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Prometheus Metric Library for Zig

This library is designed for both library and application developers. I do hope to streamline setup when comptime allocations are allowed.

It supports, counters, gauges and histograms and the labeled-variant of each.

Please see the example project. It demonstrates how a library developer, and how an application developer can initialize and output them.

Metric Setup

Setup is a bit tedious, and I welcome suggestions for improvement.

Let's start with a basic example. While the metrics within this library can be used directly, I believe that each library/application should create its own Metrics struct that encapsulates all metrics. A global instance of this struct can be created and initialized at comptime into a "noop" state.

const m = @import("metrics");

// defaults to noop metrics, making this safe to use
// whether or not initializeMetrics is called
var metrics = m.initializeNoop(Metrics);

const Metrics = struct {
    // counter can be a unsigned integer or floats
    hits: m.Counter(u32),

    // gauge can be an integer or float
    connected: m.Gauge(u16),
};

// meant to be called within the application
pub fn hit() void {
    metrics.hits.incr();
}

// meant to be called within the application
pub fn connected(value: u16) void {
    metrics.connected.set(value);
}

// meant to be called once on application startup
pub fn initializeMetrics(comptime opts: m.RegistryOpts) !void {
    metrics = .{
        .hits = m.Counter(u32).init("hits", .{}, opts),
        .connected = m.Gauge(u16).init("connected", .{}, opts),
    };
}

// thread safe
pub fn writeMetrics(writer: anytype) !void {
    return m.write(&metrics, writer);
}

The call to m.initializeNoop(Metrics) creates a Metrics and initializes each metric (hits, connected and latency) to a "noop" implementation (tagged unions are used). The initializeMetrics is called on application startup and sets these metrics to real implementation.

For library developers, this means their global metrics are always safe to use (all methods call noop). For application developers, it gives them control over which metrics to enable.

All metrics take a name and two options. Why two options? The first is designed for library developers, the second is designed to give application developers additional control.

Currently the first option has a single field:

  • help: ?[]const u8 = nulls - Used to generate the # HELP $HELP output line

The second option should has two fields:

  • prefix: []const u8 = "" - Appends prefix to the start of each metric name.
  • exclude: ?[]const []const u8 = null - A list of metric names to exclude (not including the prefix).

CounterVec, GaugeVec, Histogram and HistogramVec also require an allocator.

Note for Library Developers

Library developers are free to change the above as needed. However, having libraries consistently expose an initializeMetrics and writeMetrics should help application developers.

Library developers should ask their users to call try initializeMetrics(allocator, .{}) on startup and try writeMetrics(writer) to generate the metrics.

The RegistryOpts parameter should be supplied by the application and passed to each metric-initializer as-is.

Labels (vector-metrics)

Every metric type supports a vectored variant. This allows labels to be attached to metrics. This metrics require an std.mem.Allocator and, as you'll see in the metric API section, most of their methods can fail.

var metrics = m.initializeNoop(Metrics);

const Metrics = struct {
    hits: m.CounterVec(u32, struct{status: u16, name: []const u8}),
};

// All labeled metrics require an allocator
pub fn initializeMetrics(allocator: Allocator, opts: m.RegistryOpts) !void {
    metrics = .{
        .hits = try m.CounterVec(u32, struct{status: u16, name: []const u8}).init(allocator, "hits", .{}, opts),
    };
}

The labels are strongly types. Valid label types are: ErrorSet, Enum, Type, Bool, Int and []const u8

The CounterVec(u32, ...) has to be typed twice: once in the definition of Metrics and once in initializeMetrics. This can be improved slightly.

var metrics = m.initializeNoop(Metrics);

const Metrics = struct {
    hits: Hits,

    const Hits = m.CounterVec(u32, struct{status: u16, name: []const u8});
};

pub fn initializeMetrics(allocator: Allocator, opts: m.RegistryOpts) !void {
    metrics = .{
        .hits = try Metrics.Hits.init(allocator, "hits", .{}, opts),
    };
}

// Labels are compile-time checked. Using "anytype" here
// is just lazy so we don't have to declare the label structure
pub fn hit(labels: anytype) !void {    
    return metrics.hits.incr(labels);
}

The above would be called as:

// import your metrics file
const metrics = @import("metrics.zig");
metrics.hit(.{.status = 200, .path = "/about.txt"});

Internally, every metric is a union between a "noop" and an actual implementation. This allows metrics to be globally initialized as noop and then enabled on startup. The benefit of this approach is that library developers can safely and easily use their metrics whether or not the application has enabled them.

