Work queues
LavinMQ is commonly used for work queues, where it distributes tasks among multiple workers. This allows tasks to be processed in parallel, and prevents any single worker from becoming overloaded. LavinMQ ensures that tasks are not lost, even if some workers fail. This setup keeps the workload balanced and contributes to the system's operational stability.
Stream Queues in LavinMQ manage streaming data, like traditional queues but optimized for real-time data flow. This design ensures that all consumers can access the required data without unnecessary duplication. It is ideal for large fanouts because multiple consumers can read the same stream. Consumers can also navigate through streams for immediate use or to review past events.
Read more in the documentationInternet of Things (IoT)
IoT involves connecting many devices that rely on constant data exchange for monitoring, automation, and analysis. LavinMQ enables reliable communication between devices, users and systems, and is specifically built to manage the high volume of connections typical of IoT environments.
Internal communication (Microservices)
LavinMQ supports internal communication by reliably passing messages between different parts of a system. It uses message queues to enable asynchronous sharing of information, making it easier to build flexible and scalable applications.
Legacy system integration
LavinMQ helps older systems work with newer ones. It enables modern applications and legacy systems to exchange data efficiently through messages that can be transmitted asynchronously.
Distributed systems
In distributed systems, LavinMQ acts as a reliable middleman, ensuring effective communication across multiple servers. It guarantees messages reach their destinations. LavinMQ can manage sudden increases in activity and enables maintenance on one part of the system without disrupting the entire service.
RPC
LavinMQ supports RPC through its message queuing features, which help handle RPC requests in a queued manner. It allows clients to both send RPC requests and receive responses simultaneously. This capability helps manage multiple RPC calls, making RPC implementations with LavinMQ scalable and responsive.
