Kubernetes集群EFK日志框架部署
目标：在现有Kubernetes集群中搭建EFK日志框架，实现集群日志的存储与展示
环境：Kubernetes集群(kubeadm方式部署)
步骤：Kubernetes日志架构概述 -> Fluentd日志收集容器部署 -> Elasticsearch日志存储容器部署 -> Kibana日志展示容器部署
Kubernetes日志架构概述
在Kubernetes集群中，Cluster-Level Logging架构为集中查看并分析集群资源及服务日志的官方解决方案：
该方案采用Node Logging Agent的方式，通过在集群每个节点上部署一个Agent代理Pod服务，收集该Node上的日志并push到后端。Agent应具备进入该节点上所有服务容器日志目录的权限。
具体在EFK方案中，logging-agent使用Fluentd，logging backend使用Elasticsearch，另为方便展示，使用kibana获取并展示es数据库数据。
Fluentd日志收集容器部署
Fluentd日志收集容器以DaemonSet的形式运行在Kubernetes集群中，保证集群中每个Node都会启动一个Fluentd。
在Master节点创建fluentd服务，最终会在所有Node节点上运行。
以下所有配置文件参考：https://github.com/kubernetes/kubernetes/tree/master/cluster/addons/fluentd-elasticsearch
配置映射文件 - fluentd-es-configmap.yaml
[root@k8s-master ~]# kubectl create -f fluentd-es-configmap.yaml
configmap/fluentd-es-config-v0.2.0 createdkind: ConfigMap
apiVersion: v1
metadata:
name: fluentd-es-config-v0.2.0
namespace: kube-system
labels:
addonmanager.kubernetes.io/mode: Reconcile
data:
system.conf: |-
<system>
root_dir /tmp/fluentd-buffers/
</system>
containers.input.conf: |-
# This configuration file for Fluentd / td-agent is used
# to watch changes to Docker log files. The kubelet creates symlinks that
# capture the pod name, namespace, container name & Docker container ID
# to the docker logs for pods in the /var/log/containers directory on the host.
# If running this fluentd configuration in a Docker container, the /var/log
# directory should be mounted in the container.
#
# These logs are then submitted to Elasticsearch which assumes the
# installation of the fluent-plugin-elasticsearch & the
# fluent-plugin-kubernetes_metadata_filter plugins.
# See https://github.com/uken/fluent-plugin-elasticsearch &
# https://github.com/fabric8io/fluent-plugin-kubernetes_metadata_filter for
# more information about the plugins.
#
# Example
# =======
# A line in the Docker log file might look like this JSON:
#
# {"log":"2014/09/25 21:15:03 Got request with path wombat\n",
# "stream":"stderr",
# "time":"2014-09-25T21:15:03.499185026Z"}
#
# The time_format specification below makes sure we properly
# parse the time format produced by Docker. This will be
# submitted to Elasticsearch and should appear like:
# $ curl 'http://elasticsearch-logging:9200/_search?pretty'
# ...
# {
# "_index" : "logstash-2014.09.25",
# "_type" : "fluentd",
# "_id" : "VBrbor2QTuGpsQyTCdfzqA",
# "_score" : 1.0,
# "_source":{"log":"2014/09/25 22:45:50 Got request with path wombat\n",
# "stream":"stderr","tag":"docker.container.all",
# "@timestamp":"2014-09-25T22:45:50+00:00"}
# },
# ...
#
# The Kubernetes fluentd plugin is used to write the Kubernetes metadata to the log
# record & add labels to the log record if properly configured. This enables users
# to filter & search logs on any metadata.
# For example a Docker container's logs might be in the directory:
#
# /var/lib/docker/containers/997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b
#
# and in the file:
#
# 997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b-json.log
#
# where 997599971ee6... is the Docker ID of the running container.
# The Kubernetes kubelet makes a symbolic link to this file on the host machine
# in the /var/log/containers directory which includes the pod name and the Kubernetes
# container name:
#
# synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
# ->
# /var/lib/docker/containers/997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b/997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b-json.log
