在k8s上部署日志系统elfk
作者：互联网
日志系统elfk
前言
经过上周的技术预研，在本周一通过开会研究，根据公司的现有业务流量和技术栈，决定选择的日志系统方案为：elasticsearch(es)+logstash(lo)+filebeat(fi)+kibana(ki)组合。es选择使用aliyun提供的es，lo&fi选择自己部署，ki是阿里云送的。因为申请ecs需要一定的时间，暂时选择部署在测试&生产环境(吐槽一下，我司测试和生产公用一套k8s并且托管与aliyun......)。用时一天(前期有部署的差不多过)完成在kubernetes上部署完成elfk(先部署起来再说，优化什么的后期根据需要再搞)。
组件简介
es 是一个实时的、分布式的可扩展的搜索引擎，允许进行全文、结构化搜索，它通常用于索引和搜索大量日志数据，也可用于搜索许多不同类型的文。
lo 主要的有点就是它的灵活性，主要因为它有很多插件，详细的文档以及直白的配置格式让它可以在多种场景下应用。我们基本上可以在网上找到很多资源，几乎可以处理任何问题。
作为 Beats 家族的一员，fi 是一个轻量级的日志传输工具，它的存在正弥补了 lo 的缺点fi作为一个轻量级的日志传输工具可以将日志推送到中心lo。
ki是一个分析和可视化平台，它可以浏览、可视化存储在es集群上排名靠前的日志数据，并构建仪表盘。ki结合es操作简单集成了绝大多数es的API，是专业的日志展示应用。
数据采集流程图
日志流向：logs_data---> fi ---> lo ---> es---> ki。
logs_data通过fi收集日志，输出到lo，通过lo做一些过滤和修改之后传送到es数据库，ki读取es数据库做分析。
部署
根据我司的实际集群状况，此文档部署将完全还原日志系统的部署情况。
在本地MAC安装kubectl连接aliyun托管k8s
在客户端(随便本地一台虚机上)安装和托管的k8s一样版本的kubectl
curl -LO https://storage.googleapis.com/kubernetes-release/release/v1.14.8/bin/linux/amd64/kubectl
chmod +x ./kubectl
mv ./kubectl /usr/local/bin/kubectl
将阿里云托管的k8s的kubeconfig 复制到$HOME/.kube/config 目录下，注意用户权限的问题
部署ELFK
申请一个名称空间(一般一个项目一个名称空间)。
# cat kube-logging.yaml
apiVersion: v1
kind: Namespace
metadata:
name: loging
部署es。网上找个差不多的资源清单，根据自己的需求进行适当的修改，运行，出错就根据日志进行再修改。
# cat elasticsearch.yaml
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
name: local-class
namespace: loging
provisioner: kubernetes.io/no-provisioner
volumeBindingMode: WaitForFirstConsumer
# Supported policies: Delete, Retain
reclaimPolicy: Delete
---
kind: PersistentVolume
apiVersion: v1
metadata:
name: datadir1
namespace: logging
labels:
type: local
spec:
storageClassName: local-class
capacity:
storage: 5Gi
accessModes:
- ReadWriteOnce
hostPath:
path: "/data/data1"
---
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: elasticsearch
namespace: loging
spec:
serviceName: elasticsearch
selector:
matchLabels:
app: elasticsearch
template:
metadata:
labels:
app: elasticsearch
spec:
containers:
- name: elasticsearch
image: elasticsearch:7.3.1
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: "discovery.type"
value: "single-node"
- name: cluster.name
value: k8s-logs
- name: node.name
valueFrom:
fieldRef:
fieldPath: metadata.name
- 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: "local-class"
resources:
requests:
storage: 5Gi
---
kind: Service
apiVersion: v1
metadata:
name: elasticsearch
namespace: loging
labels:
app: elasticsearch
spec:
selector:
app: elasticsearch
clusterIP: None
ports:
- port: 9200
name: rest
- port: 9300
name: inter-node
部署ki。因为根据数据采集流程图，ki是和es结合的，配置相对简单。
# cat kibana.yaml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: kibana
namespace: loging
labels:
k8s-app: kibana
spec:
replicas: 1
selector:
matchLabels:
k8s-app: kibana
template:
metadata:
labels:
k8s-app: kibana
spec:
containers:
- name: kibana
image: kibana:7.3.1
resources:
limits:
cpu: 1
memory: 500Mi
requests:
cpu: 0.5
memory: 200Mi
env:
- name: ELASTICSEARCH_HOSTS
#注意value是es的services,因为es是有状态，用的无头服务，所以连接的就不仅仅是pod的名字了
value: http://elasticsearch:9200
ports:
- containerPort: 5601
name: ui
protocol: TCP
---
apiVersion: v1
kind: Service
metadata:
name: kibana
namespace: loging
spec:
ports:
- port: 5601
protocol: TCP
targetPort: ui
