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# Prometheus Input Plugin
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The prometheus input plugin gathers metrics from HTTP servers exposing metrics
in Prometheus format.
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### Configuration:
```toml
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# Read metrics from one or many prometheus clients
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[[inputs.prometheus]]
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## An array of urls to scrape metrics from.
urls = ["http://localhost:9100/metrics"]
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## An array of Kubernetes services to scrape metrics from.
# kubernetes_services = ["http://my-service-dns.my-namespace:9100/metrics"]
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## Kubernetes config file to create client from.
# kube_config = "/path/to/kubernetes.config"
## Scrape Kubernetes pods for the following prometheus annotations:
## - prometheus.io/scrape: Enable scraping for this pod
## - prometheus.io/scheme: If the metrics endpoint is secured then you will need to
## set this to `https` & most likely set the tls config.
## - prometheus.io/path: If the metrics path is not /metrics, define it with this annotation.
## - prometheus.io/port: If port is not 9102 use this annotation
# monitor_kubernetes_pods = true
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## Use bearer token for authorization. ('bearer_token' takes priority)
# bearer_token = "/path/to/bearer/token"
## OR
# bearer_token_string = "abc_123"
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## Specify timeout duration for slower prometheus clients (default is 3s)
# response_timeout = "3s"
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## 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
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# insecure_skip_verify = false
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```
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`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`
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#### Kubernetes Service Discovery
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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 ](https://kubernetes.io/docs/concepts/services-networking/service/#dns ).
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This method can be used to locate all
[Kubernetes headless services ](https://kubernetes.io/docs/concepts/services-networking/service/#headless-services ).
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#### Kubernetes scraping
Enabling this option will allow the plugin to scrape for prometheus annotation on Kubernetes
pods. Currently, you can run this plugin in your kubernetes cluster, or we use the kubeconfig
file to determine where to monitor.
Currently the following annotation are supported:
* `prometheus.io/scrape` Enable scraping for this pod.
* `prometheus.io/scheme` If the metrics endpoint is secured then you will need to set this to `https` & most likely set the tls config. (default 'http')
* `prometheus.io/path` Override the path for the metrics endpoint on the service. (default '/metrics')
* `prometheus.io/port` Used to override the port. (default 9102)
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#### Bearer Token
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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.
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### 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 ](https://caddyserver.com/download/linux/amd64?plugins=http.prometheus )
* 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](https://github.com/miekg/caddy-prometheus/blob/master/README.md).
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### 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.
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All metrics receive the `url` tag indicating the related URL specified in the
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Telegraf configuration. If using Kubernetes service discovery the `address`
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tag is also added indicating the discovered ip address.
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### Example Output:
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**Source**
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```
# HELP go_gc_duration_seconds A summary of the GC invocation durations.
# TYPE go_gc_duration_seconds summary
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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
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# HELP go_goroutines Number of goroutines that currently exist.
# TYPE go_goroutines gauge
go_goroutines 15
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# 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
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```
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**Output**
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```
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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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```