1.配置文件

在 Linux /tmp目录下创建prometheus.yml配置文件

# 全局配置段
global:
  # 采集间隔 
  scrape_interval:     15s # Set the scrape interval to every 15 seconds. Default is every 1 minute.
  # 计算报警和预聚合间隔
  evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute.
  # 采集超时时间
  scrape_timeout: 10s 
  # 查询日志，包含各阶段耗时统计
  query_log_file: /opt/logs/prometheus_query_log
  # 全局标签组
  # 通过本实例采集的数据都会叠加下面的标签
  external_labels:
    account: 'huawei-main'
    region: 'beijng-01'


# Alertmanager信息段
alerting:
  alertmanagers:
  - scheme: http
    static_configs:
    - targets:
      - "localhost:9093"

# 告警、预聚合配置文件段
rule_files:
    - /etc/prometheus/rules/record.yml
    - /etc/prometheus/rules/alert.yml

# 采集配置段
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']

# 远程查询段
remote_read:
  # prometheus 
  - url: http://prometheus/v1/read
    read_recent: true

  # m3db 
  - url: "http://m3coordinator-read:7201/api/v1/prom/remote/read"
    read_recent: true

# 远程写入段
remote_write:
  - url: "http://m3coordinator-write:7201/api/v1/prom/remote/write"
    queue_config:
      capacity: 10000
      max_samples_per_send: 60000
    write_relabel_configs:
      - source_labels: [__name__]
        separator: ;
        # 标签key前缀匹配到的drop
        regex: '(kubelet_|apiserver_|container_fs_).*'
        replacement: $1
        action: drop

2.安装并运行prometheus

docker run -d\
 --name=prometheus\
 -p9090:9090\
 -v /tmp/promethues.yml:/etc/prometheus/prometheus.yml\
  prom/prometheus

3.访问localhost:9090查看prometheus运行情况