Peep (peep v4.2.0)
View SourceTelemetry.Metrics reporter supporting Statsd and Prometheus.
To use it, start the reporter with start_link/1, providing a list of
Telemetry.Metrics metric definitions in a Keyword list matching the schema
specified in Peep.Options:
import Telemetry.Metrics
Peep.start_link([
name: :my_peep,
metrics: [
counter("http.request.count"),
sum("http.request.payload_size"),
last_value("vm.memory.total"),
distribution("http.request.latency")
]
])To emit Statsd metrics, Peep supports both UDP and Unix Domain Sockets.
Why another Telemetry.Metrics library?
Both TelemetryMetricsStatsd and TelemetryMetrics.Prometheus are great
choices for emitting telemetry. However, Peep makes several different
choices that may not be as general-purpose as either of those libraries.
No sampled metrics
Sampling is a popular approach to reduce the amount of Statsd data flowing out
of a service, but naive sampling dramatically reduces visibility into the
shapes of distributions. Peep represents distributions using histograms,
using a small exponential function by default. This sacrifices some
granularity on individual samples, but one usually doesn't mind too much if a
sample value of 95 is rounded to 100, or if 950 is rounded to 1000.
These histograms are emitted to statsd using the optional sample rate of
1/$count.
Peep uses :atomics stored in :ets for performance. New :atomics arrays
are created when a metric with a new set of tags is observed, so there is a
slight overhead when handling the first telemetry event with a distinct set of
tags. Peep reporter processes are not involved in the handling of any
:telemetry events, so there's no chance of a single process becoming a
bottleneck.
Distributions are aggregated immediately
This is a consequence of choosing to represent distributions as
histograms. There is no step in Peep's processing where samples are
aggregated in large batches. This leads to a flatter performance profile when
scaling up.
Statsd packets are stuffed
This is something that is not (at the time of writing) supported by
TelemetryMetricsStatsd, but the need for stuffing packets became pretty
clear when handling tens of thousands of telemetry events every second. During
each reporting period, metrics collected by a Peep reporter will be
collected into a minimum number of packets. Users can set the maximum packet
size in Peep.Options.
Supported :reporter_options
:prometheus_type- when usingsum/2orlast_value/2you can use this option to define Prometheus' type used by such metric. By defaultsum/2usescounterandlast_value/2usesgauge. It can be useful when some values are already precomputed, for example presummed socket stats.
Summary
Functions
Returns a specification to start this module under a supervisor.
Fetches all metrics from the worker. Called when preparing Prometheus or StatsD data.
Fetches a single metric from storage. Currently only used in tests.
Removes metrics whose metadata contains the specified tag patterns.
Returns measurements about the size of a running Peep's storage, in number of ETS elements and in bytes of memory.
Types
@type metric_id() :: pos_integer()
Functions
Returns a specification to start this module under a supervisor.
See Supervisor.
Fetches all metrics from the worker. Called when preparing Prometheus or StatsD data.
Fetches a single metric from storage. Currently only used in tests.
Removes metrics whose metadata contains the specified tag patterns.
Example inputs:
[%{foo: :bar}, %{baz: :quux}]removes metrics withfoo == :barORbaz == :quux[%{foo: :bar, baz: :quux}]removes metrics withfoo == :barANDbaz == :quux[%{foo: :one}, %{foo: :two}]removes metrics withfoo == :oneORfoo == :two
@spec storage_size(atom()) :: %{size: non_neg_integer(), memory: non_neg_integer()}
Returns measurements about the size of a running Peep's storage, in number of ETS elements and in bytes of memory.