API reference

Collectors

An application using the metrics module has 4 primitives (called «collectors») at its disposal:

• Counter
• Gauge
• Histogram
• Summary

A collector represents one or more observations that are changing over time.

Labels

All collectors support providing label_pairs on data modification. Labels are basically a metainfo that you associate with a metric in the format of key-value pairs. See tags in Graphite and labels in Prometheus. Labels are used to differentiate the characteristics of a thing being measured. For example, in a metric associated with the total number of http requests, you can use methods and statuses label pairs:

http_requests_total_counter:inc(1, {method = 'POST', status = '200'})

You don’t have to predefine labels in advance.

Using labels on your metrics allows you to later derive new time series (visualize their graphs) by specifying conditions on label values. In the example above, we could derive these time series:

1. The total number of requests over time with method = «POST» (and any status).
2. The total number of requests over time with status = 500 (and any method).

You can also set global labels by calling metrics.set_global_labels({ label = value, ...}).

Metrics functions

metrics.enable_default_metrics()

Enables Tarantool metrics collections. See metrics reference for details.

metrics.enable_cartridge_metrics()

Enables Cartridge metrics collections. See metrics reference for details.

metrics.set_global_labels(label_pairs)

Set global labels that will be added to every observation.

Параметры:	label_pairs (table) – Table containing label names as string keys, label values as values (table).

Global labels are applied only on metrics collection and have no effect on how observations are stored.

Global labels can be changed on the fly.

Observation label_pairs has priority over global labels: if you pass label_pairs to an observation method with the same key as some global label, the method argument value will be used.

metrics.register_callback(callback)

Registers a function callback which will be called right before metrics collection on plugin export.

Параметры:	callback (function) – Function which takes no parameters.

Most common usage is for gauge metrics updates.

Collecting HTTP requests latency statistics

metrics also provides a middleware for monitoring HTTP (set by the http module) latency statistics.

metrics.http_middleware.configure_default_collector(type_name, name, help)

Registers a collector for the middleware and sets it as default.

Параметры:	type_name (string) – Collector type: «histogram» or «summary». Default is «histogram». name (string) – Collector name. Default is «http_server_request_latency». help (string) – Help description. Default is «HTTP Server Request Latency».

If a collector with the same type and name already exists in the registry, throws an error.

metrics.http_middleware.build_default_collector(type_name, name[, help])

Registers a collector for the middleware and returns it.

Параметры:	type_name (string) – Collector type: «histogram» or «summary». Default is «histogram». name (string) – Collector name. Default is «http_server_request_latency». help (string) – Help description. Default is «HTTP Server Request Latency».

If a collector with the same type and name already exists in the registry, throws an error.

metrics.http_middleware.set_default_collector(collector)

Sets the default collector.

Параметры:	collector – Middleware collector object.

metrics.http_middleware.get_default_collector()

Returns the default collector. If the default collector hasn’t been set yet, registers it (with default http_middleware.build_default_collector(...) parameters) and sets it as default.

metrics.http_middleware.v1(handler, collector)

Latency measure wrap-up for HTTP ver. 1.x.x handler. Returns a wrapped handler.

Параметры:	handler (function) – Handler function. collector – Middleware collector object. If not set, uses the default collector (like in http_middleware.get_default_collector()).

Usage: httpd:route(route, http_middleware.v1(request_handler, collector))

For a more detailed example, see https://github.com/tarantool/metrics/blob/master/example/HTTP/latency_v1.lua

metrics.http_middleware.v2(collector)

Returns the latency measure middleware for HTTP ver. 2.x.x.

Параметры:	collector – Middleware collector object. If not set, uses the default collector (like in http_middleware.get_default_collector()).

Usage:

router = require('http.router').new()
router:route(route, request_handler)
router:use(http_middleware.v2(collector), {name = 'http_instrumentation'}) -- the second argument is optional, see HTTP docs

For a more detailed example, see https://github.com/tarantool/metrics/blob/master/example/HTTP/latency_v2.lua

CPU usage metrics

CPU metrics work only on Linux. See metrics reference for details. To enable it you should register callback:

local metrics = require('metrics')

metrics.register_callback(function()
    local cpu_metrics = require('metrics.psutils.cpu')
    cpu_metrics.update()
end)

Collected metrics example

# HELP tnt_cpu_total Host CPU time
# TYPE tnt_cpu_total gauge
tnt_cpu_total 15006759
# HELP tnt_cpu_thread Tarantool thread cpu time
# TYPE tnt_cpu_thread gauge
tnt_cpu_thread{thread_name="coio",file_name="init.lua",thread_pid="699",kind="system"} 160
tnt_cpu_thread{thread_name="tarantool",file_name="init.lua",thread_pid="1",kind="user"} 949
tnt_cpu_thread{thread_name="tarantool",file_name="init.lua",thread_pid="1",kind="system"} 920
tnt_cpu_thread{thread_name="coio",file_name="init.lua",thread_pid="11",kind="user"} 79
tnt_cpu_thread{thread_name="coio",file_name="init.lua",thread_pid="699",kind="user"} 44
tnt_cpu_thread{thread_name="coio",file_name="init.lua",thread_pid="11",kind="system"} 294

Prometheus query aggregated by thread name

sum by (thread_name) (idelta(tnt_cpu_thread[$__interval]))
  / scalar(idelta(tnt_cpu_total[$__interval]) / tnt_cpu_count)

Examples

Below are examples of using metrics primitives.

Notice that this usage is independent of export-plugins such as Prometheus / Graphite / etc. For documentation on plugins usage, see their the Metrics plugins section.

Using counters:

local metrics = require('metrics')

-- create a counter
local http_requests_total_counter = metrics.counter('http_requests_total')

-- somewhere in the HTTP requests middleware:
http_requests_total_counter:inc(1, {method = 'GET'})

Using gauges:

local metrics = require('metrics')

-- create a gauge
local cpu_usage_gauge = metrics.gauge('cpu_usage', 'CPU usage')

-- register a lazy gauge value update
-- this will be called whenever the export is invoked in any plugins
metrics.register_callback(function()
    local current_cpu_usage = math.random()
    cpu_usage_gauge:set(current_cpu_usage, {app = 'tarantool'})
end)

Using histograms:

local metrics = require('metrics')

-- create a histogram
local http_requests_latency_hist = metrics.histogram(
    'http_requests_latency', 'HTTP requests total', {2, 4, 6})

-- somewhere in the HTTP requests middleware:
local latency = math.random(1, 10)
http_requests_latency_hist:observe(latency)

Using summaries:

local metrics = require('metrics')

-- create a summary
local http_requests_latency = metrics.summary(
    'http_requests_latency', 'HTTP requests total',
    {[0.5]=0.01, [0.9]=0.01, [0.99]=0.01}
)

-- somewhere in the HTTP requests middleware:
local latency = math.random(1, 10)
http_requests_latency:observe(latency)