9 releases
0.1.1 | Sep 7, 2023 |
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0.1.0 | Sep 7, 2023 |
0.0.7 | Apr 3, 2023 |
0.0.1 | Mar 31, 2023 |
#830 in Web programming
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18KB
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Datadog tracing and log correlation for Rust services.
Datadog has official support for Python, which includes various SDKs and
other utilities (such as the Python ddtrace
library)
for tracing and logging in Python applications.
They don't have similar support for Rust. However, they do support the OpenTelemetry format for both logs and traces. This crate contains the necessary glue to bridge the gap between OpenTelemetry and Datadog.
Features
ddtrace
has the following features:
- tracing: utilities for building an OpenTelemetry tracer/layer that sends traces to the Datadog agent
- log correlation: a log formatter that converts the trace ID and span ID to the Datadog native format and injects them into the
dd.trace_id
anddd.span_id
fields (more information) - propagation: a utility function to set the Datadog propagator as the global propagator
- axum (enabled via the
axum
feature): re-exposing the functionality of axum-tracing-opentelemetry
A Complete Example
The following is an example for using ddtrace
with the axum
feature enabled
to set up an axum
service with traces and logs sent to Datadog.
use std::net::SocketAddr;
use std::time::Duration;
use axum::{routing::get, Router};
use ddtrace::axum::opentelemetry_tracing_layer;
use ddtrace::formatter::DatadogFormatter;
use ddtrace::set_global_propagator;
use ddtrace::tracer::{build_layer, TraceResult};
use tracing_subscriber::layer::SubscriberExt;
use tracing_subscriber::util::SubscriberInitExt;
#[tokio::main]
async fn main() -> TraceResult<()> {
let service_name = std::env::var("DD_SERVICE").unwrap_or("my-service".to_string());
let tracing_layer = build_layer(&service_name)?;
tracing_subscriber::registry()
.with(tracing_subscriber::EnvFilter::new(
std::env::var("RUST_LOG").unwrap_or_else(|_| "info".into()),
))
.with(
tracing_subscriber::fmt::layer()
.json()
.event_format(DatadogFormatter),
)
.with(tracing_layer)
.init();
set_global_propagator();
let app = Router::new()
.route("/", get(root))
.layer(opentelemetry_tracing_layer())
.route("/health", get(health));
let addr = SocketAddr::from(([0, 0, 0, 0], 3025));
tracing::info!("listening on {}", addr);
axum::Server::bind(&addr)
.serve(app.into_make_service())
.with_graceful_shutdown(ddtrace::axum::shutdown_signal())
.await
.unwrap();
Ok(())
}
async fn root() -> &'static str {
do_something().await;
"Hello, World!"
}
#[tracing::instrument]
async fn do_something() {
tokio::time::sleep(Duration::from_millis(120)).await;
do_something_else().await;
tracing::info!("in the middle of doing something");
tokio::time::sleep(Duration::from_millis(10)).await;
do_something_else().await;
tokio::time::sleep(Duration::from_millis(20)).await;
}
#[tracing::instrument]
async fn do_something_else() {
tokio::time::sleep(Duration::from_millis(40)).await;
}
async fn health() -> &'static str {
"healthy"
}
Please refer to the complete project with the Cargo.toml
here.
Datadog Agent Setup
The Datadog agent needs to be configured to receive OTel traces over gRPC. Please refer to the Datadog documentation to set up the agent.
Further Context and Rationale
Exporting Traces
For traces, the official Datadog agent can ingest OTel trace data with the correct environment variable settings. The traces can be sent via either HTTP or gRPC. More information on this can be found here.
OpenTelemetry has an official Rust crate with extensions for major formats/providers. This includes a Datadog exporter. We have found this exporter to be less reliable than the standard OTel exporter sending data to the OTel endpoint of the Datadog agent, though. This crate builds on the OTel exporter.
Propagation
Two commonly used propagation standards are B3
(OpenZipkin's propagation style)
and Jaeger. OpenTelemetry supports both.
Most Datadog SDK's support both B3
and the Datadog native propagation style.
For example, the Python ddtrace
library supports B3
but it
needs to be explicitly enabled.
For ease of integration with services written in other languages that use the official Datadog SDK,
we opted for sticking with Datadog-style propagation over B3
. This is set via the
set_global_propagator
function.
Reqwest Propagation
The Python library takes care of propagation of the trace context automatically. Unfortunately, we need to do this manually in Rust.
Arguably, propagation in HTTP requests is the most common need.
This crate does not provide any additional support, but we recommend using
the reqwest-middleware crate
to inject the necessary headers when using reqwest
.
If you set the global propagator using ddtrace
, it will work out of the box.
use ddtrace::set_global_propagator;
use reqwest_middleware::{ClientBuilder, ClientWithMiddleware};
use reqwest_tracing::TracingMiddleware;
#[tokio::main]
async fn main() {
set_global_propagator();
client = get_http_client();
// configure tracing, setup your app and inject the client
}
fn get_http_client() -> ClientWithMiddleware {
ClientBuilder::new(reqwest::Client::new())
.with(TracingMiddleware::default())
.build()
}
Dependencies
~15–26MB
~381K SLoC