Prometheus Input Plugin

The prometheus input plugin gathers metrics from HTTP servers exposing metrics in Prometheus format.

Configuration:

# Read metrics from one or many prometheus clients
[[inputs.prometheus]]
  ## An array of urls to scrape metrics from.
  urls = ["http://localhost:9100/metrics"]

  ## An array of Kubernetes services to scrape metrics from.
  # kubernetes_services = ["http://my-service-dns.my-namespace:9100/metrics"]

  ## Use bearer token for authorization
  # bearer_token = /path/to/bearer/token

  ## Specify timeout duration for slower prometheus clients (default is 3s)
  # response_timeout = "3s"

  ## Optional TLS Config
  # tls_ca = /path/to/cafile
  # tls_cert = /path/to/certfile
  # tls_key = /path/to/keyfile
  ## Use TLS but skip chain & host verification
  # insecure_skip_verify = false

urls can contain a unix socket as well. If a different path is required (default is /metrics for both http[s] and unix) for a unix socket, add path as a query parameter as follows: unix:///var/run/prometheus.sock?path=/custom/metrics

Kubernetes Service Discovery

URLs listed in the kubernetes_services parameter will be expanded by looking up all A records assigned to the hostname as described in Kubernetes DNS service discovery.

This method can be used to locate all Kubernetes headless services.

Bearer Token

If set, the file specified by the bearer_token parameter will be read on each interval and its contents will be appended to the Bearer string in the Authorization header.

Usage for Caddy HTTP server

If you want to monitor Caddy, you need to use Caddy with its Prometheus plugin:

Download Caddy+Prometheus plugin here
Add the prometheus directive in your CaddyFile
Restart Caddy
Configure Telegraf to fetch metrics on it:

[[inputs.prometheus]]
#   ## An array of urls to scrape metrics from.
  urls = ["http://localhost:9180/metrics"]

This is the default URL where Caddy Prometheus plugin will send data. For more details, please read the Caddy Prometheus documentation.

Metrics:

Measurement names are based on the Metric Family and tags are created for each label. The value is added to a field named based on the metric type.

All metrics receive the url tag indicating the related URL specified in the Telegraf configuration. If using Kubernetes service discovery the address tag is also added indicating the discovered ip address.

Example Output:

Source

# HELP go_gc_duration_seconds A summary of the GC invocation durations.
# TYPE go_gc_duration_seconds summary
go_gc_duration_seconds{quantile="0"} 7.4545e-05
go_gc_duration_seconds{quantile="0.25"} 7.6999e-05
go_gc_duration_seconds{quantile="0.5"} 0.000277935
go_gc_duration_seconds{quantile="0.75"} 0.000706591
go_gc_duration_seconds{quantile="1"} 0.000706591
go_gc_duration_seconds_sum 0.00113607
go_gc_duration_seconds_count 4
# HELP go_goroutines Number of goroutines that currently exist.
# TYPE go_goroutines gauge
go_goroutines 15
# HELP cpu_usage_user Telegraf collected metric
# TYPE cpu_usage_user gauge
cpu_usage_user{cpu="cpu0"} 1.4112903225816156
cpu_usage_user{cpu="cpu1"} 0.702106318955865
cpu_usage_user{cpu="cpu2"} 2.0161290322588776
cpu_usage_user{cpu="cpu3"} 1.5045135406226022

Output

go_gc_duration_seconds,url=http://example.org:9273/metrics 1=0.001336611,count=14,sum=0.004527551,0=0.000057965,0.25=0.000083812,0.5=0.000286537,0.75=0.000365303 1505776733000000000
go_goroutines,url=http://example.org:9273/metrics gauge=21 1505776695000000000
cpu_usage_user,cpu=cpu0,url=http://example.org:9273/metrics gauge=1.513622603430151 1505776751000000000
cpu_usage_user,cpu=cpu1,url=http://example.org:9273/metrics gauge=5.829145728641773 1505776751000000000
cpu_usage_user,cpu=cpu2,url=http://example.org:9273/metrics gauge=2.119071644805144 1505776751000000000
cpu_usage_user,cpu=cpu3,url=http://example.org:9273/metrics gauge=1.5228426395944945 1505776751000000000

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