#
# The /var/log directory on the host is mapped to the /var/log directory in the container
# running this instance of Fluentd and we end up collecting the file:
#
# /var/log/containers/synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
#
# This results in the tag:
#
# var.log.containers.synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
#
# The Kubernetes fluentd plugin is used to extract the namespace, pod name & container name
# which are added to the log message as a kubernetes field object & the Docker container ID
# is also added under the docker field object.
# The final tag is:
#
# kubernetes.var.log.containers.synthetic-logger-0.25lps-pod_default_synth-lgr-997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b.log
#
# And the final log record look like:
#
# {
# "log":"2014/09/25 21:15:03 Got request with path wombat\n",
# "stream":"stderr",
# "time":"2014-09-25T21:15:03.499185026Z",
# "kubernetes": {
# "namespace": "default",
# "pod_name": "synthetic-logger-0.25lps-pod",
# "container_name": "synth-lgr"
# },
# "docker": {
# "container_id": "997599971ee6366d4a5920d25b79286ad45ff37a74494f262e3bc98d909d0a7b"
# }
# }
#
# This makes it easier for users to search for logs by pod name or by
# the name of the Kubernetes container regardless of how many times the
# Kubernetes pod has been restarted (resulting in a several Docker container IDs).
# Json Log Example:
# {"log":"[info:2016-02-16T16:04:05.930-08:00] Some log text here\n","stream":"stdout","time":"2016-02-17T00:04:05.931087621Z"}
# CRI Log Example:
# 2016-02-17T00:04:05.931087621Z stdout F [info:2016-02-16T16:04:05.930-08:00] Some log text here
<source>
@id fluentd-containers.log
@type tail
path /var/log/containers/*.log
pos_file /var/log/es-containers.log.pos
tag raw.kubernetes.*
read_from_head true
<parse>
@type multi_format
<pattern>
format json
time_key time
time_format %Y-%m-%dT%H:%M:%S.%NZ
</pattern>
<pattern>
format /^(?<time>.+) (?<stream>stdout|stderr) [^ ]* (?<log>.*)$/
time_format %Y-%m-%dT%H:%M:%S.%N%:z
</pattern>
</parse>
</source>
# Detect exceptions in the log output and forward them as one log entry.
<match raw.kubernetes.**>
@id raw.kubernetes
@type detect_exceptions
remove_tag_prefix raw
message log
stream stream
multiline_flush_interval 5
max_bytes 500000
max_lines 1000
</match>
# Concatenate multi-line logs
<filter **>
@id filter_concat
@type concat
key message
multiline_end_regexp /\n$/
separator ""
</filter>
# Enriches records with Kubernetes metadata
<filter kubernetes.**>
@id filter_kubernetes_metadata
@type kubernetes_metadata
</filter>
# Fixes json fields in Elasticsearch
<filter kubernetes.**>
@id filter_parser
@type parser
key_name log
reserve_data true
remove_key_name_field true
<parse>
@type multi_format
<pattern>
format json
</pattern>
<pattern>
format none
</pattern>
</parse>
</filter>
system.input.conf: |-
# Example:
# 2015-12-21 23:17:22,066 [salt.state ][INFO ] Completed state [net.ipv4.ip_forward] at time 23:17:22.066081
<source>
@id minion
@type tail
format /^(?<time>[^ ]* [^ ,]*)[^\[]*\[[^\]]*\]\[(?<severity>[^ \]]*) *\] (?<message>.*)$/
time_format %Y-%m-%d %H:%M:%S
path /var/log/salt/minion
pos_file /var/log/salt.pos
tag salt
</source>
# Example:
# Dec 21 23:17:22 gke-foo-1-1-4b5cbd14-node-4eoj startupscript: Finished running startup script /var/run/google.startup.script
