https://medium.com/avmconsulting-blog/how-to-deploy-an-efk-stack-to-kubernetes-ebc1b539d063
01. 사전조건
02. 개요
03. 설치
03-01. Namespace 생성
- EFK Stack을 Deploy할 namespace를 생성합니다.
sansae@win10pro-worksp:/workspaces$ kubectl create ns monitor-efk
03-02. StorageClass 확인
- Elasticsearch의 PersistanceVolume을 사용하기 위하여, StorageClass를 확인 합니다.
- Elasticsearch는 AzureDisk로 Volume을 생성해야 합니다. 따라서 'managed-premium'을 사용할 것입니다.
sansae@win10pro-worksp:/workspaces$ kubectl get sc NAME PROVISIONER RECLAIMPOLICY VOLUMEBINDINGMODE ALLOWVOLUMEEXPANSION AGE azurefile kubernetes.io/azure-file Delete Immediate true 63d azurefile-premium kubernetes.io/azure-file Delete Immediate true 63d default (default) kubernetes.io/azure-disk Delete Immediate true 63d managed kubernetes.io/azure-disk Delete WaitForFirstConsumer true 28d managed-premium kubernetes.io/azure-disk Delete Immediate true 63d
03-03. Elasticsearch
- Elasticsearch를 Stable버전으로 명세 합니다.
- Volume을 영구 저장하기 위하여 PersistanceVolume를 Azure Disk로 할당 받아야 합니다. 따라서, StorageClassName을 'managed-premium'으로 설정합니다.
sansae@win10pro-worksp:/workspaces$ git clone
sansae@win10pro-worksp:/workspaces$ mv helm-charts elastic
sansae@win10pro-worksp:/workspaces$ cd elastic
sansae@win10pro-worksp:/workspaces/elastic$
sansae@win10pro-worksp:/workspaces/elastic$ vi elasticsearch/values.yaml
=========================================================
imageTag: "7.12.0"
----------------------------------------
volumeClaimTemplate:
storageClassName: managed-premium
accessModes: [ "ReadWriteOnce" ]
resources:
requests:
storage: 30Gi
=========================================================
sansae@win10pro-worksp:/workspaces/elastic$ helm install elasticsearch/ --generate-name -n monitor-efk
NAME: elasticsearch-1617184828
LAST DEPLOYED: Wed Mar 31 19:00:30 2021
NAMESPACE: monitor-efk
STATUS: deployed
REVISION: 1
NOTES:
1. Watch all cluster members come up.
$ kubectl get pods --namespace=monitor-efk -l app=elasticsearch-master -w
2. Test cluster health using Helm test.
$ helm --namespace=monitor-efk test elasticsearch-1617184828
sansae@win10pro-worksp:/workspaces/elastic$ kubectl get pod -n monitor-efk
NAME READY STATUS RESTARTS AGE
elasticsearch-master-0 1/1 Running 0 4m20s
elasticsearch-master-1 1/1 Running 0 4m20s
elasticsearch-master-2 1/1 Running 0 4m20s
03-03. Fluentd
- Elasticsearch ServiceName 'elasticsearch-master'로 설정합니다.
- Elasticsearch Port: 9200 으로 설정합니다.
