k8sEfk快速搭建
1.前言ELK 相信大家都很熟悉ElasticSearch,分布式搜索和分析引擎。Logstash,实时传输能力的数据收集引擎。Kibana,为 Elasticsearch 提供了分析和可视化的 Web 平台。它可以在 Elasticsearch 的索引中查找,交互数据,并生成各种维度表格、图形。这里我们把Logstash 替换成 Fluentd,进行部署1.1 logstash 和 fluent
1.前言
ELK 相信大家都很熟悉
- ElasticSearch,分布式搜索和分析引擎。
- Logstash,实时传输能力的数据收集引擎。
- Kibana,为 Elasticsearch 提供了分析和可视化的 Web 平台。它可以在 Elasticsearch 的索引中查找,交互数据,并生成各种维度表格、图形。
这里我们把Logstash 替换成 Fluentd,进行部署
1.1 logstash 和 fluentd 对比
名称 | 优点 | 缺点 |
---|---|---|
logstash | Logstash 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 | 效能上表现略逊,大数据量的情况下会是个问题 |
fluentd | 效能好,轻量 | 灵活性差 |
1.2 flutend 相关说明
1.2.1 flutend 介绍
Fluentd 是一个高效的日志聚合器,是用 Ruby 编写的,并且可以很好地扩展。对于大部分企业来说,Fluentd 足够高效并且消耗的资源相对较少,另外一个工具Fluent-bit更轻量级,占用资源更少,但是插件相对 Fluentd 来说不够丰富,所以整体来说,Fluentd 更加成熟,使用更加广泛,所以我们这里也同样使用 Fluentd 来作为日志收集工具
1.2.2 工作原理
Fluentd 通过一组给定的数据源抓取日志数据,处理后(转换成结构化的数据格式)将它们转发给其他服务,比如 Elasticsearch、对象存储等等。Fluentd 支持超过300个日志存储和分析服务,所以在这方面是非常灵活的。主要运行步骤如下:
- 首先 Fluentd 从多个日志源获取数据
- 结构化并且标记这些数据
- 然后根据匹配的标签将数据发送到多个目标服务去
1.2.3 架构图
2.部署
本次搭建的环境是测试环境,一个主节点,四个工作节点
- Kubernetes:v1.17.3
- Kibana镜像 :kibana:7.6.2
- Elasticsearch镜像:elasticsearch:7.6.2
- Fluentd 镜像:willdockerhub/fluentd-elasticsearch:v2.3.2
2.1 Elasticsearch 相关
2.1.1 es-statefulset.yaml配置
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: es
namespace: logging
spec:
serviceName: elasticsearch
replicas: 3
selector:
matchLabels:
app: elasticsearch
template:
metadata:
labels:
app: elasticsearch
spec:
nodeSelector:
es: log
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: elasticsearch:7.6.2
ports:
- name: rest
containerPort: 9200
- name: inter
containerPort: 9300
resources:
limits:
cpu: 1000m
requests:
cpu: 1000m
volumeMounts:
- name: elasticsearch-logging
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: elasticsearch-logging
annotations:
volume.beta.kubernetes.io/storage-class: course-nfs-storage
spec:
accessModes: [ "ReadWriteOnce" ]
resources:
requests:
storage: 1Gi
关于volumeClaimTemplates相关的内容,我是参考 简书的一个博客
2.1.2 es-svc.yaml配置
kind: Service
apiVersion: v1
metadata:
name: elasticsearch
namespace: logging
labels:
app: elasticsearch
spec:
selector:
app: elasticsearch
clusterIP: None
ports:
- port: 9200
name: rest
- port: 9300
name: inter-node
2.1.3 安装es相关配置文件
$ kubectl create -f es-statefulset.yaml -n logging
$ kubectl create -f es-svc.yaml -n logging
$ kubectl get pods -n logging
NAME READY STATUS RESTARTS AGE
es-0 1/1 Running 0 6h9m
es-1 1/1 Running 0 6h9m
es-2 1/1 Running 0 6h8m
ps node label
$ kubectl get svc -n logging
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
elasticsearch ClusterIP None <none> 9200/TCP,9300/TCP 6h17m
2.1.4 测试es
$ kubectl port-forward es-0 9200:9200 --namespace=logging
Forwarding from 127.0.0.1:9200 -> 9200
Forwarding from [::1]:9200 -> 9200
打开新的终端
$ curl http://localhost:9200/_cluster/state?pretty
正常应该是可以看到该信息的
2.2 Kibana 相关
2.2.1 kibana.yaml配置文件
apiVersion: v1
