七, 跨语言微服务框架 - Istio日志采集EFK

ELK日志系统你们不会陌生(zipkin + jaeger , prometheus + grafana)解决了你们对于链路对于统计采集的需求,可是真正的对于日志进行存储仍是得专业的上,在Istio中官方提供的方案是EFK(Fluentd + Elasticsearch + Kibana)Fluentd 是一个开源的日志收集器，支持多种数据输出而且有一个可插拔架构。 Elasticsearch是一个流行的后端日志记录程序， Kibana 用于查看。

附上:

喵了个咪的博客:w-blog.cn

Istio官方地址:https://preliminary.istio.io/zh

Istio中文文档:https://preliminary.istio.io/zh/docs/

PS : 此处基于当前最新istio版本1.0.3版本进行搭建和演示

一. 准备环境

咱们把Fluentd，Elasticsearch 和 Kibana 在一个非生产集合 Services 和 Deployments 在一个新的叫作logging的 Namespace 中。

> vim logging-stack.yaml

# Logging Namespace. All below are a part of this namespace.
apiVersion: v1
kind: Namespace
metadata:
  name: logging
---
# Elasticsearch Service
apiVersion: v1
kind: Service
metadata:
  name: elasticsearch
  namespace: logging
  labels:
    app: elasticsearch
spec:
  ports:
  - port: 9200
    protocol: TCP
    targetPort: db
  selector:
    app: elasticsearch
---
# Elasticsearch Deployment
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: elasticsearch
  namespace: logging
  labels:
    app: elasticsearch
  annotations:
    sidecar.istio.io/inject: "false"
spec:
  template:
    metadata:
      labels:
        app: elasticsearch
    spec:
      containers:
      - image: docker.elastic.co/elasticsearch/elasticsearch-oss:6.1.1
        name: elasticsearch
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        env:
          - name: discovery.type
            value: single-node
        ports:
        - containerPort: 9200
          name: db
          protocol: TCP
        - containerPort: 9300
          name: transport
          protocol: TCP
        volumeMounts:
        - name: elasticsearch
          mountPath: /data
      volumes:
      - name: elasticsearch
        emptyDir: {}
---
# Fluentd Service
apiVersion: v1
kind: Service
metadata:
  name: fluentd-es
  namespace: logging
  labels:
    app: fluentd-es
spec:
  ports:
  - name: fluentd-tcp
    port: 24224
    protocol: TCP
    targetPort: 24224
  - name: fluentd-udp
    port: 24224
    protocol: UDP
    targetPort: 24224
  selector:
    app: fluentd-es
---
# Fluentd Deployment
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: fluentd-es
  namespace: logging
  labels:
    app: fluentd-es
  annotations:
    sidecar.istio.io/inject: "false"
spec:
  template:
    metadata:
      labels:
        app: fluentd-es
    spec:
      containers:
      - name: fluentd-es
        image: gcr.io/google-containers/fluentd-elasticsearch:v2.0.1
        env:
        - name: FLUENTD_ARGS
          value: --no-supervisor -q
        resources:
          limits:
            memory: 500Mi
          requests:
            cpu: 100m
            memory: 200Mi
        volumeMounts:
        - name: config-volume
          mountPath: /etc/fluent/config.d
      terminationGracePeriodSeconds: 30
      volumes:
      - name: config-volume
        configMap:
          name: fluentd-es-config
---
# Fluentd ConfigMap, contains config files.
kind: ConfigMap
apiVersion: v1
data:
  forward.input.conf: |-
    # Takes the messages sent over TCP
    <source>
      type forward
    </source>
  output.conf: |-
    <match **>
       type elasticsearch
       log_level info
       include_tag_key true
       host elasticsearch
       port 9200
       logstash_format true
       # Set the chunk limits.
       buffer_chunk_limit 2M
       buffer_queue_limit 8
       flush_interval 5s
       # Never wait longer than 5 minutes between retries.
       max_retry_wait 30
       # Disable the limit on the number of retries (retry forever).
       disable_retry_limit
       # Use multiple threads for processing.
       num_threads 2
    </match>
metadata:
  name: fluentd-es-config
  namespace: logging
---
# Kibana Service
apiVersion: v1
kind: Service
metadata:
  name: kibana
  namespace: logging
  labels:
    app: kibana
spec:
  ports:
  - port: 5601
    protocol: TCP
    targetPort: ui
  selector:
    app: kibana
---
# Kibana Deployment
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: kibana
  namespace: logging
  labels:
    app: kibana
  annotations:
    sidecar.istio.io/inject: "false"
spec:
  template:
    metadata:
      labels:
        app: kibana
    spec:
      containers:
      - name: kibana
        image: docker.elastic.co/kibana/kibana-oss:6.1.1
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        env:
          - name: ELASTICSEARCH_URL
            value: http://elasticsearch:9200
        ports:
        - containerPort: 5601
          name: ui
          protocol: TCP
---

建立资源

kubectl apply -f logging-stack.yaml

二, 配置Istio

如今有一个正在运行的 Fluentd 守护进程，使用新的日志类型配置 Istio，并将这些日志发送到监听守护进程。

建立一个新的 YAML 文件来保存日志流的配置，Istio 将自动生成并收集。

> vim fluentd-istio.yaml
apiVersion: "config.istio.io/v1alpha2"
kind: logentry
metadata:
  name: newlog
  namespace: istio-system
spec:
  severity: '"info"'
  timestamp: request.time
  variables:
    source: source.labels["app"] | source.workload.name | "unknown"
    user: source.user | "unknown"
    destination: destination.labels["app"] | destination.workload.name | "unknown"
    responseCode: response.code | 0
    responseSize: response.size | 0
    latency: response.duration | "0ms"
  monitored_resource_type: '"UNSPECIFIED"'
---
# fluentd handler 的配置
apiVersion: "config.istio.io/v1alpha2"
kind: fluentd
metadata:
  name: handler
  namespace: istio-system
spec:
  address: "fluentd-es.logging:24224"
---
# 发送 logentry 实例到 fluentd handler 的规则
apiVersion: "config.istio.io/v1alpha2"
kind: rule
metadata:
  name: newlogtofluentd
  namespace: istio-system
spec:
  match: "true" # match for all requests
  actions:
   - handler: handler.fluentd
     instances:
     - newlog.logentry
---

PS : 处理程序配置中 address: "fluentd-es.logging:24224" 行指向咱们设置的 Fluentd 守护进程示例软件栈。

使其生效

kubectl apply -f fluentd-istio.yaml

三, 查看采集的日志

咱们先访问如下咱们的示例程序bookinfo,而后老方式经过端口映射访问kibana

kubectl -n logging port-forward $(kubectl -n logging get pod -l app=kibana -o jsonpath='{.items[0].metadata.name}') 5601:5601

PS : 推荐吧ES和kibana单独部署在集群外部,ES对存储和资源有较高要求