API reference

Collectors

An application using the metrics module has 4 primitives, called collectors, at its disposal:

A collector represents one or more observations that change over time.

Labels

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

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

You don’t have to predefine labels in advance.

With labels, you can extract new time series (visualize their graphs) by specifying conditions with regard to label values. The example above allows extracting the following 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.cfg([config])¶

Entrypoint to setup the module. Since 0.17.0.

Параметры:

config (table) – module configuration options: cfg.include (string/table, default 'all'): 'all to enable all supported default metrics, 'none' to disable all default metrics, table with names of the default metrics to enable a specific set of metrics. cfg.exclude (table, default {}): table containing the names of the default metrics that you want to disable. Has higher priority than cfg.include. cfg.labels (table, default {}): table containing label names as string keys, label values as values.

You can work with metrics.cfg as a table to read values, but you must call metrics.cfg{} as a function to update them.

Supported default metric names (for cfg.include and cfg.exclude tables):

• network
• operations
• system
• replicas
• info
• slab
• runtime
• memory
• spaces
• fibers
• cpu
• vinyl
• memtx
• luajit
• cartridge_issues
• cartridge_failover
• clock
• event_loop

See metrics reference for details. All metric collectors from the collection have metainfo.default = true.

cfg.labels are the global labels to be added to every observation.

Global labels are applied only to metric collection. They have no effect on how observations are stored.

Global labels can be changed on the fly.

label_pairs from observation objects have 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.

Note that both label names and values in label_pairs are treated as strings.

metrics.enable_default_metrics([include, exclude])¶

Same as metrics.cfg{include=include, exclude=exclude}, but include={} is treated as include='all' for backward compatibility.

metrics.set_global_labels(label_pairs)¶

Same as metrics.cfg{labels=label_pairs}.

metrics.collect([opts])¶

Collect observations from each collector.

Параметры:	opts (table) – table of collect options: invoke_callbacks – if true, invoke_callbacks() is triggerred before actual collect. default_only – if true, observations contain only default metrics (metainfo.default = true).

object registry¶

registry:unregister(collector)¶

Remove a collector from the registry.

Параметры:	collector (collector_obj) – the collector to be removed.

Example:

local collector = metrics.gauge('some-gauge')

-- after a while, we don't need it anymore

metrics.registry:unregister(collector)

registry:find(kind, name)¶

Find a collector in the registry.

Параметры:	kind (string) – collector kind (counter, gauge, histogram, or summary). name (string) – collector name.
Return:	A collector object or nil.
Rtype:	collector_obj

Example:

local collector = metrics.gauge('some-gauge')

collector = metrics.registry:find('gauge', 'some-gauge')

metrics.register_callback(callback)¶

Register a function named callback, which will be called right before metric collection on plugin export.

Параметры:	callback (function) – a function that takes no parameters.

This method is most often used for gauge metrics updates.

Example:

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

metrics.unregister_callback(callback)¶

Unregister a function named callback that is called right before metric collection on plugin export.

Параметры:	callback (function) – a function that takes no parameters.

Example:

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

metrics.register_callback(cpu_callback)

-- after a while, we don't need that callback function anymore

metrics.unregister_callback(cpu_callback)

metrics.invoke_callbacks()¶

Invoke all registered callbacks. Has to be called before each collect(). (Since version 0.16.0, you may use collect{invoke_callbacks = true} instead.) If you’re using one of the default exporters, invoke_callbacks() will be called by the exporter.

Metrics role API

Below are the functions that you can call with metrics = require('cartridge.roles.metrics') specified in your init.lua.

metrics.set_export(export)¶

Параметры:	export (table) – a table containing paths and formats of the exported metrics.

Configure the endpoints of the metrics role:

local metrics = require('cartridge.roles.metrics')
metrics.set_export({
    {
        path = '/path_for_json_metrics',
        format = 'json'
    },
    {
        path = '/path_for_prometheus_metrics',
        format = 'prometheus'
    },
    {
        path = '/health',
        format = 'health'
    }
})

You can add several entry points of the same format but with different paths, for example:

metrics.set_export({
    {
        path = '/path_for_json_metrics',
        format = 'json'
    },
    {
        path = '/another_path_for_json_metrics',
        format = 'json'
    },
})

metrics.set_default_labels(label_pairs)¶

Add default global labels. Note that both label names and values in label_pairs are treated as strings.

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

local metrics = require('cartridge.roles.metrics')
metrics.set_default_labels({ ['my-custom-label'] = 'label-value' })

Collecting HTTP request latency statistics

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

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

Register a collector for the middleware and set it as default.

Параметры:	type_name (string) – collector type: histogram or summary. The default is histogram. name (string) – collector name. The default is http_server_request_latency. help (string) – collector description. The default is HTTP Server Request Latency.

Possible errors:

• A collector with the same type and name already exists in the registry.

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

Register and return a collector for the middleware.

Параметры:	type_name (string) – collector type: histogram or summary. The default is histogram. name (string) – collector name. The default is http_server_request_latency. help (string) – collector description. The default is HTTP Server Request Latency.
Return:	A collector object.

Possible errors:

• A collector with the same type and name already exists in the registry.

metrics.http_middleware.set_default_collector(collector)¶

Set the default collector.

Параметры:	collector – middleware collector object.

metrics.http_middleware.get_default_collector()¶

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

Return:	A collector object.

metrics.http_middleware.v1(handler, collector)¶

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

Параметры:	handler (function) – handler function. collector – middleware collector object. If not set, the default collector is used (like in http_middleware.get_default_collector()).

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

See GitHub for a more detailed example.

CPU usage metrics

CPU metrics work only on Linux. See the metrics reference for details.

To enable CPU metrics, first register a callback function:

local metrics = require('metrics')

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

metrics.register_callback(cpu_callback)

Collected metrics example:

# HELP tnt_cpu_time Host CPU time
# TYPE tnt_cpu_time gauge
tnt_cpu_time 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)

All psutils metric collectors have metainfo.default = true.

To clear CPU metrics when you don’t need them anymore, remove the callback and clear the collectors with a method:

metrics.unregister_callback(cpu_callback)
cpu_metrics.clear()

Examples

Below are some examples of using metric primitives.

Notice that this usage is independent of export plugins such as Prometheus, Graphite, etc. For documentation on how to use the plugins, see 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 export is invoked in any plugins
metrics.register_callback(function()
    local current_cpu_usage = some_cpu_collect_function()
    cpu_usage_gauge:set(current_cpu_usage, {app = 'tarantool'})
end)

Using histograms:

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

-- somewhere in the HTTP request middleware:

local t0 = fiber.clock()
observable_function()
local t1 = fiber.clock()

local latency = t1 - t0
http_requests_latency_hist:observe(latency)

Using summaries:

local metrics = require('metrics')
local fiber = require('fiber')

-- create a summary with a window of 5 age buckets and a bucket lifetime of 60 s
local http_requests_latency = metrics.summary(
    'http_requests_latency', 'HTTP requests total',
    {[0.5]=0.01, [0.9]=0.01, [0.99]=0.01},
    {max_age_time = 60, age_buckets_count = 5}
)

-- somewhere in the HTTP requests middleware:
local t0 = fiber.clock()
observable_function()
local t1 = fiber.clock()

local latency = t1 - t0
http_requests_latency:observe(latency)