Metrics Developer Guide#

This guide explains how to create and use custom metrics in Dynamo components using the Dynamo metrics API.

Metrics Exposure#

All metrics created via the Dynamo metrics API are automatically exposed on the /metrics HTTP endpoint in Prometheus Exposition Format text when the following environment variable is set:

  • DYN_SYSTEM_PORT=<port> - Port for the metrics endpoint (set to positive value to enable, default: -1 disabled)

Example:

DYN_SYSTEM_PORT=8081 python -m dynamo.vllm --model <model>

Prometheus Exposition Format text metrics will be available at: http://localhost:8081/metrics

Metric Name Constants#

The prometheus_names.rs module provides centralized metric name constants and sanitization functions to ensure consistency across all Dynamo components.

Metrics API in Rust#

The metrics API is accessible through the .metrics() method on runtime, namespace, component, and endpoint objects. See Runtime Hierarchy for details on the hierarchical structure.

Available Methods#

  • .metrics().create_counter(): Create a counter metric

  • .metrics().create_gauge(): Create a gauge metric

  • .metrics().create_histogram(): Create a histogram metric

  • .metrics().create_countervec(): Create a counter with labels

  • .metrics().create_gaugevec(): Create a gauge with labels

  • .metrics().create_histogramvec(): Create a histogram with labels

Creating Metrics#

use dynamo_runtime::DistributedRuntime;

let runtime = DistributedRuntime::new()?;
let endpoint = runtime.namespace("my_namespace").component("my_component").endpoint("my_endpoint");

// Simple metrics
let requests_total = endpoint.metrics().create_counter(
    "requests_total",
    "Total requests",
    &[]
)?;

let active_connections = endpoint.metrics().create_gauge(
    "active_connections",
    "Active connections",
    &[]
)?;

let latency = endpoint.metrics().create_histogram(
    "latency_seconds",
    "Request latency",
    &[],
    Some(vec![0.001, 0.01, 0.1, 1.0, 10.0])
)?;

Using Metrics#

// Counters
requests_total.inc();

// Gauges
active_connections.set(42.0);
active_connections.inc();
active_connections.dec();

// Histograms
latency.observe(0.023);  // 23ms

Vector Metrics with Labels#

// Create vector metrics with label names
let requests_by_model = endpoint.metrics().create_countervec(
    "requests_by_model",
    "Requests by model",
    &["model_type", "model_size"],
    &[]
)?;

let memory_by_gpu = endpoint.metrics().create_gaugevec(
    "gpu_memory_bytes",
    "GPU memory by device",
    &["gpu_id", "memory_type"],
    &[]
)?;

// Use with specific label values
requests_by_model.with_label_values(&["llama", "7b"]).inc();
memory_by_gpu.with_label_values(&["0", "allocated"]).set(8192.0);

Advanced Features#

Custom histogram buckets:

let latency = endpoint.metrics().create_histogram(
    "latency_seconds",
    "Request latency",
    &[],
    Some(vec![0.001, 0.01, 0.1, 1.0, 10.0])
)?;

Constant labels:

let counter = endpoint.metrics().create_counter(
    "requests_total",
    "Total requests",
    &[("region", "us-west"), ("env", "prod")]
)?;
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