cluster-operator VS RabbitMQ

Alternatively, you can use RabbitMQ configuration files to declare multiple types of RabbitMQ objects, including vhosts, channels, exchanges, and queues. This method provides a more structured approach to managing RabbitMQ resources and configurations.

Currently we run the SFS using podManagementPolicy: ordered, and have a list of 3 availability zones to start in, which starts pod 0 first in say us-east-1a, then pod 1 in us-east-1b, pod 2 in us-east-1c. This works fine however we've hit some scenarios where if there's multiple node restarts in multiple zones where rabbit pods are sitting the cluster can become unavailable and won't restart. As per this issue the fix is to run podManagementPolicy: parallel which will not require the lower number pods to be fully Ready before starting the higher.

RabbitMQ uses distributed deployment mechanism. You can set up instances in a highly available manner. Just like Memphis, RabbitMQ is cloud available. This allows you to run a highly available cluster on top of infrastructure such as kubernetes in the cloud.

kubectl apply -f https://github.com/rabbitmq/cluster-operator/releases/latest/download/cluster-operator.yml

Today, I will discuss some things that need to be considered to have a kind of reliable server when using Rabbitmq as a message broker.

Choose a consistent communication protocol for inter-service communication. Common protocols include HTTP, gRPC, and message brokers like RabbitMQ or Kafka. NestJS supports various communication strategies, allowing you to choose the one that best fits your needs.

Some simple best practices around performing RabbitMQ upgrades.

ℹ️ Manage quorum queues easily by using the rabbitmq-queues CLI. Here are some useful CLI commands.

RabbitMQ is an open-source message broker that implements the Advanced Message Queuing Protocol (AMQP). Its primary purpose is to facilitate reliable and efficient communication between different components of a distributed system. RabbitMQ acts as an intermediary, receiving messages from producers and forwarding them to consumers, ensuring that messages are delivered even if the receiving application is temporarily unavailable.

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 😅