测试部署一套elasticsearch+kibana的日志监控的容器
启动一台es容器
# es暴露的端口很多
# es十分耗内存
# es数据一般需要放置到安全目录挂载
# 启动elasticsearch
[root@k8s-master ~]# docker run -d --name elasticsearch -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" elasticsearch:7.6.2
#访问
[root@k8s-master ~]# curl 127.0.0.1:9200
{
"name" : "7426e97975a1",
"cluster_name" : "docker-cluster",
"cluster_uuid" : "aNGISnU9QZm3qQw9obQiPg",
"version" : {
"number" : "7.6.2",
"build_flavor" : "default",
"build_type" : "docker",
"build_hash" : "ef48eb35cf30adf4db14086e8aabd07ef6fb113f",
"build_date" : "2020-03-26T06:34:37.794943Z",
"build_snapshot" : false,
"lucene_version" : "8.4.0",
"minimum_wire_compatibility_version" : "6.8.0",
"minimum_index_compatibility_version" : "6.0.0-beta1"
},
"tagline" : "You Know, for Search"
}
使用命令dcker stats查看es容器的内存占用情况太大
# 关闭刚刚启动的es容器,增加内存的限制,修改配置文件 -e 环境配置修改
docker run -d --name elasticsearch -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" -e ES_JAVA_OPTS="-Xms64m -Xmx512m" elasticsearch:7.6.2
[root@k8s-master ~]# curl 127.0.0.1:9200
{
"name" : "66fdfb9147aa",
"cluster_name" : "docker-cluster",
"cluster_uuid" : "7vONQG4HSjKXdtpMmEzbIg",
"version" : {
"number" : "7.6.2",
"build_flavor" : "default",
"build_type" : "docker",
"build_hash" : "ef48eb35cf30adf4db14086e8aabd07ef6fb113f",
"build_date" : "2020-03-26T06:34:37.794943Z",
"build_snapshot" : false,
"lucene_version" : "8.4.0",
"minimum_wire_compatibility_version" : "6.8.0",
"minimum_index_compatibility_version" : "6.0.0-beta1"
},
"tagline" : "You Know, for Search"
}
启动一台kibana容器
# 运行一台kibana7.6.2的容器,并添加到elasticsearch容器的网络中,使用--link或者创建自定义网络
docker run -d --name kibana --link elasticsearch -p 5601:5601 kibana:7.6.2
# 访问查看;选择一个样本数据进行测试是否与es连接