Histograms

Histograms are setup like Counter and Gauge, and have a vectored-variant, but they require a comptime list of buckets:

const Metrics = struct {
    latency: Latency,

    const Latency = m.Histogram(f32, &.{0.005, 0.01, 0.05, 0.1, 0.25, 1, 5, 10});
};

pub fn initializeMetrics(opts: m.RegistryOpts) !void {
    metrics = .{
        .latency = Metrics.Latency.init("hits", .{}, opts),
    };
}

The HistogramVec is even more verbose, requiring the label struct and bucket list. And, like all vectored metrics, requires an std.mem.Allocator and can fail:

var metrics = m.initializeNoop(Metrics);

const Metrics = struct {
    latency: Latency,

    const Latency = m.HistogramVec(
        u32,
        struct{path: []const u8},
        &.{5, 10, 25, 50, 100, 250, 500, 1000}
    );
};

pub fn initializeMetrics(allocator: Allocator, opts: m.RegistryOpts) !void {
    metrics = .{
        .latency = try Metrics.Latency.init(allocator, "hits", .{}, opts),
    };
}

// Labels are compile-time checked. Using "anytype" here
// is just lazy so we don't have to declare the label structure
// Would be called as:
//   @import("metrics.zig").recordLatency(.{.path = "robots.txt"}, 2);
pub fn recordLatency(labels: anytype, value: u32) !void {
    return metrics.latency.observe(labels, value);
}

Metrics

Utility

The package exposes the following utility functions.

initializeNoop(T) T

Creates an initializes metric T with noop implementation of every metric field. T should contain only metrics (Counter, Gauge, Historgram or their vectored variants) and primitive fields (int, bool, []const u8, enum, float).

initializeNoop(T) will set any non-metric field to its default value.

This method is designed to allow a global "metrics" instance to exist and be safe to use within libraries.

write(metrics: anytype, writer anytype) !void

Calls the write(writer) !void method on every metric field within metrics.

Library developers are expected to wrap this method in a writeMetric(writer: anytype) !void function. This function requires a pointer to your metrics.

Counter(T)

A Counter(T) is used for incrementing values. T can be an unsigned integer or a float. Its two main methods are incr() and incrBy(value: T). incr() is a short version of incrBy(1).

init(comptime name: []const, comptime opts: Opts, comptime ropts: RegistryOpts) !Counter(T)

Initializes the counter.

Opts is:

  • help: ?[]const - optional help text to include in the prometheus output

incr(self: *Counter(T)) void

Increments the counter by 1.

incrBy(self: *Counter(T), value: T) void

Increments the counter by value.

write(self: *const Counter(T), writer: anytype) !void

Writes the counter to writer.

CounterVec(T, L)

A CounterVec(T, L) is used for incrementing values with labels. T can be an unsigned integer or a float. L must be a struct where the field names and types will define the lables. Its two main methods are incr(labels: L) and incrBy(labels: L, value: T). incr(L) is a short version of incrBy(L, 1).

init(allocator: Allocator, comptime name: []const, comptim eopts: Opts, comptime ropts: RegistryOpts) !CounterVec(T, L)

Initializes the counter. Name must be given at comptime.

Opts is:

  • help: ?[]const - optional help text to include in the prometheus output

deinit(self: *CounterVec(T, L)) void

Deallocates the counter

incr(self: *CounterVec(T, L), labels: L) !void

Increments the counter by 1. Vectored metrics can fail.

incrBy(self: *CounterVec(T, L), labels: L, value: T) !void

Increments the counter by value. Vectored metrics can fail.

remove(self: *CounterVec(T, L), labels: L) void

Removes the labeled value from the counter. Safe to call if labels is not an existing label.

write(self: *CounterVec(T, L), writer: anytype) !void

Writes the counter to writer.