<source>
@id startupscript.log
@type tail
format syslog
path /var/log/startupscript.log
pos_file /var/log/es-startupscript.log.pos
tag startupscript
</source>
# Examples:
# time="2016-02-04T06:51:03.053580605Z" level=info msg="GET /containers/json"
# time="2016-02-04T07:53:57.505612354Z" level=error msg="HTTP Error" err="No such image: -f" statusCode=404
# TODO(random-liu): Remove this after cri container runtime rolls out.
<source>
@id docker.log
@type tail
format /^time="(?<time>[^)]*)" level=(?<severity>[^ ]*) msg="(?<message>[^"]*)"( err="(?<error>[^"]*)")?( statusCode=($<status_code>\d+))?/
path /var/log/docker.log
pos_file /var/log/es-docker.log.pos
tag docker
</source>
# Example:
# 2016/02/04 06:52:38 filePurge: successfully removed file /var/etcd/data/member/wal/00000000000006d0-00000000010a23d1.wal
<source>
@id etcd.log
@type tail
# Not parsing this, because it doesn't have anything particularly useful to
# parse out of it (like severities).
format none
path /var/log/etcd.log
pos_file /var/log/es-etcd.log.pos
tag etcd
</source>
# Multi-line parsing is required for all the kube logs because very large log
# statements, such as those that include entire object bodies, get split into
# multiple lines by glog.
# Example:
# I0204 07:32:30.020537 3368 server.go:1048] POST /stats/container/: (13.972191ms) 200 [[Go-http-client/1.1] 10.244.1.3:40537]
<source>
@id kubelet.log
@type tail
format multiline
multiline_flush_interval 5s
format_firstline /^\w\d{4}/
format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
time_format %m%d %H:%M:%S.%N
path /var/log/kubelet.log
pos_file /var/log/es-kubelet.log.pos
tag kubelet
</source>
# Example:
# I1118 21:26:53.975789 6 proxier.go:1096] Port "nodePort for kube-system/default-http-backend:http" (:31429/tcp) was open before and is still needed
<source>
@id kube-proxy.log
@type tail
format multiline
multiline_flush_interval 5s
format_firstline /^\w\d{4}/
format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
time_format %m%d %H:%M:%S.%N
path /var/log/kube-proxy.log
pos_file /var/log/es-kube-proxy.log.pos
tag kube-proxy
</source>
# Example:
# I0204 07:00:19.604280 5 handlers.go:131] GET /api/v1/nodes: (1.624207ms) 200 [[kube-controller-manager/v1.1.3 (linux/amd64) kubernetes/6a81b50] 127.0.0.1:38266]
<source>
@id kube-apiserver.log
@type tail
format multiline
multiline_flush_interval 5s
format_firstline /^\w\d{4}/
format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
time_format %m%d %H:%M:%S.%N
path /var/log/kube-apiserver.log
pos_file /var/log/es-kube-apiserver.log.pos
tag kube-apiserver
</source>
# Example:
# I0204 06:55:31.872680 5 servicecontroller.go:277] LB already exists and doesn't need update for service kube-system/kube-ui
<source>
@id kube-controller-manager.log
@type tail
format multiline
multiline_flush_interval 5s
format_firstline /^\w\d{4}/
format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
time_format %m%d %H:%M:%S.%N
path /var/log/kube-controller-manager.log
pos_file /var/log/es-kube-controller-manager.log.pos
tag kube-controller-manager
</source>
# Example:
# W0204 06:49:18.239674 7 reflector.go:245] pkg/scheduler/factory/factory.go:193: watch of *api.Service ended with: 401: The event in requested index is outdated and cleared (the requested history has been cleared [2578313/2577886]) [2579312]
<source>
@id kube-scheduler.log
@type tail
format multiline
multiline_flush_interval 5s
format_firstline /^\w\d{4}/
format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
time_format %m%d %H:%M:%S.%N
path /var/log/kube-scheduler.log
pos_file /var/log/es-kube-scheduler.log.pos
tag kube-scheduler
</source>
# Example:
# I0603 15:31:05.793605 6 cluster_manager.go:230] Reading config from path /etc/gce.conf
<source>
@id glbc.log
@type tail
format multiline
multiline_flush_interval 5s
format_firstline /^\w\d{4}/
format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
time_format %m%d %H:%M:%S.%N
path /var/log/glbc.log
pos_file /var/log/es-glbc.log.pos
tag glbc
</source>
# Example:
# I0603 15:31:05.793605 6 cluster_manager.go:230] Reading config from path /etc/gce.conf
<source>
@id cluster-autoscaler.log
@type tail
format multiline
multiline_flush_interval 5s
format_firstline /^\w\d{4}/
format1 /^(?<severity>\w)(?<time>\d{4} [^\s]*)\s+(?<pid>\d+)\s+(?<source>[^ \]]+)\] (?<message>.*)/