kind: Service
metadata:
name: kibana
namespace: logging
labels:
app: kibana
spec:
ports:
- port: 5601
type: NodePort
selector:
app: kibana
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: kibana
namespace: logging
labels:
app: kibana
spec:
selector:
matchLabels:
app: kibana
template:
metadata:
labels:
app: kibana
spec:
nodeSelector:
es: log
containers:
- name: kibana
image: kibana:7.6.2
resources:
limits:
cpu: 1000m
requests:
cpu: 1000m
env:
- name: ELASTICSEARCH_HOSTS
value: http://elasticsearch:9200
ports:
- containerPort: 5601
2.2.2 部署kibana相关yaml
$ kubectl create -f kibana.yaml -n logging
$ kubectl get pods -n logging
NAME READY STATUS RESTARTS AGE
es-0 1/1 Running 0 6h9m
es-1 1/1 Running 0 6h9m
es-2 1/1 Running 0 6h8m
kibana-7fc6d9dcbf-9twkd 1/1 Running 0 5h22m
$ kubectl get svc -n logging
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
elasticsearch ClusterIP None <none> 9200/TCP,9300/TCP 6h9m
kibana NodePort 10.108.169.43 <none> 5601:32355/TCP 5h14m
2.2.5 测试kibana
在浏览器中输入 访问 10.104.61.249:32355 即可打开kibana 即可
2.3 flutend相关
2.3.1 fluentd-es-configmap.yaml
kind: ConfigMap
apiVersion: v1
metadata:
name: fluentd-es-config-v0.2.0
namespace: logging
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>
<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,$.kubernetes.pod_name,$.stream,$.tag
</filter>
<filter kubernetes.**>
@id filter_log
@type grep
<regexp>
key $.kubernetes.labels.logging
pattern ^true$
</regexp>
</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
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
total_limit_size 500M
overflow_action block
</buffer>
</match>
2.3.2 fluentd-es-ds.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
name: fluentd-es
namespace: logging
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: logging
apiGroup: ""
roleRef:
kind: ClusterRole
name: fluentd-es
apiGroup: ""
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
name: fluentd-es-v2.3.2
namespace: logging
labels:
k8s-app: fluentd-es
version: v2.3.2
addonmanager.kubernetes.io/mode: Reconcile
spec:
selector:
matchLabels:
k8s-app: fluentd-es
version: v2.3.2
template:
metadata:
labels:
k8s-app: fluentd-es
version: v2.3.2
# 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:
seccomp.security.alpha.kubernetes.io/pod: 'docker/default'
spec:
priorityClassName: system-node-critical
serviceAccountName: fluentd-es
containers:
- name: fluentd-es
image: willdockerhub/fluentd-elasticsearch:v2.3.2
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: /home/docker/data/containers
readOnly: true
- name: config-volume
mountPath: /etc/fluent/config.d
ports:
- containerPort: 24231
name: prometheus
protocol: TCP
livenessProbe:
tcpSocket:
port: prometheus
initialDelaySeconds: 5
timeoutSeconds: 10
readinessProbe:
tcpSocket:
port: prometheus
initialDelaySeconds: 5
timeoutSeconds: 10
terminationGracePeriodSeconds: 30