Gauge(T)

A Gauge(T) is used for setting values. T can be an integer or a float. Its main methods are incr(), incrBy(value: T) and set(value: T). incr() is a short version of incrBy(1).

init(comptime name: []const, comptime opts: Opts, comptime ropts: RegistryOpts) !Gauge(T)

Initializes the gauge. Name must be given at comptime.

Opts is:

  • help: ?[]const - optional help text to include in the prometheus output

incr(self: *Gauge(T)) void

Increments the gauge by 1.

incrBy(self: *Gauge(T), value: T) void

Increments the gauge by value.

set(self: *Gauge(T), value: T) void

Sets the the gauge to value.

write(self: *Gauge(T), writer: anytype) !void

Writes the gauge to writer.

GaugeVec(T, L)

A GaugeVec(T, L) is used for incrementing values with labels. T can be an integer or a float. L must be a struct where the field names and types will define the lables. Its main methods are incr(labels: L), incrBy(labels: L, value: T) and set(labels: L, value: T). incr(L) is a short version of incrBy(L, 1).

init(allocator: Allocator, comptime name: []const, comptime opts: Opts, comptime ropts: RegistryOpts) !GaugeVec(T, L)

Initializes the gauge. Name must be given at comptime.

Opts is:

  • help: ?[]const - optional help text to include in the prometheus output

deinit(self: *GaugeVec(T, L)) void

Deallocates the gauge

incr(self: *GaugeVec(T, L), labels: L) !void

Increments the gauge by 1. Vectored metrics can fail.

incrBy(self: *GaugeVec(T, L), labels: L, value: T) !void

Increments the gauge by value. Vectored metrics can fail.

set(self: *GaugeVec(T, L), labels: L, value: T) !void

Sets the gauge to value. Vectored metrics can fail.

remove(self: *GaugeVec(T, L), labels: L) void

Removes the labeled value from the gauge. Safe to call if labels is not an existing label.

write(self: *GaugeVec(T, L), writer: anytype) !void

Writes the gauge to writer.

Histogram(T, []T)

A Histogram(T, []T) is used to track the size and frequency of events. T can be an unsigned integer or a float. Its main methods is observe(T).

Observed valued will fall within one of the provided buckets, []T. The buckets must be in ascending order. A final "infinite" bucket should not be provided.

init(comptime name: []const, comptime opts: Opts, comptime ropts: RegistryOpts) !Histogram(T, []T)

Initializes the histogram. Name must be given at comptime.

Opts is:

  • help: ?[]const - optional help text to include in the prometheus output

observe(self: *Histogram(T, []T), value: T) void

Observes value, bucketing it based on the provided comptime buckets.

write(self: *Histogram(T, []T), writer: anytype) !void

Writes the histogram to writer.

Histogram(T, L, []T)

A Histogram(T, L, []T) is used to track the size and frequency of events. T can be an unsigned integer or a float. L must be a struct where the field names and types will define the lables. Its main methods is observe(T).

Observed valued will fall within one of the provided buckets, []T. The buckets must be in ascending order. A final "infinite" bucket should not be provided.

init(allocator: Allocator, comptime name: []const, comptime opts: Opts, comptime ropts: RegistryOpts) !Histogram(T, L, []T)

Initializes the histogram. Name must be given at comptime.

Opts is:

  • help: ?[]const - optional help text to include in the prometheus output

deinit(self: *Histogram(T, L, []T)) void

Deallocates the histogram

observe(self: Histogram(T, L, []T), value: T) void

Observes value, bucketing it based on the provided comptime buckets.

remove(self: *Histogram(T, L, []T), labels: L) void

Removes the labeled value from the histogram. Safe to call if labels is not an existing label.

write(self: Histogram(T, L, []T), writer: anytype) !void

Writes the histogram to writer.