iapetos

iapetos is a Clojure wrapper around the Prometheus Java Client, providing idiomatic and simple access to commonly used functionality while retaining low-level flexibility for tackling more complex tasks.

Basic Usage

Registering Metrics

Documentation

All metrics have to be registered with a collector registry before being used:

(require '[iapetos.core :as prometheus])

(defonce registry
  (-> (prometheus/collector-registry)
      (prometheus/register
        (prometheus/histogram :app/duration-seconds)
        (prometheus/gauge     :app/active-users-total)
        (prometheus/counter   :app/runs-total))
      (prometheus/register-lazy
        (prometheus/gauge     :app/last-success-unixtime))))

Now, they are ready to be set and changed:

(-> registry
    (prometheus/inc     :app/runs-total)
    (prometheus/observe :app/duration-seconds 0.7)
    (prometheus/set     :app/active-users-total 22))

The registry itself implements clojure.lang.IFn to allow access to all registered metrics (plus setting of metric labels), e.g.:

(registry :app/duration-seconds)
;; => #object[io.prometheus.client.Histogram$Child ...]

All metric operations can be called directly on such a collector, i.e.:

(prometheus/inc     (registry :app/runs-total))
(prometheus/observe (registry :app/duration-seconds) 0.7)
(prometheus/set     (registry :app/active-users-total) 22)

Metric Export

Documentation

Metrics can be transformed into a textual representation using iapetos.export/text-format:

(require '[iapetos.export :as export])

(print (export/text-format registry))
;; # HELP app_active_users_total a gauge metric.
;; # TYPE app_active_users_total gauge
;; app_active_users_total 22.0
;; # HELP app_runs_total a counter metric.
;; # TYPE app_runs_total counter
;; app_runs_total 1.0
;; ...

This could now be exposed e.g. using an HTTP endpoint (see also iapetos' Ring integration or the standalone server ).

Metric Push

Documentation

Another way of communicating metrics to Prometheus is using push mechanics, intended to be used for e.g. batch jobs that might not live long enough to be scraped in time. Iapetos offers a special kind of registry for this:

(require '[iapetos.export :as export])

(defonce registry
  (-> (export/pushable-collector-registry
        {:push-gateway "push-gateway-host:12345"
         :job          "my-batch-job"})
      (prometheus/register ...)))
...
(export/push! registry)

Note that you can reduce the amount of boilerplate in most cases down to something like:

(export/with-push-gateway [registry {:push-gateway "...", :job "..."}]
  (-> registry
      (prometheus/register
        (prometheus/counter :app/rows-inserted-total)
        ...)
      (run-job! ...)))

Labels

Prometheus allows for labels to be associated with metrics which can be declared for each collector before it is registered:

(def job-latency-histogram
  (prometheus/histogram
    :app/job-latency-seconds
    {:description "job execution latency by job type"
     :labels [:job-type]
     :buckets [1.0 5.0 7.5 10.0 12.5 15.0]}))

(defonce registry
  (-> (prometheus/collector-registry)
      (prometheus/register job-latency-histogram)))

Now, you can lookup a collector bound to a set of labels by calling the registry with a label/value-map:

(prometheus/observe (registry :app/job-latency-seconds {:job-type "pull"}) 14.2)
(prometheus/observe (registry :app/job-latency-seconds {:job-type "push"}) 8.7)

(print (export/text-format registry))
;; # HELP app_job_latency_seconds job execution latency by job type
;; # TYPE app_job_latency_seconds histogram
;; app_job_latency_seconds_bucket{job_type="pull",le="1.0",} 0.0
;; app_job_latency_seconds_bucket{job_type="pull",le="5.0",} 0.0
;; ...
;; app_job_latency_seconds_bucket{job_type="push",le="1.0",} 0.0
;; app_job_latency_seconds_bucket{job_type="push",le="5.0",} 0.0
;; ...