selector:
k8s-app: kibana
配置ingress-controller。因为我司用的是阿里云托管的k8s自带的nginx-ingress，并且配置了强制转换https。所以kibana-ingress也要配成https。
# openssl genrsa -out tls.key 2048
# openssl req -new -x509 -key tls.key -out tls.crt -subj /C=CN/ST=Beijing/L=Beijing/O=DevOps/CN=kibana.test.realibox.com
# kubectl create secret tls kibana-ingress-secret --cert=tls.crt --key=tls.key
kibana-ingress配置如下。提供两种，一种是https，一种是https。
https:
# cat kibana-ingress.yaml
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: kibana
namespace: loging
spec:
tls:
- hosts:
- kibana.test.realibox.com
secretName: kibana-ingress-secret
rules:
- host: kibana.test.realibox.com
http:
paths:
- path: /
backend:
serviceName: kibana
servicePort: 5601
http:
# cat kibana-ingress.yaml
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: kibana
namespace: logging
spec:
rules:
- host: kibana.test.realibox.com
http:
paths:
- path: /
backend:
serviceName: kibana
servicePort: 5601
部署lo。因为lo的作用是对fi收集到的日志进行过滤，需要根据不同的日志做不同的处理，所以可能要经常性的进行改动，要进行解耦。所以选择以configmap的形式进行挂载。
# cat logstash.yaml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: logstash
namespace: loging
spec:
replicas: 1
selector:
matchLabels:
app: logstash
template:
metadata:
labels:
app: logstash
spec:
containers:
- name: logstash
image: elastic/logstash:7.3.1
volumeMounts:
- name: config
mountPath: /opt/logstash/config/containers.conf
subPath: containers.conf
command:
- "/bin/sh"
- "-c"
- "/opt/logstash/bin/logstash -f /opt/logstash/config/containers.conf"
volumes:
- name: config
configMap:
name: logstash-k8s-config
---
apiVersion: v1
kind: Service
metadata:
labels:
app: logstash
name: logstash
namespace: loging
spec:
ports:
- port: 8080
targetPort: 8080
selector:
app: logstash
type: ClusterIP
# cat logstash-config.yaml
---
apiVersion: v1
kind: Service
metadata:
labels:
app: logstash
name: logstash
namespace: loging
spec:
ports:
- port: 8080
targetPort: 8080
selector:
app: logstash
type: ClusterIP
---
apiVersion: v1
kind: ConfigMap
metadata:
name: logstash-k8s-config
namespace: loging
data:
containers.conf: |
input {
beats {
port => 8080 #filebeat连接端口
}
}
output {
elasticsearch {
hosts => ["elasticsearch:9200"] #es的service
index => "logstash-%{+YYYY.MM.dd}"
}
}
注意：修改configmap 相当于修改镜像。必须重新apply 应用资源清单才能生效。根据数据采集流程图，lo的数据由fi流入，流向es。
部署fi。fi的主要作用是进行日志的采集，然后将数据交给lo。
# cat filebeat.yaml
---
apiVersion: v1
kind: ConfigMap
metadata:
name: filebeat-config
namespace: loging
labels:
app: filebeat
data:
filebeat.yml: |-
filebeat.config:
inputs:
# Mounted `filebeat-inputs` configmap:
path: ${path.config}/inputs.d/*.yml
# Reload inputs configs as they change:
reload.enabled: false
modules:
path: ${path.config}/modules.d/*.yml
# Reload module configs as they change:
reload.enabled: false
# To enable hints based autodiscover, remove `filebeat.config.inputs` configuration and uncomment this:
#filebeat.autodiscover:
# providers:
# - type: kubernetes
# hints.enabled: true
output.logstash:
hosts: ['${LOGSTASH_HOST:logstash}:${LOGSTASH_PORT:8080}'] #流向lo
---
apiVersion: v1
kind: ConfigMap
metadata:
name: filebeat-inputs
namespace: loging
labels:
app: filebeat
data:
kubernetes.yml: |-
- type: docker
containers.ids:
- "*"
processors:
