind: ClusterRole
name: fluentd
apiGroup: rbac.authorization.k8s.io
subjects:
- kind: ServiceAccount
name: fluentd
namespace: dev
我们需要在每台节点上都部署Fluent，这相当于是一个日志收集的Agent，因此我们采用DaemonSet的方式部署Fluentd。
编写fluentd-daemonSet.yaml文件如下：
apiVersion: apps/v1
kind: DaemonSet
metadata:
name: fluentd
namespace: dev
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: fluent/fluentd-kubernetes-daemonset:v1.10.4-debian-elasticsearch7-1.0
env:
- name: FLUENT_ELASTICSEARCH_HOST
value: "elasticsearch.dev.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: 256Mi
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
文件准备好之后，执行
kubectl apply -f ./fluentd-serviceAccount.yaml
kubectl apply -f ./fluentd-daemonSet.yaml
部署之后，查看fluentd daemonset的部署情况
kubectl get ds -n kube-system
输出信息大致如下：
NAME DESIRED CURRENT READY UP-TO-DATE AVAILABLE NODE SELECTOR AGE
fluentd 3 3 3 3 3 <none> 33s
如果DESIRED和READY列值不一致的话，说明是某个Node上的Pod启用失败了。那么可以查看Pod的启用情况：
kubectl get pod -n kube-system
# 假设Pod fluentd-8hmbd一直未成功启用，使用kubectl describe 或kubectl logs命令检查
kubectl describe pod fluentd-8hmbd -n kube-system
kubectl logs fluentd-8hmbd -n kube-system