标签：har tar artifact yml enc 响应 inter arp clu
jvm：
maven添加dependence
<!-- https://mvnrepository.com/artifact/io.micrometer/micrometer-registry-prometheus -->
<dependency>
<groupId>io.micrometer</groupId>
<artifactId>micrometer-registry-prometheus</artifactId>
<version>1.3.5</version>
</dependency>
编辑springboot项目的yml文件
yml配置参考https://blog.csdn.net/u014401141/article/details/84784422
server:
port: 8085
spring:
#for monitor
application:
name: mall_prometheus
management:
#TODO endpoint 解释查询
endpoints:
web:
exposure:
#include: "*"
include: info, health, beans, env, metrics, mappings, scheduledtasks, sessions, threaddump, docs, logfile, jolokia, prometheus
base-path: /actuator #默认该路径，不更改可不用配置
#cors跨域支持
cors:
allowed-origins: http://example.com
allowed-methods: GET,PUT,POST,DELETE
prometheus:
id: springmetrics
endpoint:
beans:
cache:
time-to-live: 10s #端点缓存响应的时间量
health:
show-details: always #详细信息显示给所有用户
server:
port: 8001 #默认8888
#address: 127.0.0.1 #配置此项表示不允许远程连接
#monitor
metrics:
export:
datadog:
application-key: ${spring.application.name}
web:
server:
auto-time-requests: true
配置prometheus.yml
global:
scrape_interval: 15s # By default, scrape targets every 15 seconds.
evaluation_interval: 15s # Evaluate rules every 15 seconds.
scrape_configs:
- job_name: prometheus
static_configs:
- targets: [‘localhost:9090‘]
labels:
instance: prometheus
- job_name: linux
static_configs:
- targets: [‘47.112.188.174:9100‘]
labels:
instance: node
- job_name: ‘spring‘
metrics_path: ‘/actuator/prometheus‘
static_configs:
- targets: [‘47.112.188.174:8001‘]
docker 启动服务时，开放8001端口
# 9100是exporter的端口 docker run -p 8001:8001 -p 8085:8085 --name mall-portal --link mall-mysql:db --link mall-redis:redis --link mongo:mongo --link rabbitmq:rabbit -v /etc/localtime:/etc/localtime -v/usr/local/dockerdata/mall-project/mall-port/logs:/var/logs -d mall/mall-portal:1.0-SNAPSHOT
启动prometheus时加载配置
docker run --name prometheus -d -p 9090:9090 --privileged=true -v /usr/local/dockerdata/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus --config.file=/etc/prometheus/prometheus.yml
grafana添加对应dashboard:4701
https://grafana.com/grafana/dashboards/4701
mysql
启动mysql的时候
数据库内执行：
use mall; GRANT REPLICATION CLIENT, PROCESS ON *.* to ‘exporter‘@‘%‘ identified by ‘exporter‘; GRANT SELECT ON performance_schema.* TO ‘exporter‘@‘%‘; flush privileges;
docker 启动 mysqld_exporter
docker run -d --restart=always --name mysqld-exporter -p 9104:9104 -e DATA_SOURCE_NAME=‘exporter:exporter@(47.112.188.174:3306)/‘ prom/mysqld-exporter
curl 验证一下
curl localhost:9104/metrics
process_virtual_memory_bytes 1.16281344e+08
# HELP process_virtual_memory_max_bytes Maximum amount of virtual memory available in bytes.
# TYPE process_virtual_memory_max_bytes gauge
process_virtual_memory_max_bytes -1
# HELP promhttp_metric_handler_requests_in_flight Current number of scrapes being served.
# TYPE promhttp_metric_handler_requests_in_flight gauge
promhttp_metric_handler_requests_in_flight 1
# HELP promhttp_metric_handler_requests_total Total number of scrapes by HTTP status code.
# TYPE promhttp_metric_handler_requests_total counter
promhttp_metric_handler_requests_total{code="200"} 0
promhttp_metric_handler_requests_total{code="500"} 0
promhttp_metric_handler_requests_total{code="503"} 0
然后修改一下prometheus的yaml。。。。。。具体编写和运行不再赘述。。。
上面这种方式太过繁琐，几乎每次加一个exporter，都要修改prometheus.yml，并重启。可以使用consul来自动搜寻服务。
- job_name: consul
consul_sd_configs:
- server: ‘47.112.188.174:8500‘
services: []
relabel_configs:
- source_labels: [__meta_consul_tags]
regex: .*mall.*
action: keep
prometheus系列监控：jvm,mongodb,mysql,redis
标签：har tar artifact yml enc 响应 inter arp clu
原文地址：https://www.cnblogs.com/zhizhiyin/p/12418671.html