time_format %m%d %H:%M:%S.%N
path /var/log/cluster-autoscaler.log
pos_file /var/log/es-cluster-autoscaler.log.pos
tag cluster-autoscaler
</source>
# Logs from systemd-journal for interesting services.
# TODO(random-liu): Remove this after cri container runtime rolls out.
<source>
@id journald-docker
@type systemd
matches [{ "_SYSTEMD_UNIT": "docker.service" }]
<storage>
@type local
persistent true
path /var/log/journald-docker.pos
</storage>
read_from_head true
tag docker
</source>
<source>
@id journald-container-runtime
@type systemd
matches [{ "_SYSTEMD_UNIT": "{{ fluentd_container_runtime_service }}.service" }]
<storage>
@type local
persistent true
path /var/log/journald-container-runtime.pos
</storage>
read_from_head true
tag container-runtime
</source>
<source>
@id journald-kubelet
@type systemd
matches [{ "_SYSTEMD_UNIT": "kubelet.service" }]
<storage>
@type local
persistent true
path /var/log/journald-kubelet.pos
</storage>
read_from_head true
tag kubelet
</source>
<source>
@id journald-node-problem-detector
@type systemd
matches [{ "_SYSTEMD_UNIT": "node-problem-detector.service" }]
<storage>
@type local
persistent true
path /var/log/journald-node-problem-detector.pos
</storage>
read_from_head true
tag node-problem-detector
</source>
<source>
@id kernel
@type systemd
matches [{ "_TRANSPORT": "kernel" }]
<storage>
@type local
persistent true
path /var/log/kernel.pos
</storage>
<entry>
fields_strip_underscores true
fields_lowercase true
</entry>
read_from_head true
tag kernel
</source>
forward.input.conf: |-
# Takes the messages sent over TCP
<source>
@id forward
@type forward
</source>
monitoring.conf: |-
# Prometheus Exporter Plugin
# input plugin that exports metrics
<source>
@id prometheus
@type prometheus
</source>
<source>
@id monitor_agent
@type monitor_agent
</source>
# input plugin that collects metrics from MonitorAgent
<source>
@id prometheus_monitor
@type prometheus_monitor
<labels>
host ${hostname}
</labels>
</source>
# input plugin that collects metrics for output plugin
<source>
@id prometheus_output_monitor
@type prometheus_output_monitor
<labels>
host ${hostname}
</labels>
</source>
# input plugin that collects metrics for in_tail plugin
<source>
@id prometheus_tail_monitor
@type prometheus_tail_monitor
<labels>
host ${hostname}
</labels>
</source>
output.conf: |-
<match **>
@id elasticsearch
@type elasticsearch
@log_level info
type_name _doc
include_tag_key true
host elasticsearch-logging
port 9200
logstash_format true
<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>部署及服务文件 - fluentd-es-ds.yaml
[root@k8s-master ~]# kubectl create -f fluentd-es-ds.yaml
serviceaccount/fluentd-es created
clusterrole.rbac.authorization.k8s.io/fluentd-es created
clusterrolebinding.rbac.authorization.k8s.io/fluentd-es created
daemonset.apps/fluentd-es-v2.5.2 created[root@k8s-master ~]# kubectl get pods -n kube-system | grep fluentd
fluentd-es-v2.5.2-4wvj7 1/1 Running 0 10h
fluentd-es-v2.5.2-5vv8t 1/1 Running 0 10h
fluentd-es-v2.5.2-bxwmg 1/1 Running 0 10h
fluentd-es-v2.5.2-f2b2n 1/1 Running 0 10h
fluentd-es-v2.5.2-flm47 1/1 Running 0 10hapiVersion: v1
kind: ServiceAccount
metadata:
name: fluentd-es
namespace: kube-system
labels:
k8s-app: fluentd-es
addonmanager.kubernetes.io/mode: Reconcile
---
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
metadata:
name: fluentd-es
labels:
k8s-app: fluentd-es
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
addonmanager.kubernetes.io/mode: Reconcile
subjects:
- kind: ServiceAccount
name: fluentd-es
namespace: kube-system
apiGroup: ""
roleRef:
kind: ClusterRole
name: fluentd-es
apiGroup: ""
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
name: fluentd-es-v2.5.2
namespace: kube-system
labels:
k8s-app: fluentd-es
version: v2.5.2
addonmanager.kubernetes.io/mode: Reconcile
spec:
selector:
matchLabels:
k8s-app: fluentd-es
version: v2.5.2
template:
metadata:
labels:
