What factors should you consider when selecting a message queue for your application?

If you are following a reactive event driven architecture then it is always recommended to go for the publish -subscribe model. Here the publisher can publish a message regarding some event that has happened, the key here is to communicate what has happened and not direct other systems as to what it should do or perform. This design allows for scalability and flexibility, the publisher is not aware of the consumers hence systems are decoupled making future changes easier to make. Reducing system cohesion is of the key aspect of this pattern.

At-most-once is recommended when the data is changing quickly and it does not matter if you drop few as it will anyways be stale. For example, stock prices during a trading session, the publisher will keep publishing it and if the subscriber does not get one then they can always pick up the next one. At-least-once is the most commonly used in transactional system when there is change in state. For example, a shopping cart being submitted, order handling, financial transactions . In this case the queueing system will resend the message if it is not sure that the subscriber has received it. This may result in duplicate messages being received by the subscriber and it is the subscriber’s responsibility to perform the duplicate check.

It's also vital to consider the flexibility and configurability of these features in the message queue system. Some applications may require dynamic adjustment of priorities based on changing conditions or the ability to re-order messages in response to specific events. Therefore, selecting a message queue that allows for customizable order and priority settings can be crucial for applications operating in rapidly changing environments or with evolving business logic. This level of control ensures that your application can adapt to different scenarios, maintaining efficiency and effectiveness in its message handling.

It is crucial to evaluate the performance implications of these aspects. Larger message sizes can impact the speed of transmission and processing, potentially leading to bottlenecks in high-throughput systems. Conversely, too small a message size might lead to inefficiencies due to overhead in message handling. Therefore, finding a balance that suits your application's needs is essential.

Architecture ilities is one of the important aspects when selecting a message queue for at-scale usage: 1. Scalability 2. High availability 3. Reliability 4. Interoperability and many others. Choose the ilities that become the most concerns when implementing use cases

I would strongly consider a queue speed control to balance input rate against output rate. The message feeding system speed usually difers from the message consuming speed, so it is possible to face the following cases: a) Huge queue because of high number of puts and few number of gets: Possible middleware overload. b) No queue because of fewer puts than thet the number of gets: Slow down performance of the consuming system. c) Balanced puts and gets to sustain an acceptable queue length for both the feeding system and the consuming system: Overall performance balanced. There are several implementation approaches for this common problem but only few providers and developers consider a queue speed control mechanism.