Memcached VS RabbitMQ

> Multiple clients racing can't be fixed.

Really? You can't think of a single way for multiple clients to operate on the same data without racing? (Here's a hint if you're still having trouble: https://github.com/memcached/memcached/wiki/Commands#cas.)

Memcached: A simple, open-source, distributed memory object caching system primarily used for caching strings. Best suited for lightweight, non-persistent caching needs.

Oh, thank you! I didn't realize that LRU Maintainer Thread was more than an expiration reaper. When it was first being introduced that was its first responsibility as lazy expiration removal by size eviction meant dead entries wasted capacity. It was all work in progress when I had read about it [1] and talked to dormando, so it got fuzzy. The compat code [2, 3] might have also thrown me off if I only looked at the setting and not the usage. Its a neat variant to all of these ideas.

[1] https://github.com/memcached/memcached/pull/97

stores session state in a session store like Memcached or Redis.

memcached has recently gained the ability to spill to disk: https://github.com/memcached/memcached/wiki/Extstore

we recently implemented this to grow our caches to >50TB

Django supports using Memcached as a cache backend. Memcached is a high-performance, distributed memory caching system that can be used to store cached data across multiple servers.

In server-side authentication, the session state is stored on the server-side, which can be scaled horizontally across multiple servers using tools like Redis or Memcached.

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.