官方配置指南
官方文檔->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信息： metrics_path 和 basic_auth。其中，metrics_path 用於指定 HTTP 類指標信息采集時的路由地址，默認值是 /metrics；字段 basic_auth 則是用來進行權限驗證的，而且密碼這里可以指定密碼文件，而不是直接填寫明文（一般來說，指定密碼文件的安全性稍高與明文）。
有效的配置
根據官方文檔的指引，我們很快便可以推導出正確的配置寫法：
- 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，這里並不需要填寫 http:// 字樣，因為 Prometheus 默認的 Scheme 就是 http。如果地址的 Scheme 是 https 的話，按照文檔指引，我們需要添加 scheme 字段，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
配置完成后，Prometheus 應該就能順利的采集到數據了，配上 Grafana，就能夠看到開篇給出的監控效果圖。