k8s-app: fluentd-es
version: v2.5.2
# This annotation ensures that fluentd does not get evicted if the node
# supports critical pod annotation based priority scheme.
# Note that this does not guarantee admission on the nodes (#40573).
annotations:
scheduler.alpha.kubernetes.io/critical-pod: ''
seccomp.security.alpha.kubernetes.io/pod: 'docker/default'
spec:
priorityClassName: system-node-critical
serviceAccountName: fluentd-es
containers:
- name: fluentd-es
image: gcr.io/fluentd-elasticsearch/fluentd:v2.5.2
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: /var/lib/docker/containers
readOnly: true
- name: config-volume
mountPath: /etc/fluent/config.d
terminationGracePeriodSeconds: 30
volumes:
- name: varlog
hostPath:
path: /var/log
- name: varlibdockercontainers
hostPath:
path: /var/lib/docker/containers
- name: config-volume
configMap:
name: fluentd-es-config-v0.2.0Elasticsearch日志存储容器部署
Elasticsearch的主要作用是将日志信息进行分割，建立索引。
node环境配置
将max_map_count值设置为655360，防止该值低于es运行所需，导致es无法正常运行，sysctl -p应用
# vim /etc/sysctl.conf
vm.max_map_count=65536
# sysctl -pes部署文件与服务文件
[root@k8s-master ~]# kubectl create -f es-statefulset.yaml
serviceaccount/elasticsearch-logging created
clusterrole.rbac.authorization.k8s.io/elasticsearch-logging created
clusterrolebinding.rbac.authorization.k8s.io/elasticsearch-logging created
statefulset.apps/elasticsearch-logging created
[root@k8s-master ~]# kubectl create -f es-service.yaml
service/elasticsearch-logging createdes-statefulset.yaml
# RBAC authn and authz
apiVersion: v1
kind: ServiceAccount
metadata:
name: elasticsearch-logging
namespace: kube-system
labels:
k8s-app: elasticsearch-logging
addonmanager.kubernetes.io/mode: Reconcile
---
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
metadata:
name: elasticsearch-logging
labels:
k8s-app: elasticsearch-logging
addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups:
- ""
resources:
- "services"
- "namespaces"
- "endpoints"
verbs:
- "get"
---
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1
metadata:
namespace: kube-system
name: elasticsearch-logging
labels:
k8s-app: elasticsearch-logging
addonmanager.kubernetes.io/mode: Reconcile
subjects:
- kind: ServiceAccount
name: elasticsearch-logging
namespace: kube-system
apiGroup: ""
roleRef:
kind: ClusterRole
name: elasticsearch-logging
apiGroup: ""
---
# Elasticsearch deployment itself
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: elasticsearch-logging
namespace: kube-system
labels:
k8s-app: elasticsearch-logging
version: v6.6.1
addonmanager.kubernetes.io/mode: Reconcile
spec:
serviceName: elasticsearch-logging
replicas: 2
selector:
matchLabels:
k8s-app: elasticsearch-logging
version: v6.7.2
template:
metadata:
labels:
k8s-app: elasticsearch-logging
version: v6.7.2
spec:
serviceAccountName: elasticsearch-logging
containers:
- image: gcr.io/fluentd-elasticsearch/elasticsearch:v6.6.1
name: elasticsearch-logging
resources:
# need more cpu upon initialization, therefore burstable class
limits:
cpu: 1000m
requests:
cpu: 100m
ports:
- containerPort: 9200
name: db
protocol: TCP
- containerPort: 9300
name: transport
protocol: TCP
volumeMounts:
- name: elasticsearch-logging
mountPath: /data
env:
- name: "NAMESPACE"
valueFrom:
fieldRef:
fieldPath: metadata.namespace
volumes:
