Open Source ChromeOS Distributed Tracing Tools

Odigos supports any application written in Java, Python, .NET, Node.js and Go. Historically, compiled languages like Go have been difficult to instrument without code changes. Odigos solves this problem by uniquely leveraging eBPF. Odigos currently supports all the popular managed and open source destinations. By producing data in the OpenTelemetry format, Odigos can be used with any observability tool that supports OTLP. Odigos automatically scales OpenTelemetry collectors based on observability data volume. Manage and configure collectors via a convenient web UI. Installing Odigos takes less than 5 minutes, and requires no code changes.

Brave is a distributed tracing instrumentation library. Brave typically intercepts production requests to gather timing data, correlate and propagate trace contexts. While typically trace data is sent to Zipkin server, third-party plugins are available to send to alternate services such as Amazon X-Ray. This repository includes dependency-free Java libraries and instrumentation for common components used in production services. For example, this includes trace filters for Servlet and log correlation for Apache Log4J. Brave's dependency-free tracer library works against JRE6+. This is the underlying api that instrumentation use to time operations and add tags that describe them. This library also includes code that parses X-B3-TraceId headers.

Kamon Telemetry is a set of libraries for instrumenting applications running on the JVM. With Kamon Telemetry you can collect metrics, propagate context across threads and services, and get distributed traces automatically. The best way to get started is by following our installation guides and taking it from there. Have fun with Kamon. Monitor your backend applications, fix performance issues, and get alerted when problems happen. All without being a monitoring expert. Everybody starts monitoring with logs because they are there by default. Just connect to your server and start tailing. But logs have a hard time showing you the overall response times for your application, or whether certain calls to the database are happening in sequence or parallel (among a million other things).

Autoconfigures and runs the embedded gRPC server with @GRpcService-enabled beans as part of the spring-boot application. If you are using Spring Boot Dependency Management plugin, it might pull not the same version as the version this started was compiled against, causing binary incompatibility issue.

Spring Boot starter module for gRPC framework.

Spring Cloud Sleuth provides Spring Boot auto-configuration for distributed tracing. Sleuth configures everything you need to get started. This includes where trace data (spans) are reported to, how many traces to keep (sampling), if remote fields (baggage) are sent, and which libraries are traced. Add Spring Cloud Sleuth to the classpath of a Spring Boot application (together with a Tracer implementation) and you will see trace IDs in logs.