Subsystems

In addition to namespaces, you can create collector declarations belonging to a subsystem, i.e.:

(prometheus/counter
  :app/job-runs-total
  {:description "the total number of finished job executions."
   :subsystem "worker"})

But this reduces its reusability - you might want to register the above counter twice in different subsystems without having to create it anew - which is why iapetos lets you specify the subsystem on the registry level:

(defonce registry
  (prometheus/collector-registry))

(defonce worker-registry
  (-> registry
      (prometheus/subsystem "worker")
      (prometheus/register ...)))

(defonce httpd-registry
  (-> registry
      (prometheus/subsystem "httpd")
      (prometheus/register ...)))

Now, collectors added to worker-registry and httpd-registry will have the appropriate subsystem. And when registry is exported it will contain all metrics that were added to the subsystems.

(Note, however, that the subsystem registries will not have access to the original registry's collectors, i.e. you have to reregister things like function instrumentation or Ring collectors.)

Features

Code Block Instrumentation

Documentation

iapetos provides a number of macros that you can use to instrument parts of your code, e.g. with-failure-timestamp to record the last time a task has thrown an error or with-duration to track execution time:

(prometheus/with-failure-timestamp (registry :app/last-worker-failure-unixtime)
  (prometheus/with-duration (registry :app/worker-latency-seconds)
    (run-worker! task)))

See the auto-generated documentation for all available macros or the function instrumentation section below on how to easily wrap them around existing functions.

JVM Metrics

Documentation

Some characteristics of your current JVM are always useful (e.g. memory usage, thread count, ...) and can be added to your registry using the iapetos.collector.jvm namespace:

(require '[iapetos.collector.jvm :as jvm])

(defonce registry
  (-> (prometheus/collector-registry)
      (jvm/initialize)))

Alternatively, you can selectively register the JVM collectors:

(defonce registry
  (-> (prometheus/collector-registry)
      (prometheus/register
        (jvm/standard)
        (jvm/gc)
        (jvm/memory-pools)
        (jvm/threads))))

Note: You need to include the artifact io.prometheus/simpleclient_hotspot explicitly in your project's dependencies.

Function Instrumentation

Documentation

To collect metrics about specific functions, you can use the functionality provided in iapetos.collector.fn:

(require '[iapetos.collector.fn :as fn])

(defn- run-the-job!
  [job]
  ...)

(defonce registry
  (-> (prometheus/collector-registry)
      ...
      (fn/initialize)))

(fn/instrument! registry #'run-the-job!)

Now, every call to run-the-job! will update a series of duration, success and failure metrics. Note, however, that re-evaluation of the run-the-job! declaration will remove the instrumentation again.

Ring

Documentation

iapetos.collector.ring offers middlewares to

• expose a iapetos collector registry via a fixed HTTP endpoint, and
• collect metrics for Ring handlers.

First, you need to initialize the available collectors in the registry:

(require '[iapetos.collector.ring :as ring])

(defonce registry
  (-> (prometheus/collector-registry)
      (ring/initialize)))

Afterwards, you can add the middlewares to your Ring stack:

(def app
  (-> (constantly {:status 200})
      (ring/wrap-metrics registry {:path "/metrics"})))

The following metrics will now be collected and exposed via the GET /metrics endpoint:

• http_requests_total
• http_request_latency_seconds
• http_exceptions_total

These are, purposefully, compatible with the metrics produced by prometheus-clj, as to allow a smooth migration.

Standalone HTTP Server

Documentation

A zero-dependency standalone HTTP server is included in iapetos.standalone and can be run using:

(require '[iapetos.standalone :as standalone])

(defonce httpd
  (standalone/metrics-server registry {:port 8080}))

This is particularly useful for applications that do not expose an HTTP port themselves but shall still be scraped by Prometheus. By default, metrics will be exposed at /metrics.

License

MIT License

Copyright (c) 2016 Yannick Scherer

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