gem 'bc-prometheus-ruby'
Then in your application.rb
, prior to extending Rails::Application
or any initializers:
require 'bigcommerce/prometheus'
Then in your web server config file (e.g. puma.rb
)
before_fork do
Rails.application.config.before_fork_callbacks.each(&:call)
end
You can then view your metrics at: http://0.0.0.0:9394/metrics
For extra Puma metrics, add this to config/puma.rb
:
after_worker_fork do
Rails.application.config.after_fork_callbacks.each(&:call)
end
In your task 'resque:setup'
rake task, do:
require 'bigcommerce/prometheus'
Bigcommerce::Prometheus::Instrumentors::Resque.new(app: Rails.application).start
After requiring the main file, you can further configure with:
Option | Description | Default | Environment Variable |
---|---|---|---|
client_custom_labels | A hash of custom labels to send with each client request | {} |
None |
client_max_queue_size | The max amount of metrics to send before flushing | 10000 |
ENV['PROMETHEUS_CLIENT_MAX_QUEUE_SIZE'] |
client_thread_sleep | How often to sleep the worker thread that manages the client buffer (seconds) | 0.5 |
ENV['PROMETHEUS_CLIENT_THREAD_SLEEP'] |
puma_collection_frequency | How often to poll puma collection metrics (seconds) | 30 |
ENV['PROMETHEUS_PUMA_COLLECTION_FREQUENCY'] |
server_host | The host to run the exporter on | "0.0.0.0" |
ENV['PROMETHEUS_SERVER_HOST'] |
server_port | The port to run the exporter on | 9394 |
ENV['PROMETHEUS_SERVER_PORT'] |
server_thread_pool_size | The number of threads used for the exporter server | 3 |
ENV['PROMETHEUS_SERVER_THREAD_POOL_SIZE'] |
process_name | What the current process name is (used in logging) | "unknown" |
ENV['PROCESS'] |
railtie_disabled | Opt out flag for Railtie; use Bigcommerce::Prometheus::Instrumentors::Web.new(app: Rails.application).start in your app's code to start it up yourself |
0 |
ENV['PROMETHEUS_DISABLE_RAILTIE'] |
To create custom metrics and collectors, simply create two files: a collector (the class that runs and collects metrics), and the type collector, which runs on the threaded prometheus server and
First, create a type collector. Note that the "type" of this will be the full name of the class, with TypeCollector
stripped. This is important later. Our example here will have a "type" of "app".
class AppTypeCollector < ::Bigcommerce::Prometheus::TypeCollectors::Base
def build_metrics
{
honks: PrometheusExporter::Metric::Counter.new('honks', 'Running counter of honks'),
points: PrometheusExporter::Metric::Gauge.new('points', 'Current amount of points')
}
end
def collect_metrics(data:, labels: {})
metric(:points).observe(data.fetch('points', 0))
metric(:honks).observe(1, labels) if data.fetch('honks', 0).to_i.positive?
end
end
There are two important methods here: build_metrics
, which registers the different metrics you want to measure, and
collect_metrics
, which actually takes in the metrics and prepares them to be rendered so that Prometheus can scrape
them.
Note also in the example the different ways of observing Gauges vs Counters.
Next, create a collector. Your "type" of the Collector must match the type collector above, so that bc-prometheus-ruby knows how to map the metrics to the right TypeCollector. This is inferred from the class name. Here, it is "app":
class AppCollector < ::Bigcommerce::Prometheus::Collectors::Base
def honk!
push(
honks: 1,
custom_labels: {
volume: 'loud'
}
)
end
def collect(metrics)
metrics[:points] = rand(1..100)
metrics
end
end
There are two types of metrics here: on-demand, and polled. Let's look at the first:
To issue an on-demand metric (usually a counter) that then automatically updates, in your application code, you would then run:
app_collector = AppCollector.new
app_collector.honk!
This will "push" the metrics to our AppTypeCollector
instance, which will render them as:
# HELP ruby_honks Running counter of honks
# TYPE ruby_honks counter
ruby_honks{volume="loud"} 2
As you can see this will respect any custom labels we push in as well.
Using our same AppCollector, if you note the collect
method: this method will run on a 15 second polled basis
(the frequency of which is configurable in the initializer of the AppCollector). Here we're just spitting out random
points, so it'll look something like this:
# HELP ruby_points Current amount of points
# TYPE ruby_points gauge
ruby_points 42
Each different type of integration will need to have the collectors passed into them, where appropriate. For example, if we want these collectors to run on our web, resque, and hutch processes, we'll need to:
::Bigcommerce::Prometheus.configure do |c|
c.web_collectors = [AppCollector]
c.web_type_collectors = [AppTypeCollector.new]
c.resque_collectors = [AppCollector]
c.resque_type_collectors = [AppTypeCollector.new]
c.hutch_collectors = [AppCollector]
c.hutch_type_collectors = [AppTypeCollector.new]
end
For custom integrations that initialize their own server, you'll need to pass your TypeCollector instance via the
.add_type_collector
method on the prometheus server instance before starting it:
server = ::Bigcommerce::Prometheus::Server.new
Bigcommerce::Prometheus.web_type_collectors.each do |tc|
server.add_type_collector(tc)
end
# and for polling:
AppCollector.start
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