We are planning to introduce both, pub-sub and request-reply communication models to our micriservices architecture. Both communication models are needed.
One of the solutions could be using RabbitMQ as it can provide both models and provide HA, clusterring ang other interesting features.
RabbitMQ request-reply model requires using queues, both for input and for output messages. Only one service can read from the input queue and this increases coupling.
Is there any other recommended solution for using both request-reply and pub-sub communication models in the same system? Does service mesh could be a better option?
It shall be suppoered by node.js, python and. Net CORE.
Thank you for your help
There multiple pub-sub and request-reply support HA communication models :
1. Kafka
Kafka relies heavily on the filesystem for storing and caching messages. All data is immediately written to a persistent log on the filesystem without necessarily flushing to disk. In effect this just means that it is transferred into the kernel’s pagecache.
Kafka is designed with failure in mind. At some point in time, web communications or storage resources fail. When a broker goes offline, one of the replicas becomes the new leader for the partition. When the broker comes back online, it has no leader partitions. Kafka keeps track of which machine is configured to be the leader. Once the original broker is back up and in a good state, Kafka restores the information it missed in the interim and makes it the partition leader once more.
See :
2. Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Redis has built-in replication, Lua scripting, LRU eviction, transactions and different levels of on-disk persistence, and provides high availability via Redis Sentinel and automatic partitioning with Redis Cluster.
See :
3. ZeroMQ
ZeroMQ (also known as ØMQ, 0MQ, or zmq) looks like an embeddable networking library but acts like a concurrency framework. It gives you sockets that carry atomic messages across various transports like in-process, inter-process, TCP, and multicast. You can connect sockets N-to-N with patterns like fan-out, pub-sub, task distribution, and request-reply. It's fast enough to be the fabric for clustered products. Its asynchronous I/O model gives you scalable multicore applications, built as asynchronous message-processing tasks. It has a score of language APIs and runs on most operating systems.
See :
4. RabbitMQ
RabbitMQ is lightweight and easy to deploy on premises and in the cloud. It supports multiple messaging protocols. RabbitMQ can be deployed in distributed and federated configurations to meet high-scale, high-availability requirements.