2017-10-26 13:33:45 -07:00
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---
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title: Federation
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sort_rank: 6
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---
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# Federation
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Federation allows a Prometheus server to scrape selected time series from
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another Prometheus server.
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2023-01-12 00:03:45 -08:00
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_Note about native histograms (experimental feature): To scrape native histograms
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via federation, the scraping Prometheus server needs to run with native histograms
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enabled (via the command line flag `--enable-feature=native-histograms`), implying
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that the protobuf format is used for scraping. Should the federated metrics contain
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a mix of different sample types (float64, counter histogram, gauge histogram) for
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the same metric name, the federation payload will contain multiple metric families
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with the same name (but different types). Technically, this violates the rules of
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the protobuf exposition format, but Prometheus is nevertheless able to ingest all
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metrics correctly._
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2017-10-26 13:33:45 -07:00
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## Use cases
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There are different use cases for federation. Commonly, it is used to either
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achieve scalable Prometheus monitoring setups or to pull related metrics from
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one service's Prometheus into another.
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### Hierarchical federation
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Hierarchical federation allows Prometheus to scale to environments with tens of
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data centers and millions of nodes. In this use case, the federation topology
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resembles a tree, with higher-level Prometheus servers collecting aggregated
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time series data from a larger number of subordinated servers.
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For example, a setup might consist of many per-datacenter Prometheus servers
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that collect data in high detail (instance-level drill-down), and a set of
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global Prometheus servers which collect and store only aggregated data
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(job-level drill-down) from those local servers. This provides an aggregate
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global view and detailed local views.
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### Cross-service federation
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In cross-service federation, a Prometheus server of one service is configured
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to scrape selected data from another service's Prometheus server to enable
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alerting and queries against both datasets within a single server.
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For example, a cluster scheduler running multiple services might expose
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resource usage information (like memory and CPU usage) about service instances
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running on the cluster. On the other hand, a service running on that cluster
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will only expose application-specific service metrics. Often, these two sets of
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metrics are scraped by separate Prometheus servers. Using federation, the
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Prometheus server containing service-level metrics may pull in the cluster
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resource usage metrics about its specific service from the cluster Prometheus,
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so that both sets of metrics can be used within that server.
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## Configuring federation
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On any given Prometheus server, the `/federate` endpoint allows retrieving the
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current value for a selected set of time series in that server. At least one
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`match[]` URL parameter must be specified to select the series to expose. Each
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`match[]` argument needs to specify an
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[instant vector selector](querying/basics.md#instant-vector-selectors) like
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`up` or `{job="api-server"}`. If multiple `match[]` parameters are provided,
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the union of all matched series is selected.
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To federate metrics from one server to another, configure your destination
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Prometheus server to scrape from the `/federate` endpoint of a source server,
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while also enabling the `honor_labels` scrape option (to not overwrite any
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labels exposed by the source server) and passing in the desired `match[]`
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parameters. For example, the following `scrape_configs` federates any series
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with the label `job="prometheus"` or a metric name starting with `job:` from
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the Prometheus servers at `source-prometheus-{1,2,3}:9090` into the scraping
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Prometheus:
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```yaml
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scrape_configs:
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- job_name: 'federate'
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scrape_interval: 15s
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honor_labels: true
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metrics_path: '/federate'
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params:
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'match[]':
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- '{job="prometheus"}'
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- '{__name__=~"job:.*"}'
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static_configs:
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- targets:
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- 'source-prometheus-1:9090'
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- 'source-prometheus-2:9090'
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- 'source-prometheus-3:9090'
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2017-10-26 13:33:45 -07:00
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```
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