volumes:
- name: varlog
hostPath:
path: /var/log
- name: varlibdockercontainers
hostPath:
path: /home/docker/data/containers
- name: config-volume
configMap:
name: fluentd-es-config-v0.2.0
为了能够灵活控制哪些节点的日志可以被收集,所以这里还添加了一个 nodSelector 属性
nodeSelector:
beta.kubernetes.io/fluentd-ds-ready: "true"
想采集节点的日志,那么我们就需要给节点打上上面的标签 我是在所有的节点打上标签
$ kubectl label nodes node名 beta.kubernetes.io/fluentd-ds-ready=true
$ kubectl get nodes --show-labels
NAME STATUS ROLES AGE VERSION LABELS
v10-104-141-164 Ready <none> 69d v1.17.3 beta.kubernetes.io/arch=amd64,beta.kubernetes.io/fluentd-ds-ready=true,beta.kubernetes.io/os=linux,kubernetes.io/arch=amd64,kubernetes.io/hostname=v10-104-141-164,kubernetes.io/os=linux
v10-104-61-249 Ready master 69d v1.17.3 beta.kubernetes.io/arch=amd64,beta.kubernetes.io/fluentd-ds-ready=true,beta.kubernetes.io/os=linux,kubernetes.io/arch=amd64,kubernetes.io/hostname=v10-104-61-249,kubernetes.io/os=linux,node-role.kubernetes.io/master=
v10-104-61-251 Ready <none> 69d v1.17.3 app=ingress,beta.kubernetes.io/arch=amd64,beta.kubernetes.io/fluentd-ds-ready=true,beta.kubernetes.io/os=linux,es=log,kubernetes.io/arch=amd64,kubernetes.io/hostname=v10-104-61-251,kubernetes.io/os=linux
v10-104-61-252 Ready <none> 69d v1.17.3 app=ingress,beta.kubernetes.io/arch=amd64,beta.kubernetes.io/fluentd-ds-ready=true,beta.kubernetes.io/os=linux,es=log,kubernetes.io/arch=amd64,kubernetes.io/hostname=v10-104-61-252,kubernetes.io/os=linux
v10-104-61-253 Ready <none> 69d v1.17.3 beta.kubernetes.io/arch=amd64,beta.kubernetes.io/fluentd-ds-ready=true,beta.kubernetes.io/os=linux,es=log,kubernetes.io/arch=amd64,kubernetes.io/hostname=v10-104-61-253,kubernetes.io/os=linux
这里需要注意的是,docker的根目录:
$ docker info
Docker Root Dir: /home/docker/data
所以上面要获取 docker 的容器目录需要更改成/home/docker/data/containers,这个地方非常重要,当然如果你没有更改 docker 根目录则使用默认的/var/lib/docker/containers目录即可
2.3.3 部署fluentd
$ kubectl create -f fluentd-es-configmap.yaml -n logging
$ kubectl create -f fluentd-es-ds.yaml -n logging
$ kubectl get pods -n logging
NAME READY STATUS RESTARTS AGE
es-0 1/1 Running 0 6h14m
es-1 1/1 Running 0 6h13m
es-2 1/1 Running 0 6h13m
fluentd-es-v2.3.2-64phl 1/1 Running 0 5h18m
fluentd-es-v2.3.2-fqtpf 1/1 Running 0 5h18m
fluentd-es-v2.3.2-gjk72 1/1 Running 0 5h18m
fluentd-es-v2.3.2-m8bv5 1/1 Running 0 5h18m
fluentd-es-v2.3.2-rb6z6 1/1 Running 0 5h18m
kibana-7fc6d9dcbf-9twkd 1/1 Running 0 5h26m
2.3.4 测试fluentd
部署一个简单的测试应用,新建 counter.yaml 文件,文件内容如下
apiVersion: v1
kind: Pod
metadata:
name: counter
labels:
logging: "true" # 一定要具有该标签才会被采集 在fluentd配置文件中有过滤
spec:
containers:
- name: count
image: busybox
args: [/bin/sh, -c,
'i=0; while true; do echo "$i: $(date)"; i=$((i+1)); sleep 1; done']
到这里,基本上efk就可以使用了
参考资料:
阳明博客
github单节点的简单项目
快速搭建博客
k8s yaml文件详解
nfs相关资料
项目地址
我这边把这次搭建的相关资料全部放在 项目资料,欢迎大家批评指正。
因为是快速搭建,可能还有之后要完善的地方,后续还会继续更新。
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