- add_kubernetes_metadata:
in_cluster: true
---
apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
name: filebeat
namespace: loging
labels:
app: filebeat
spec:
selector:
matchLabels:
app: filebeat
template:
metadata:
labels:
app: filebeat
spec:
serviceAccountName: filebeat
terminationGracePeriodSeconds: 30
containers:
- name: filebeat
image: elastic/filebeat:7.3.1
args: [
"-c", "/etc/filebeat.yml",
"-e",
]
env: #注入变量
- name: LOGSTASH_HOST
value: logstash
- name: LOGSTASH_PORT
value: "8080"
securityContext:
runAsUser: 0
# If using Red Hat OpenShift uncomment this:
#privileged: true
resources:
limits:
memory: 200Mi
requests:
cpu: 100m
memory: 100Mi
volumeMounts:
- name: config
mountPath: /etc/filebeat.yml
readOnly: true
subPath: filebeat.yml
- name: inputs
mountPath: /usr/share/filebeat/inputs.d
readOnly: true
- name: data
mountPath: /usr/share/filebeat/data
- name: varlibdockercontainers
mountPath: /var/lib/docker/containers
readOnly: true
volumes:
- name: config
configMap:
defaultMode: 0600
name: filebeat-config
- name: varlibdockercontainers
hostPath:
path: /var/lib/docker/containers
- name: inputs
configMap:
defaultMode: 0600
name: filebeat-inputs
# data folder stores a registry of read status for all files, so we don't send everything again on a Filebeat pod restart
- name: data
hostPath:
path: /var/lib/filebeat-data
type: DirectoryOrCreate
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRoleBinding
metadata:
name: filebeat
subjects:
- kind: ServiceAccount
name: filebeat
namespace: loging
roleRef:
kind: ClusterRole
name: filebeat
apiGroup: rbac.authorization.k8s.io
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRole
metadata:
name: filebeat
labels:
app: filebeat
rules:
- apiGroups: [""] # "" indicates the core API group
resources:
- namespaces
- pods
verbs:
- get
- watch
- list
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: filebeat
namespace: loging
labels:
app: filebeat
---
至此完成在k8s上部署es+lo+fi+ki ，进行简单验证。
验证
查看svc、pod、ingress信息
# kubectl get svc,pods,ingress -n loging
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/elasticsearch ClusterIP None <none> 9200/TCP,9300/TCP 151m
service/kibana ClusterIP xxx.168.239.2xx <none> 5601/TCP 20h
service/logstash ClusterIP xxx.168.38.1xx <none> 8080/TCP 122m
NAME READY STATUS RESTARTS AGE
pod/elasticsearch-0 1/1 Running 0 151m
pod/filebeat-24zl7 1/1 Running 0 118m
pod/filebeat-4w7b6 1/1 Running 0 118m
pod/filebeat-m5kv4 1/1 Running 0 118m
pod/filebeat-t6x4t 1/1 Running 0 118m
pod/kibana-689f4bd647-7jrqd 1/1 Running 0 20h
pod/logstash-76bc9b5f95-qtngp 1/1 Running 0 122m
NAME HOSTS ADDRESS PORTS AGE
ingress.extensions/kibana kibana.test.realibox.com xxx.xx.xx.xxx 80, 443 19h
web配置
配置索引
发现
至此算是简单完成。后续需要不断优化，不过那是后事了。
问题总结
这应该算是第一次亲自在测试&生产环境部署应用了，而且是自己很不熟悉的日子系统，遇到了很多问题，需要总结。
- 如何调研一项技术栈；
- 如何选定方案；
- 因为网上几乎没有找到类似的方案(也不晓得别的公司是怎么搞的，反正网上找不到有效的可能借鉴的)。需要自己根据不同的文档总结尝试；
- 一个组件的标签尽可能一致；
- 如何查看公司是否做了端口限制和https强制转换；
- 遇到IT的事一定要看日志，这点很重要，日志可以解决绝大多数问题；
- 一个人再怎么整也会忽略一些点，自己先尝试然后请教朋友，共同进步。
- 项目先上线再说别的，目前是这样，一件事又百分之20的把握就可以去做了。百分之80再去做就没啥意思了。
- 自学重点学的是理论，公司才能学到操作。
标签：filebeat,name,app,elfk,kibana,日志,k8s,logstash,metadata 来源： https://www.cnblogs.com/zisefeizhu/p/13084635.html