sansae@win10pro-worksp:/workspaces$ git clone
sansae@win10pro-worksp:/workspaces$ mv helm-charts fluent
sansae@win10pro-worksp:/workspaces$ cd fluent
sansae@win10pro-worksp:/workspaces/fluent$ cd charts
sansae@win10pro-worksp:/workspaces/fluent/charts$ vi fluentd/values.yaml
=========================================================
env:
#- name: "FLUENTD_CONF"
# value: "../../etc/fluent/fluent.conf"
- name: FLUENT_ELASTICSEARCH_HOST
value: "elasticsearch-master"
- name: FLUENT_ELASTICSEARCH_PORT
value: "9200"
=========================================================
sansae@win10pro-worksp:/workspaces/fluent/charts$ helm install fluentd --generate-name -n monitor-efk
NAME: fluentd-1617186347
LAST DEPLOYED: Wed Mar 31 19:25:49 2021
NAMESPACE: monitor-efk
STATUS: deployed
REVISION: 1
NOTES:
Get Fluentd build information by running these commands:
export POD_NAME=$(kubectl get pods --namespace monitor-efk -l "app.kubernetes.io/name=fluentd,app.kubernetes.io/instance=fluentd-1617186347" -o jsonpath="{.items[0].metadata.name}")
echo "curl http://127.0.0.1:24231/metrics for Fluentd metrics"
kubectl --namespace monitor-efk port-forward $POD_NAME 24231:24231
sansae@win10pro-worksp:/workspaces/fluent/charts$ kubectl get pod -n monitor-efk
NAME READY STATUS RESTARTS AGE
elasticsearch-master-0 1/1 Running 0 16m
elasticsearch-master-1 1/1 Running 0 16m
elasticsearch-master-2 1/1 Running 0 16m
fluentd-1617190066-9g8n8 1/1 Running 2 12m
fluentd-1617190066-9vnjh 1/1 Running 3 12m
fluentd-1617190066-ccmth 0/1 CrashLoopBackOff 7 12m
fluentd-1617190066-kfr96 1/1 Running 2 12m
fluentd-1617190066-kxtmh 1/1 Running 6 12m
fluentd-1617190066-n4566 1/1 Running 6 12m
fluentd-1617190066-n77b8 1/1 Running 4 12m
fluentd-1617190066-nxxq5 1/1 Running 2 12m
fluentd-1617190066-v4dp9 1/1 Running 2 12m
fluentd-1617190066-x4l6g 1/1 Running 6 12m
03-04. Kibana
sansae@win10pro-worksp:/workspaces$ cd elastic sansae@win10pro-worksp:/workspaces/elastic$ sansae@win10pro-worksp:/workspaces/elastic$ vi kibana/values.yaml ========================================================= imageTag: "7.12.0" ========================================================= sansae@win10pro-worksp:/workspaces/elastic$ helm install kibana/ --generate-name -n monitor-efk NAME: kibana-1617190735 LAST DEPLOYED: Wed Mar 31 20:38:57 2021 NAMESPACE: monitor-efk STATUS: deployed REVISION: 1 TEST SUITE: None sansae@win10pro-worksp:/workspaces/elastic$ kubectl get pod -n monitor-efk NAME READY STATUS RESTARTS AGE elasticsearch-master-0 1/1 Running 0 15h elasticsearch-master-1 1/1 Running 0 15h elasticsearch-master-2 1/1 Running 0 15h fluentd-1617190066-9g8n8 1/1 Running 2 14h fluentd-1617190066-9vnjh 1/1 Running 3 14h fluentd-1617190066-ccmth 1/1 Running 8 14h fluentd-1617190066-kfr96 1/1 Running 2 14h fluentd-1617190066-kxtmh 1/1 Running 6 14h fluentd-1617190066-n4566 1/1 Running 6 14h fluentd-1617190066-n77b8 1/1 Running 4 14h fluentd-1617190066-nxxq5 1/1 Running 2 14h fluentd-1617190066-v4dp9 1/1 Running 2 14h fluentd-1617190066-x4l6g 1/1 Running 6 14h kibana-1617190735-kibana-77f8f5b8c8-zxt8b 1/1 Running 0 14h
04. Dashboard 확인
sansae@win10pro-worksp:/workspaces/elastic$ kubectl get svc -n monitor-efk NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE elasticsearch-master ClusterIP 10.0.186.68 <none> 9200/TCP,9300/TCP 18m elasticsearch-master-headless ClusterIP None <none> 9200/TCP,9300/TCP 18m fluentd-1617190066 ClusterIP 10.0.173.141 <none> 24231/TCP 14m kibana-1617190735-kibana ClusterIP 10.0.17.173 <none> 5601/TCP 3m4s sansae@win10pro-worksp:/workspaces/elastic$ kubectl port-forward svc/kibana-1617190735-kibana 5601 -n monitor-efk Forwarding from 127.0.0.1:5601 -> 5601 Forwarding from [::1]:5601 -> 5601
