Prometheus.jl/docs/src/index.md

Prometheus.jl

Introduction

This package is a Julia client for Prometheus. If you are not familiar with Prometheus it is recommended to browse the upstream documentation. The documentation here focuses on the Julia client.

Two of the basic concepts of a Prometheus client are Registries and Collectors. Registries are collections of collectors, and the collectors are the units responsible to record and capture metrics. Client libraries implement a default registry which all collectors implicity register with, so for basic usage there is no need to interact with a registry (see Default registry).

The third important concept is Exposition of the collected metrics. Typically metrics are exposed over a HTTP server, as in the Quickstart-example just below. See the section about Exposition for more details and examples on how metrics can be exposed.

Quickstart

1. Install Prometheus.jl and HTTP.jl using the package manager:

   pkg> add Prometheus HTTP
   

2. Paste the following code into a Julia REPL.

   # Load the packages
   using Prometheus, HTTP
   
   # Create a Counter metric
   const request_counter = Prometheus.Counter("request_count", "Number of handled requests")
   
   # Start a HTTP server on localhost port 8000 to server the metrics
   server = HTTP.listen!(8000) do http
       Prometheus.inc(request_counter) # Increment the request counter
       return Prometheus.expose(http)  # Expose the metrics
   end
   

3. Visit http://localhost:8000 in your browser. You will see something like the following

   # HELP gc_alloc_bytes_total Total number of allocated bytes
   # TYPE gc_alloc_bytes_total counter
   gc_alloc_bytes_total 365578814
   
   [...]
   
   # HELP request_count Number of handled requests
   # TYPE request_count counter
   request_count 1
   

   The output contains some default metrics related to the running process, as well as the request counter that we added ourselves. Every time you refresh, the counter will increment its value. close(server) will shutdown the server.

Collectors

This section documents the collectors that are currently supported. This include the "basic" collectors (Counter, Gauge, Summary) as well as some custom collectors (GCCollector, ProcessCollector). There is also a section on how to implement your own collector, see Custom collectors.

Upstream documentation:

• https://prometheus.io/docs/concepts/metric_types/
• https://prometheus.io/docs/instrumenting/writing_clientlibs/#metrics

Counter

Quoting the upstream documentation:

A counter is a cumulative metric that represents a single monotonically increasing counter whose value can only increase or be reset to zero on restart. For example, you can use a counter to represent the number of requests served, tasks completed, or errors.

Do not use a counter to expose a value that can decrease. For example, do not use a counter for the number of currently running processes; instead use a gauge.

Counter API reference

Prometheus.Counter(::String, ::String; kwargs...)
Prometheus.inc(::Prometheus.Counter, ::Any)

Gauge

Quoting the upstream documentation:

A gauge is a metric that represents a single numerical value that can arbitrarily go up and down.

Gauges are typically used for measured values like temperatures or current memory usage, but also "counts" that can go up and down, like the number of concurrent requests.

Gauge API reference

Prometheus.Gauge(::String, ::String; kwargs...)
Prometheus.inc(::Prometheus.Gauge, ::Any)
Prometheus.dec(::Prometheus.Gauge, ::Any)
Prometheus.set(::Prometheus.Gauge, ::Any)
Prometheus.set_to_current_time(::Prometheus.Gauge)

Summary

Quoting the upstream documentation:

Similar to a histogram, a summary samples observations (usually things like request durations and response sizes). While it also provides a total count of observations and a sum of all observed values, it calculates configurable quantiles over a sliding time window.

Summary API reference

Prometheus.Summary(::String, ::String; kwargs...)
Prometheus.observe(::Prometheus.Summary, ::Any)

GCCollector

A collector that exports metrics about allocations and garbage collection (for example number of allocations, number of bytes allocated, time spent in garbage collection, etc). These metrics have the gc_ prefix in their name.

ProcessCollector

A collector that exports metrics about a running process, for example CPU seconds and metrics about I/O operations. Metrics from this collector have the process_ prefix in their name. This collector is only available on Linux since it requires the /proc file system.

A ProcessCollector for the current process is registered automatically with the default registry, see Default registry for more details.

ProcessCollector API reference

Prometheus.ProcessCollector(::Function; kwargs...)

Custom collectors

RandomCollector

Labels

See https://prometheus.io/docs/concepts/data_model/#metric-names-and-labels for details.

All metrics can be labeled using the special Prometheus.Family collector. For example, a labeled Counter collector

labelnames = ["endpoint", "status_code"]
counter_family = Prometheus.Family{Prometheus.Collector}(
    "http_requests",
    "Number of processed requests",
    labelnames,
)

Supported methods:

• Prometheus.labels(family, ["label 1", "label 2"]): extract the child collector corresponding to the labels ["label 1", "label 2"].
• Prometheus.remove(family, ["label 1", "label 2"]): remove the child collector corresponding to the labels ["label 1", "label 2"].
• Prometheus.clear(family): clear all child collectors.

Registries

Default registry

Exposition

Prometheus support

Prometheus.expose