- name: elasticsearch-logging
emptyDir: {}
# Elasticsearch requires vm.max_map_count to be at least 262144.
# If your OS already sets up this number to a higher value, feel free
# to remove this init container.
initContainers:
- image: alpine:3.6
command: ["/sbin/sysctl", "-w", "vm.max_map_count=262144"]
name: elasticsearch-logging-init
securityContext:
privileged: truees-service.yaml
apiVersion: v1
kind: Service
metadata:
name: elasticsearch-logging
namespace: kube-system
labels:
k8s-app: elasticsearch-logging
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
kubernetes.io/name: "Elasticsearch"
spec:
ports:
- port: 9200
protocol: TCP
targetPort: db
selector:
k8s-app: elasticsearch-logging查看服务列表及日志输出，确认es服务启动成功
[root@k8s-master ~]# kubectl get service -n kube-system
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
calico-typha ClusterIP 10.96.133.196 <none> 5473/TCP 26h
default-http-backend ClusterIP 10.110.35.232 <none> 80/TCP 18h
elasticsearch-logging ClusterIP 10.100.34.148 <none> 9200/TCP 71s
kube-dns ClusterIP 10.96.0.10 <none> 53/UDP,53/TCP,9153/TCP 3d21h
kubernetes-dashboard NodePort 10.98.37.20 <none> 80:30006/TCP 3d3h
[root@k8s-master ~]# kubectl logs -f elasticsearch-logging-0 -n kube-system
[root@k8s-master ~]# kubectl logs -f elasticsearch-logging-1 -n kube-systemKibana日志展示容器部署
Kibana是一个开源的分析与可视化平台，与elasticsearch配合使用，可以使用kibana搜索、查看存储在es中的数据
kibana部署文件
kibana-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: kibana-logging
namespace: kube-system
labels:
k8s-app: kibana-logging
addonmanager.kubernetes.io/mode: Reconcile
spec:
replicas: 1
selector:
matchLabels:
k8s-app: kibana-logging
template:
metadata:
labels:
k8s-app: kibana-logging
annotations:
seccomp.security.alpha.kubernetes.io/pod: 'docker/default'
spec:
containers:
- name: kibana-logging
image: docker.elastic.co/kibana/kibana-oss:6.6.1
resources:
# need more cpu upon initialization, therefore burstable class
limits:
cpu: 1000m
requests:
cpu: 100m
env:
- name: ELASTICSEARCH_URL
value: http://elasticsearch-logging:9200
- name: SERVER_BASEPATH
value: /api/v1/namespaces/kube-system/services/kibana-logging/proxy
ports:
- containerPort: 5601
name: ui
protocol: TCP
livenessProbe:
httpGet:
path: /api/status
port: ui
initialDelaySeconds: 5
timeoutSeconds: 10
readinessProbe:
httpGet:
path: /api/status
port: ui
initialDelaySeconds: 5
timeoutSeconds: 10kibana服务文件
kibana-service.yaml
apiVersion: v1
kind: Service
metadata:
name: kibana-logging
namespace: kube-system
labels:
k8s-app: kibana-logging
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
kubernetes.io/name: "Kibana"
spec:
ports:
- port: 5601
protocol: TCP
targetPort: ui
selector:
k8s-app: kibana-logging查看kibana对应的服务地址：
[root@k8s-master ~]# kubectl cluster-info | grep kibana
Kibana is running at https://192.168.0.8:6443/api/v1/namespaces/kube-system/services/kibana-logging/proxy因此通过proxy代理将kibana服务暴露出来：
kubectl proxy --port=8080 --address=192.168.0.8 --accept-hosts=^*$访问节点，端口改为8080：http://192.168.80.8
以上，kubernetes集群EFK日志框架构建完成。
版权声明：
作者：Joe.Ye
链接：https://www.appblog.cn/index.php/2023/03/23/kubernetes-cluster-efk-log-framework-deployment/
来源：APP全栈技术分享
文章版权归作者所有，未经允许请勿转载。
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Kubernetes集群EFK日志框架部署
目标：在现有Kubernetes集群中搭建EFK日志框架，实现集群日志的存储与展示
环境：Kubernetes集群(kubeadm方式部署)
步骤：Kubernetes日志架构概述 -> Fluen……
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