You are right, you don’t need Celery at all. When you are designing a distributed system there are a lot of options and there is no right way to do things that fits all situations. Many people find that it is more flexible to have pools of message consumers waiting for a message to appear … Read more
you could use redis with the lightning fast node_redis client. It even has built-in pubsub semantics.
Kafka uses the abstraction of a distributed log that consists of partitions. Splitting a log into partitions allows to scale-out the system. Keys are used to determine the partition within a log to which a message get’s appended to. While the value is the actual payload of the message. The examples are actually not very … Read more
Message Bus A Message Bus is a messaging infrastructure to allow different systems to communicate through a shared set of interfaces(message bus). Source: EIP Message Queue The basic idea of a message queue is a simple one: Two (or more) processes can exchange information via access to a common system message queue. The sending process … Read more
Your question is a bit messy but Let’s see its bits one by one. General concept: The Java Message Service (JMS) API is a Java Message Oriented Middleware (MOM) API for sending messages between two or more clients. JMS is a part of the Java Platform, Enterprise Edition, and is defined by a specification developed … Read more
Here the simplest algorithm, if you want just to drop messages when they arrive too quickly (instead of queuing them, which makes sense because the queue might get arbitrarily large): rate = 5.0; // unit: messages per = 8.0; // unit: seconds allowance = rate; // unit: messages last_check = now(); // floating-point, e.g. usec … Read more
JMS (ActiveMQ is a JMS broker implementation) can be used as a mechanism to allow asynchronous request processing. You may wish to do this because the request take a long time to complete or because several parties may be interested in the actual request. Another reason for using it is to allow multiple clients (potentially … Read more
Rabbit’s queues reside in memory and will therefore be much faster than implementing this in a database. A (good)dedicated message queue should also provide essential queuing related features such as throttling/flow control, and the ability to choose different routing algorithms, to name a couple(rabbit provides these and more). Depending on the size of your project, … Read more
When you use a web service you have a client and a server: If the server fails the client must take responsibility to handle the error. When the server is working again the client is responsible of resending it. If the server gives a response to the call and the client fails the operation is … Read more
RabbitMQ is a solid, general-purpose message broker that supports several protocols such as AMQP, MQTT, STOMP, etc. It can handle high throughput. A common use case for RabbitMQ is to handle background jobs or long-running task, such as file scanning, image scaling or PDF conversion. RabbitMQ is also used between microservices, where it serves as … Read more