kubernetes EFK
约 317 字
预计阅读 1 分钟
次阅读
kubernetes EFK
初始化环境
1
2
3
4
5
| # 增加max_map_count
echo 'vm.max_map_count=262144' >> /etc/sysctl.conf
sysctl -p
|
配置 namespace
1
2
3
4
5
6
7
8
| vi logging-namespace.yaml
---
apiVersion: v1
kind: Namespace
metadata:
name: logging
|
配置 elasticsearch
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
| # 增加 elasticsearch-deployment.yaml
curl -O https://raw.githubusercontent.com/jicki/kuberneres/master/efk/elasticsearch-deployment.yaml
# 这里需要按需修改
# JVM 配置
"-Xms4g -Xmx4g"
# volume 配置
volumes:
- name: es-volume
persistentVolumeClaim:
claimName: efk-claim
|
1
2
3
4
| # 增加 elasticsearch-service.yaml 文件
curl -O https://raw.githubusercontent.com/jicki/kuberneres/master/efk/elasticsearch-service.yaml
|
配置 fluentd
1
2
3
4
5
| # 增加 fluentd-daemonset.yaml
# td-agent 这一段 配置输入,请按需配置
curl -O https://raw.githubusercontent.com/jicki/kuberneres/master/efk/fluentd-daemonset.yaml
|
配置 kibana
1
2
3
4
5
6
7
8
9
| # 增加 kibana-deployment.yaml
curl -O https://raw.githubusercontent.com/jicki/kuberneres/master/efk/kibana-deployment.yaml
# 增加 kibana-service.yaml
curl -O https://raw.githubusercontent.com/jicki/kuberneres/master/efk/kibana-service.yaml
|
导入 yaml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
| # 导入
kubectl apply -f logging-namespace.yaml
kubectl apply -f fluentd-daemonset.yaml
kubectl apply -f elasticsearch-deployment.yaml
kubectl apply -f elasticsearch-service.yaml
kubectl apply -f kibana-deployment.yaml
kubectl apply -f kibana-service.yaml
# 查看导入
kubectl get all --namespace=logging -o wide
|
测试
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
| # elasticsearch 管理端口为 30200
http://node-ip:30200/
# kibana 访问页面 30601
http://node-ip:30601
# 1. 选择 @timestamps 点击 create
# 2. curl -O https://raw.githubusercontent.com/jicki/kuberneres/master/efk/dashboards/elk-v1.json
# 3. 选择 management > Saved Object > Import > elk-v1.json
# 4. 选择 Dashboard 勾选 ELK 并点击 ELK,等待加载。
|
