ts_opentelemetry_otlp

Crates.iots_opentelemetry_otlp
lib.rsts_opentelemetry_otlp
version0.13.0-beta.1
sourcesrc
created_at2023-06-19 12:56:49.172332
updated_at2023-06-19 12:56:49.172332
descriptionThis is a fork of the exporter for the OpenTelemetry Collector
homepagehttps://github.com/ThetaSinner/opentelemetry-rust
repositoryhttps://github.com/ThetaSinner/opentelemetry-rust
max_upload_size
id894098
size137,399
raw-window-metal (github:rust-windowing:raw-window-metal)

documentation

README

OpenTelemetry — An observability framework for cloud-native software.

OpenTelemetry Collector Rust Exporter

OTLP integration for applications instrumented with OpenTelemetry.

Crates.io: opentelemetry-otlp Documentation LICENSE GitHub Actions CI Slack

Overview

OpenTelemetry is a collection of tools, APIs, and SDKs used to instrument, generate, collect, and export telemetry data (metrics, logs, and traces) for analysis in order to understand your software's performance and behavior.

This crate provides an exporter for sending trace and metric data in the OTLP format to the OpenTelemetry collector. The OpenTelemetry Collector offers a vendor-agnostic implementation on how to receive, process, and export telemetry data. In addition, it removes the need to run, operate, and maintain multiple agents/collectors in order to support open-source telemetry data formats (e.g. Jaeger, Prometheus, etc.) sending to multiple open-source or commercial back-ends.

Quickstart

First make sure you have a running version of the opentelemetry collector you want to send data to:

$ docker run -p 4317:4317 otel/opentelemetry-collector-dev:latest

Then install a new pipeline with the recommended defaults to start exporting telemetry:

use opentelemetry::trace::Tracer;

fn main() -> Result<(), Box<dyn std::error::Error + Send + Sync + 'static>> {
    // use tonic as grpc layer here.
    // If you want to use grpcio. enable `grpc-sys` feature and use with_grpcio function here.
    let tracer = opentelemetry_otlp::new_pipeline()
      .tracing()
      .with_exporter(opentelemetry_otlp::new_exporter().tonic())
      .install_simple()?;

    tracer.in_span("doing_work", |cx| {
        // Traced app logic here...
    });

    Ok(())
}

Performance

For optimal performance, a batch exporter is recommended as the simple exporter will export each span synchronously on drop. You can enable the [rt-tokio], [rt-tokio-current-thread] or [rt-async-std] features and specify a runtime on the pipeline builder to have a batch exporter configured for you automatically.

[dependencies]
opentelemetry = { version = "*", features = ["async-std"] }
opentelemetry-otlp = { version = "*", features = ["grpc-sys"] }
let tracer = opentelemetry_otlp::new_pipeline()
    .install_batch(opentelemetry::runtime::AsyncStd)?;

Kitchen Sink Full Configuration

Example showing how to override all configuration options.

Generally there are two parts of configuration. One is metrics config or tracing config. Users can config it via [OtlpTracePipeline] or [OtlpMetricPipeline]. The other is exporting configuration. Users can set those configurations using [OtlpExporterPipeline] based on the choice of exporters.

Grpc libraries comparison

Multiple gRPC transport layers are available. tonic is the default gRPC transport layer and is enabled by default. grpcio is optional.

gRPC transport layer hyperium/tonic tikv/grpc-rs
Feature --features=default --features=grpc-sys
gRPC library tonic grpcio
Transport hyperium/hyper (Rust) grpc/grpc (C++ binding)
TLS support yes yes
TLS library rustls OpenSSL
TLS optional yes yes
Supported .proto generator prost prost, protobuf
Commit count: 642

cargo fmt