tomevault-io Metrics
Prometheus-compatible metrics for production monitoring.
Setup
# Cargo.toml
[dependencies]
metrics = "0.22"
metrics-exporter-prometheus = "0.13"
Initialize Prometheus Exporter
use metrics_exporter_prometheus::PrometheusBuilder;
fn init_metrics() -> Result<()> {
PrometheusBuilder::new()
.with_http_listener(([0, 0, 0, 0], 9090))
.install()?;
Ok(())
}
// Access metrics at http://localhost:9090/metrics
Counter (Monotonically Increasing)
use metrics::counter;
// Increment by 1
counter!("videos_processed_total").increment(1);
// With labels
counter!("http_requests_total", "method" => "GET", "status" => "200").increment(1);
// In a function
fn record_request(method: &str, status: u16) {
counter!(
"http_requests_total",
"method" => method.to_string(),
"status" => status.to_string()
).increment(1);
}
Gauge (Can Go Up or Down)
use metrics::gauge;
// Set absolute value
gauge!("gpu_vram_used_gb").set(8.5);
// Increment/decrement
gauge!("active_connections").increment(1.0);
gauge!("active_connections").decrement(1.0);
// With labels
gauge!("queue_depth", "queue" => "embedding").set(42.0);
Histogram (Distribution of Values)
use metrics::histogram;
// Record a value
histogram!("request_duration_seconds").record(0.125);
// With labels
histogram!(
"processing_duration_seconds",
"model" => "whisper",
"phase" => "inference"
).record(duration.as_secs_f64());
// Record timing
let start = std::time::Instant::now();
do_work();
histogram!("operation_duration_seconds").record(start.elapsed().as_secs_f64());
Describe Metrics
use metrics::{describe_counter, describe_gauge, describe_histogram, Unit};
fn describe_metrics() {
describe_counter!(
"videos_processed_total",
Unit::Count,
"Total number of videos processed"
);
describe_gauge!(
"gpu_vram_used_gb",
Unit::Gigabytes,
"Current GPU VRAM usage"
);
describe_histogram!(
"request_duration_seconds",
Unit::Seconds,
"Request processing time distribution"
);
}
Metrics Struct Pattern
use metrics::{counter, gauge, histogram};
pub struct ProcessorMetrics;
impl ProcessorMetrics {
pub fn record_video_processed(model: &str) {
counter!("videos_processed_total", "model" => model.to_string()).increment(1);
}
pub fn record_processing_time(model: &str, duration: std::time::Duration) {
histogram!(
"processing_duration_seconds",
"model" => model.to_string()
).record(duration.as_secs_f64());
}
pub fn set_queue_depth(queue: &str, depth: usize) {
gauge!("queue_depth", "queue" => queue.to_string()).set(depth as f64);
}
pub fn record_error(error_type: &str) {
counter!("processing_errors_total", "type" => error_type.to_string()).increment(1);
}
}
// Usage
ProcessorMetrics::record_video_processed("whisper");
ProcessorMetrics::record_processing_time("whisper", elapsed);
Scheduler Metrics Example
pub struct SchedulerMetrics {
model_switches: AtomicU64,
items_processed: DashMap<ModelType, u64>,
processing_times: DashMap<ModelType, f64>,
}
impl SchedulerMetrics {
pub fn new() -> Self {
Self {
model_switches: AtomicU64::new(0),
items_processed: DashMap::new(),
processing_times: DashMap::new(),
}
}
pub fn record_model_switch(&self, from: Option<ModelType>, to: ModelType) {
self.model_switches.fetch_add(1, Ordering::Relaxed);
counter!(
"model_switches_total",
"to" => format!("{:?}", to)
).increment(1);
}
pub fn record_batch_processed(&self, model: ModelType, count: u64, duration: Duration) {
*self.items_processed.entry(model).or_insert(0) += count;
counter!(
"items_processed_total",
"model" => format!("{:?}", model)
).increment(count);
histogram!(
"batch_processing_seconds",
"model" => format!("{:?}", model)
).record(duration.as_secs_f64());
}
pub fn export(&self) -> MetricsSnapshot {
MetricsSnapshot {
model_switches: self.model_switches.load(Ordering::Relaxed),
items_processed: self.items_processed.iter()
.map(|e| (*e.key(), *e.value()))
.collect(),
}
}
}
HTTP Endpoint Integration
use axum::{routing::get, Router};
use metrics_exporter_prometheus::{Matcher, PrometheusBuilder, PrometheusHandle};
fn setup_metrics() -> PrometheusHandle {
PrometheusBuilder::new()
.set_buckets_for_metric(
Matcher::Prefix("http_request".to_string()),
&[0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1.0, 5.0],
)
.unwrap()
.install_recorder()
.unwrap()
}
async fn metrics_handler(handle: axum::Extension<PrometheusHandle>) -> String {
handle.render()
}
#[tokio::main]
async fn main() {
let handle = setup_metrics();
let app = Router::new()
.route("/metrics", get(metrics_handler))
.layer(axum::Extension(handle));
axum::Server::bind(&"0.0.0.0:8080".parse().unwrap())
.serve(app.into_make_service())
.await
.unwrap();
}
Common Metric Patterns
// Request duration with status
fn record_request(method: &str, path: &str, status: u16, duration: Duration) {
let labels = [
("method", method.to_string()),
("path", path.to_string()),
("status", status.to_string()),
];
counter!("http_requests_total", &labels).increment(1);
histogram!("http_request_duration_seconds", &labels).record(duration.as_secs_f64());
}
// Error rate tracking
fn record_operation(success: bool, operation: &str) {
let status = if success { "success" } else { "error" };
counter!(
"operations_total",
"operation" => operation.to_string(),
"status" => status.to_string()
).increment(1);
}
// Resource utilization
fn update_resource_metrics(cpu: f64, memory: f64, disk: f64) {
gauge!("cpu_usage_percent").set(cpu);
gauge!("memory_usage_percent").set(memory);
gauge!("disk_usage_percent").set(disk);
}
Guidelines
- Use counters for things that only increase (requests, errors)
- Use gauges for things that go up and down (connections, memory)
- Use histograms for latency and size distributions
- Include relevant labels but avoid high cardinality
- Describe metrics with units and descriptions
- Expose metrics on standard port (9090 or /metrics endpoint)
- Use consistent naming:
<namespace>_<name>_<unit>
Examples
See hercules-local-algo/src/scheduler/metrics.rs for production metrics.
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