在k8s上部署日志系统elfk

2024-02-28 11:47:34

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

在k8s上部署日志系统elfk

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k8s上部署日志系统elfk

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
在k8s上部署日志系统elfk
在k8s上部署日志系统elfk
发现
在k8s上部署日志系统elfk
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。

  1. 如何调研一项技术栈；
  2. 如何选定方案；
  3. 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；
  4. 一个组件的标签尽可能一致；
  5. 如何查看公司是否做了端口限制和https强制转换；
  6. 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；
  7. 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。
  8. 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。
  9. 自学重点学的是理论，公司才能学到操作。
上一篇：Pandas库----TCGA metadata.json处理


下一篇：深入剖析Kubernetes学习笔记：Pod基本概念进阶（15）