官方配置指南

官方文件->Prometheus Configuration

# The job name assigned to scraped metrics by default.
job_name: <job_name>

# How frequently to scrape targets from this job.
[ scrape_interval: <duration> | default = <global_config.scrape_interval> ]

# Per-scrape timeout when scraping this job.
[ scrape_timeout: <duration> | default = <global_config.scrape_timeout> ]

# The HTTP resource path on which to fetch metrics from targets.
[ metrics_path: <path> | default = /metrics ]

# honor_labels controls how Prometheus handles conflicts between labels that are
# already present in scraped data and labels that Prometheus would attach
# server-side ("job" and "instance" labels, manually configured target
# labels, and labels generated by service discovery implementations).
#
# If honor_labels is set to "true", label conflicts are resolved by keeping label
# values from the scraped data and ignoring the conflicting server-side labels.
#
# If honor_labels is set to "false", label conflicts are resolved by renaming
# conflicting labels in the scraped data to "exported_<original-label>" (for
# example "exported_instance", "exported_job") and then attaching server-side
# labels.
#
# Setting honor_labels to "true" is useful for use cases such as federation and
# scraping the Pushgateway, where all labels specified in the target should be
# preserved.
#
# Note that any globally configured "external_labels" are unaffected by this
# setting. In communication with external systems, they are always applied only
# when a time series does not have a given label yet and are ignored otherwise.
[ honor_labels: <boolean> | default = false ]

# honor_timestamps controls whether Prometheus respects the timestamps present
# in scraped data.
#
# If honor_timestamps is set to "true", the timestamps of the metrics exposed
# by the target will be used.
#
# If honor_timestamps is set to "false", the timestamps of the metrics exposed
# by the target will be ignored.
[ honor_timestamps: <boolean> | default = true ]

# Configures the protocol scheme used for requests.
[ scheme: <scheme> | default = http ]

# Optional HTTP URL parameters.
params:
  [ <string>: [<string>, ...] ]

# Sets the `Authorization` header on every scrape request with the
# configured username and password.
# password and password_file are mutually exclusive.
basic_auth:
  [ username: <string> ]
  [ password: <secret> ]
  [ password_file: <string> ]

# Sets the `Authorization` header on every scrape request with
# the configured bearer token. It is mutually exclusive with `bearer_token_file`.
[ bearer_token: <secret> ]

# Sets the `Authorization` header on every scrape request with the bearer token
# read from the configured file. It is mutually exclusive with `bearer_token`.
[ bearer_token_file: <filename> ]
 

如果你認真看的話，應該會關注到幾個關鍵資訊： metrics_path 和 basic_auth。其中，metrics_path 用於指定 HTTP 類指標資訊採集時的路由地址，預設值是 /metrics；欄位 basic_auth 則是用來進行許可權驗證的，而且密碼這裡可以指定密碼檔案，而不是直接填寫明文（一般來說，指定密碼檔案的安全性稍高與明文）。

有效的配置

根據官方文件的指引，我們很快便可以推匯出正確的配置寫法：

- job_name: 'web'
    metrics_path: /status/format/prometheus
    static_configs:
    - targets: ['www.weishidong.com']
    basic_auth:
      username: weishidong
      password: 0099887kk
 

要注意的是，這裡並不需要填寫 http:// 字樣，因為 Prometheus 預設的 Scheme 就是 http。如果地址的 Scheme 是 https 的話，按照文件指引，我們需要新增 scheme 欄位，對應的配置為：

- job_name: 'web'
    metrics_path: /status/format/prometheus
    static_configs:
    - targets: ['www.weishidong.com']
    scheme: https
    basic_auth:
      username: weishidong
      password: 0099887kk
 

配置完成後，Prometheus 應該就能順利的採集到資料了，配上 Grafana，就能夠看到開篇給出的監控效果圖。