opentelemetry-ext-js VS RabbitMQ

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

Although they did not make it into production, I experimented with the RabbitMQ message broker, Python (Django, Flask), Kubernetes + minikube, JWT, and NGINX. This was a hobby project, but I intended to learn about microservices along the way.

Messaging/Queueing Systems (Amazon SQS, RabbitMQ, Beanstalkd)

Later, we discovered Propan, a library created by Nikita Pastukhov, which solved similar problems but for RabbitMQ. Recognizing the potential for collaboration, we joined forces with Nikita to build a unified library that could work seamlessly with both Kafka and RabbitMQ. And that's how FastStream came to be—a solution born out of the need for simplicity and efficiency in microservices development.

Inter-Service Communication: Middleware provides communication channels and protocols that enable microservices to communicate with each other. This can include message brokers like RabbitMQ, Apache Kafka, RPC frameworks like gRPC, or RESTful APIs.

This is an implementation of pub/sub. The publisher is on a separate project. The message broker is Azure Service Bus. We use NServiceBus for code implementation. I use rabbitMQ broker for local tests. Nothing I can do about the tech stack. This is more of a high level single project structure review 😅

RabbitMQ is a robust and highly configurable open-source message broker that implements the Advanced Message Queuing Protocol (AMQP).

When using third-party services, especially within a "transaction", it's often a good idea to use a persistent Message Queue (MQ) system like RabbitMQ. Go through all their tutorials to get a really good understanding of how message queues work and how they can be used to solve your problem.

The best technical solution to provide the event queues is to use a message-broker technology like RabbitMQ.