Maple Rust style
SkillMonitoring & opsLets your agent set up Rust code with OpenTelemetry tracing that sends telemetry data to Maple.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Maple Rust style skill
About this capability
Rust OpenTelemetry style for Maple: opentelemetry + opentelemetry_sdk + opentelemetry-otlp HTTP exporter, tracing-opentelemetry bridge for the tracing crate, inline endpoint + ingest key, semconv resource attributes.
What this skill tells your AI
The instructions your AI receives, as published by mapletechlabs/maple in skills/maple-rust-style/SKILL.md and read by ahel’s review.
Use the official opentelemetry + opentelemetry_sdk crates with opentelemetry-otlp (HTTP exporter, not gRPC). Bridge the tracing crate via tracing-opentelemetry so existing info! / error! calls flow through OTLP.
Cargo.toml
[dependencies]
opentelemetry = "0.27"
opentelemetry_sdk = { version = "0.27", features = ["rt-tokio"] }
opentelemetry-otlp = { version = "0.27", features = ["http-proto", "reqwest-client", "logs", "metrics"] }
opentelemetry-semantic-conventions = "0.27"
tracing = "0.1"
tracing-subscriber = { version = "0.3", features = ["env-filter"] }
tracing-opentelemetry = "0.28"
Bootstrap
Inline the endpoint and ingest key — they're a project-scoped, write-only token (Sentry-DSN-shaped).
use opentelemetry::{global, KeyValue};
use opentelemetry_otlp::{LogExporter, MetricExporter, Protocol, SpanExporter, WithExportConfig};
use opentelemetry_sdk::{
logs::LoggerProvider, metrics::SdkMeterProvider, trace::TracerProvider, Resource,
};
use opentelemetry_semantic_conventions::resource::{
DEPLOYMENT_ENVIRONMENT_NAME, SERVICE_NAME,
};
use tracing_subscriber::{layer::SubscriberExt, util::SubscriberInitExt};
const MAPLE_ENDPOINT: &str = "https://ingest.maple.dev";
const MAPLE_KEY: &str = "MAPLE_TEST"; // set by maple-onboard skill on pairing
pub fn init() -> Result<(TracerProvider, LoggerProvider, SdkMeterProvider), opentelemetry_otlp::ExporterBuildError> {
let auth = format!("Bearer {MAPLE_KEY}");
let mut headers = std::collections::HashMap::new();
headers.insert("authorization".to_string(), auth);
let resource = Resource::builder()
.with_attributes([
KeyValue::new(SERVICE_NAME, "orders-api"),
KeyValue::new(DEPLOYMENT_ENVIRONMENT_NAME, std::env::var("DEPLOYMENT_ENV").unwrap_or_else(|_| "development".into())),
KeyValue::new("vcs.repository.url.full", "https://github.com/acme/orders-api"),
KeyValue::new("vcs.ref.head.revision", std::env::var("GITHUB_SHA").unwrap_or_default()),
])
.build();
let trace_exporter = SpanExporter::builder()
.with_http()
.with_endpoint(format!("{MAPLE_ENDPOINT}/v1/traces"))
.with_headers(headers.clone())
.with_protocol(Protocol::HttpJson)
.build()?;
let tracer_provider = TracerProvider::builder()
.with_batch_exporter(trace_exporter)
.with_resource(resource.clone())
.build();
global::set_tracer_provider(tracer_provider.clone());
let log_exporter = LogExporter::builder()
.with_http()
.with_endpoint(format!("{MAPLE_ENDPOINT}/v1/logs"))
.with_headers(headers.clone())
.with_protocol(Protocol::HttpJson)
.build()?;
let logger_provider = LoggerProvider::builder()
.with_batch_exporter(log_exporter)
.with_resource(resource.clone())
.build();
let metric_exporter = MetricExporter::builder()
.with_http()
.with_endpoint(format!("{MAPLE_ENDPOINT}/v1/metrics"))
.with_headers(headers)
.with_protocol(Protocol::HttpJson)
.build()?;
let meter_provider = SdkMeterProvider::builder()
.with_periodic_exporter(metric_exporter)
.with_resource(resource)
.build();
global::set_meter_provider(meter_provider.clone());
let otel_layer = tracing_opentelemetry::layer().with_tracer(global::tracer("orders.api"));
let otel_log_layer = opentelemetry_appender_tracing::layer::OpenTelemetryTracingBridge::new(&logger_provider);
tracing_subscriber::registry()
.with(tracing_subscriber::EnvFilter::from_default_env())
.with(tracing_subscriber::fmt::layer())
.with(otel_layer)
.with(otel_log_layer)
.init();
Ok((tracer_provider, logger_provider, meter_provider))
}
Call from main and shut down on exit:
#[tokio::main]
async fn main() {
let (tracer_provider, logger_provider, meter_provider) =
telemetry::init().expect("telemetry init");
// app run …
let _ = tracer_provider.shutdown();
let _ = logger_provider.shutdown();
let _ = meter_provider.shutdown();
}
Bounded business spans via tracing
The point of bridging tracing is so existing instrumentation works unchanged. Use #[tracing::instrument] on bounded async operations:
#[tracing::instrument(name = "order.submit", skip_all, fields(order.id = %order_id))]
async fn submit_order(order_id: &str) -> Result<(), Error> {
charge_order(order_id).await?;
Ok(())
}
tracing::error! and ?err field interpolation will record the exception and set the span status to ERROR via the bridge.
Coexistence
If the project already uses tracing with a Honeycomb / Datadog / Jaeger layer, leave it in place — add Maple's tracing-opentelemetry layer alongside. Don't strip the existing exporter unless the user asks.
Signals
- GitHub stars
- 2k
- Forks
- 117
- Last commit
- Sep 2026
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maple-rust-style- Source
- github.com/mapletechlabs/maple