liftbridge VS RabbitMQ

Liftbridge (https://liftbridge.io/) is more or less the NATS Kafka versioning.

[Gufo Liftbridge](https://pypi.org/project/gufo-liftbridge/) is the Python asyncio Liftbridge client.

https://liftbridge.io/

Apache Pulsar might be worth a look, but it's actually more complex under the hood than Kafka, but has a lot of features built-in that either aren't in FOSS Kafka yet, like tiered storage, or won't be until Confluent doesn't dominate the PMC (like an integrated schema registry), or just can't be done very nicely, if at all, like decent multi-tenancy.

That said, it's a fast moving target, the code quality last I looked was patchy in places, ditto the documentation for both it and Bookkeeper, and the admin overhead is higher (managing bookies and brokers and Zookeepers vs. just brokers and ZK with Kafka, or when KRaft is production ready, just brokers).

This is basically an ad for GCP right?

That said, it looks like Kafka is by far and away the way to handle persistent logs/events at scale. AFAIK a company here in Japan called LINE has all their messaging flowing through a large kafka cluster themselves.

Wonder if anyone is running large NATS Jetstream[0]/Liftbridge[1] or Pulsar[2] (yahoo runs those) clusters. I guess Pulsar might be #2 in terms of adoption at large scale?

[0]: https://docs.nats.io/jetstream/jetstream

[1]: https://liftbridge.io/

[2]: https://pulsar.apache.org/

Do you need the messages to be durable, if so you can have a look at Liftbridge: - https://liftbridge.io/ - https://github.com/liftbridge-io/liftbridge

And if you want closer kafka semantics built on top of nats, check out liftbridge:

https://liftbridge.io/

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.