K8s上搭建 EFK 日志收集系统
文章目录创建命名空间创建es集群部署Fluentd创建Kibana用于验证日志采集的pod在CentOS主机上安装fluentd并收集java的日志说明: k8s集群已支持nfs做es数据存储创建命名空间ns.yamlapiVersion: v1kind: Namespacemetadata:name: efk创建es集群es.yamlkind: ServiceapiVersion: v1meta
·
说明: k8s集群已支持nfs做es数据存储
创建命名空间
- ns.yaml
apiVersion: v1
kind: Namespace
metadata:
name: efk
创建es集群
- es.yaml
kind: Service
apiVersion: v1
metadata:
name: elasticsearch
namespace: efk
labels:
app: elasticsearch
spec:
selector:
app: elasticsearch
clusterIP: None
ports:
- port: 9200
name: rest
- port: 9300
name: inter-node
---
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: es
namespace: efk
spec:
serviceName: elasticsearch
replicas: 3
selector:
matchLabels:
app: elasticsearch
template:
metadata:
labels:
app: elasticsearch
spec:
initContainers:
- 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
containers:
- name: elasticsearch
image: docker.elastic.co/elasticsearch/elasticsearch:7.6.2
ports:
- name: rest
containerPort: 9200
- name: inter
containerPort: 9300
resources:
limits:
cpu: 1000m
requests:
cpu: 1000m
volumeMounts:
- name: data
mountPath: /usr/share/elasticsearch/data
env:
- name: cluster.name
value: k8s-logs
- name: node.name
valueFrom:
fieldRef:
fieldPath: metadata.name
- name: cluster.initial_master_nodes
value: "es-0,es-1,es-2"
- name: discovery.zen.minimum_master_nodes
value: "2"
- name: discovery.seed_hosts
value: "elasticsearch"
- name: ES_JAVA_OPTS
value: "-Xms512m -Xmx512m"
- name: network.host
value: "0.0.0.0"
volumeClaimTemplates:
- metadata:
name: data
labels:
app: elasticsearch
spec:
accessModes: [ "ReadWriteOnce" ]
storageClassName: nfs-storage
resources:
requests:
storage: 50Gi
部署Fluentd
- fluentd-daemonset.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
name: fluentd-es
namespace: efk
labels:
k8s-app: fluentd-es
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
---
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
metadata:
name: fluentd-es
labels:
k8s-app: fluentd-es
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups:
- ""
resources:
- "namespaces"
- "pods"
verbs:
- "get"
- "watch"
- "list"
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
name: fluentd-es
labels:
k8s-app: fluentd-es
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
subjects:
- kind: ServiceAccount
name: fluentd-es
namespace: efk
apiGroup: ""
roleRef:
kind: ClusterRole
name: fluentd-es
apiGroup: ""
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
name: fluentd-es
namespace: efk
labels:
k8s-app: fluentd-es
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
spec:
selector:
matchLabels:
k8s-app: fluentd-es
template:
metadata:
labels:
k8s-app: fluentd-es
kubernetes.io/cluster-service: "true"
# 此注释确保如果节点被驱逐,fluentd不会被驱逐,支持关键的基于 pod 注释的优先级方案。
annotations:
scheduler.alpha.kubernetes.io/critical-pod: ''
spec:
serviceAccountName: fluentd-es
containers:
- name: fluentd-es
image: quay.io/fluentd_elasticsearch/fluentd:v3.0.1
env:
- name: FLUENTD_ARGS
value: --no-supervisor -q
resources:
limits:
memory: 500Mi
requests:
cpu: 100m
memory: 200Mi
volumeMounts:
- name: varlog
mountPath: /var/log
- name: varlibdockercontainers
mountPath: /data/docker/containers ##docker 的根目录/data/docker
readOnly: true
- name: config-volume
mountPath: /etc/fluent/config.d
tolerations:
- operator: Exists
terminationGracePeriodSeconds: 30
volumes:
- name: varlog
hostPath:
path: /var/log
- name: varlibdockercontainers
hostPath:
path: /data/docker/containers ##docker 的根目录/data/docker
- name: config-volume
configMap:
name: fluentd-config
- fluentd-configmap.yaml
kind: ConfigMap
apiVersion: v1
metadata:
name: fluentd-config
namespace: efk
data:
system.conf: |-
<system>
root_dir /tmp/fluentd-buffers/
</system>
containers.input.conf: |-
<source>
@id fluentd-containers.log
@type tail # Fluentd 内置的输入方式,其原理是不停地从源文件中获取新的日志。
path /var/log/containers/*.log # 挂载的服务器Docker容器日志地址
pos_file /var/log/es-containers.log.pos
tag raw.kubernetes.* # 设置日志标签
read_from_head true
<parse> # 多行格式化成JSON
@type multi_format # 使用 multi-format-parser 解析器插件
<pattern>
format json # JSON解析器
time_key time # 指定事件时间的时间字段
time_format %Y-%m-%dT%H:%M:%S.%NZ # 时间格式
</pattern>
<pattern>
format /^(?<time>.+) (?<stream>stdout|stderr) [^ ]* (?<log>.*)$/
time_format %Y-%m-%dT%H:%M:%S.%N%:z
</pattern>
</parse>
</source>
