opentelemetry-java-instrumentation VS opentelemetry-ext-js

Java

wget https://github.com/open-telemetry/opentelemetry-java-instrumentation/releases/latest/download/opentelemetry-javaagent.jar

We are actually able to handle the long tail of tracing by leveraging the amazing open source community. For languages like Java we use the automatic instrumentation created by the OpenTelemetry community which is really great and support ton of libraries, you can see a list of supported libraries here: https://github.com/open-telemetry/opentelemetry-java-instrum...

As in Python, it creates spans for every method call and HTTP entry point. It also instruments JDBC calls, but we have a Reactive stack and thus use R2DBC. For the record, a GitHub issue is open for adding support.

Download the latest Java agent ‘JAR’ from the official repo on GitHub and copy the opentelemetry-javaagent-all.jar file to your project.

Java OpenTelemetry MongoDB library for Java applications

Download the latest version of the Java JAR agent, and copy jar agent file in your application code. We have placed the agent under the folder named agents.

OpenTelemetry and Java Flight Recorder (JFR) cover most bases. Use the OpenTelemetry Java agent if you want auto-instrumentation or just the APIs if you want to do your own instrumentation.

Download the latest Java JAR agent.

OpenTelemetry provides three repositories to instrument applications. The opentelemetry-java-instrumentation repo contains the code for auto-instrumentation of Java applications.

AWS has good tools for tracing, but in this example, I will use another remote and distributed tracing platform – Aspecto.

For this article, I will be using Aspecto to visualize my traces. You can follow along by quickly creating a free account.

If we drill down into one of these traces, we can see in more detail how long each request took and clear visualization of the entire workflow.

For the purposes of this guide, I chose to use Aspecto as my visualization tool. This is because Aspecto provides built-in support for visualizing messaging systems like Kafka (and, of course, any other part of our microservice architectures).

To follow along, you can open a new free-forever Aspecto account or log in to your existing one.

That’s about it for this OpenTelemetry Java guide, folks. If you have any questions or issues with any of these steps, feel free to reach out to us via chat or join our OpenTelemetry Slack channel (part of the CNCF Slack).

At Aspecto, you can sign up for free and use our generous free-forever plan (no limited features).

Aspecto has a free-forever tier and provides everything included in Jaeger and more. Sort of like Jaeger on steroids.

However, you can take your tracing visualization to the next level with Aspecto. Try it yourself with the free-forever plan that has no limited features.

Hi all, we wanted to share some love back to the Kafka community. We hope you'd find this instrumentation helpful, check it out on GitHub 🌟and npm