jmeter+grafana+prometheus的docker性能压测体系

好记性不如烂笔头，记下来便人便己：

1、搭建Prometheus的容器：

docker run -d --name prometheus -p 9090:9090 --network grafana -v $PWD/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus

其中:

①prometheus.yml文件的默认配置可以从容器中挂载出来一份，也可以直接修改。我要访问的的服务在本机。这里有个坑，就是在容器里面要访问宿主机的ip的话，不能写localhost。方法是：要么将容器共享宿主机网络，这个不建议；要么就直接写宿主机的内网ip即可。

# my global config
global:
  scrape_interval:     15s # Set the scrape interval to every 15 seconds. Default is every 1 minute.
  evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute.
  # scrape_timeout is set to the global default (10s).

# Alertmanager configuration
alerting:
  alertmanagers:
  - static_configs:
    - targets:
      # - alertmanager:9093

# Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
rule_files:
  # - "first_rules.yml"
  # - "second_rules.yml"

# A scrape configuration containing exactly one endpoint to scrape:
# Here it's Prometheus itself.
scrape_configs:
  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
  - job_name: 'prometheus'

    # metrics_path defaults to '/metrics'
    # scheme defaults to 'http'.

    static_configs:
    - targets: ['localhost:9090']

  - job_name: 'python-modules'

    static_configs:
    - targets: ['ip:80']

②创建一个grafana共享网络，使之与grafana容器处于同一网络空间

 

2、启动grafana容器

docker run -d --name grafana --network grafana -p 3000:3000 grafana/grafana:6.6.2

 

3、 在grafana里面配置好Prometheus的数据源，即dashboard即可。完成后的样例如下：