# 在日志输出中检测异常,并将其作为一条日志转发
# https://github.com/GoogleCloudPlatform/fluent-plugin-detect-exceptions
<match raw.kubernetes.**> # 匹配tag为raw.kubernetes.**日志信息
@id raw.kubernetes
@type detect_exceptions # 使用detect-exceptions插件处理异常栈信息
remove_tag_prefix raw # 移除 raw 前缀
message log
stream stream
multiline_flush_interval 5
max_bytes 500000
max_lines 1000
</match>
<filter **> # 拼接日志
@id filter_concat
@type concat # Fluentd Filter 插件,用于连接多个事件中分隔的多行日志。
key message
multiline_end_regexp /\n$/ # 以换行符“\n”拼接
separator ""
</filter>
# 添加 Kubernetes metadata 数据
<filter kubernetes.**>
@id filter_kubernetes_metadata
@type kubernetes_metadata
</filter>
# 修复 ES 中的 JSON 字段
# 插件地址:https://github.com/repeatedly/fluent-plugin-multi-format-parser
<filter kubernetes.**>
@id filter_parser
@type parser # multi-format-parser多格式解析器插件
key_name log # 在要解析的记录中指定字段名称。
reserve_data true # 在解析结果中保留原始键值对。
remove_key_name_field true # key_name 解析成功后删除字段。
<parse>
@type multi_format
<pattern>
format json
</pattern>
<pattern>
format none
</pattern>
</parse>
</filter>
# 删除一些多余的属性
<filter kubernetes.**>
@type record_transformer
remove_keys $.docker.container_id,$.kubernetes.container_image_id,$.kubernetes.pod_id,$.kubernetes.namespace_id,$.kubernetes.master_url,$.kubernetes.labels.pod-template-hash
</filter>
# 只保留具有logging=true标签的Pod日志
<filter kubernetes.**>
@id filter_log
@type grep
<regexp>
key $.kubernetes.labels.logging
pattern ^true$
</regexp>
</filter>
###### 监听配置,一般用于日志聚合用 ######
forward.input.conf: |-
# 监听通过TCP发送的消息
<source>
@id forward
@type forward
</source>
output.conf: |-
<match **>
@id elasticsearch
@type elasticsearch
@log_level info
include_tag_key true
host elasticsearch
port 9200
logstash_format true
logstash_prefix k8s # 设置 index 前缀为 k8s
request_timeout 30s
<buffer>
@type file
path /var/log/fluentd-buffers/kubernetes.system.buffer
flush_mode interval
retry_type exponential_backoff
flush_thread_count 2
flush_interval 5s
retry_forever
retry_max_interval 30
chunk_limit_size 2M
queue_limit_length 8
overflow_action block
</buffer>
</match>
创建Kibana
- kibana.yaml
apiVersion: v1
kind: Service
metadata:
name: kibana
namespace: efk
labels:
app: kibana
spec:
ports:
- port: 5601
nodePort: 30001
type: NodePort
selector:
app: kibana
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: kibana
namespace: efk
labels:
app: kibana
spec:
selector:
matchLabels:
app: kibana
template:
metadata:
labels:
app: kibana
spec:
containers:
- name: kibana
image: docker.elastic.co/kibana/kibana:7.6.2
resources:
limits:
cpu: 1000m
requests:
cpu: 1000m
env:
- name: ELASTICSEARCH_HOSTS
value: http://elasticsearch:9200
ports:
- containerPort: 5601
用于验证日志采集的pod
- pod.yaml
apiVersion: v1
kind: Pod
metadata:
name: test-log
labels:
logging: "true" # 一定要具有该标签才会被采集
spec:
containers:
- name: count
image: busybox
args: [/bin/sh, -c,
'i=0; while true; do echo "$i: $(date)"; i=$((i+1)); sleep 1; done']
在CentOS主机上安装fluentd 并收集java的日志
- 安装fluentd并启动
curl -L https://toolbelt.treasuredata.com/sh/install-redhat-td-agent4.sh | sh
systemctl start td-agent.service
systemctl enable td-agent.service
- 日志采集配置/etc/td-agent/td-agent.conf
#日志采集并格式化
<source>
@type tail
path /data/onboard/logs/DataOnBoard_*.log
pos_file /var/log/td-agent/td-agent.log.pos
read_from_head true
tag onboard-ecs-log
<parse>
@type multiline
format_firstline /\d{4}-\d{1,2}-\d{1,2}/
format1 /^(?<time>\d{4}-\d{1,2}-\d{1,2} \d{1,2}:\d{1,2}:\d{1,2}) \[(?<thread>.*)\] (?<level>[^\s]+)(?<message>.*)/
</parse>
</source>
<filter onboard-ecs-log>
@type record_transformer
remove_keys _id
<record>
tag ${tag}
hostname "#{Socket.gethostname}"
</record>
</filter>
<filter onboard-ecs-log>
@type grep #排除掉一些不需要的日志
<exclude>
key message
pattern /.*healthcheck.*|.*prometheusMetrics.*|.*(v1+\/)+(configurations)+(\/+versions).*/
</exclude>
</filter>
### ToES
<match onboard**>
@id elasticsearch
@type elasticsearch
@log_level info
include_tag_key true
host 10.127.40.227
port 9200
logstash_format true
logstash_prefix onboard # 设置 index 前缀为 k8s
request_timeout 30s
<buffer>
@type file
path /tmp/fluentd-buffers/kubernetes.system.buffer
flush_mode interval
retry_type exponential_backoff
flush_thread_count 2
flush_interval 5s
retry_forever
retry_max_interval 30
chunk_limit_size 2M
queue_limit_length 8
overflow_action block
</buffer>
</match>
更多推荐
已为社区贡献13条内容
所有评论(0)