A previous post gave an introduction to stream filtering, a new and exciting feature in RabbitMQ 3.13. In this post we cover the internals of stream filtering. Knowing the design and implementation will help you to configure and use stream filtering in the most optimal way for your use cases.
Stream filtering is a new feature in RabbitMQ 3.13. It allows to save bandwidth between the broker and consuming applications when those applications need only a subset of the messages of a stream.
Keep reading to find out how stream filtering works and see it in action.
Native MQTT released in RabbitMQ 3.12 has delivered substantial scalability and performance improvements for IoT use cases.
RabbitMQ 3.13 will support MQTT 5.0 and will therefore be the next big step in our journey to make RabbitMQ one of the leading MQTT brokers.
This blog post explains how the new MQTT 5.0 features are used in RabbitMQ.
RabbitMQ 3.11 will bring a feature with one of the coolest names in its history: super streams. Super streams are a way to scale out by partitioning a large stream into smaller streams. They integrate with single active consumer to preserve message order within a partition.
This blog post gives an overview of super streams and the use cases they unlock. Read on to learn more, we value your feedback to make this feature the best it can be.
RabbitMQ 3.11 will bring a noteworthy feature to streams: single active consumer. Single active consumer provides exclusive consumption and consumption continuity on a stream. It is also critical to get the most out of super streams, our solution for partitioning, that provide scalability for streams.
Read on to find out more about single active consumer for streams and don't hesitate to experiment with what is already available: try it, break it, tell us what you like and don't like, what's missing. Your feedback is essential to make this feature the best it can be.
RabbitMQ 3.10 has recently been released and has some major new features which focus on optimizations, performance, and stability.
Release notes page includes information about the specific changes in this version as well as various installation assets. See our upgrade guide for more information about upgrading to 3.10.0.
Let's have a tour!
Quorum queues in RabbitMQ 3.10 provide a safer form of dead lettering that uses at-least-once guarantees for the message transfer between queues. This blog post explains everything you need to know to start using at-least-once dead lettering.
This post also introduces two other RabbitMQ 3.10 features: message Time-To-Live (TTL) for quorum queues and Prometheus metrics for dead lettered messages.
RabbitMQ streams allow applications to convey detailled information thanks to the powerful message format they use. Streams are a feature of their own, but they also fully integrate with the existing resources and protocols that RabbitMQ supports. This blog post covers the interoperability of streams in RabbitMQ and explores the scenarios it unlocks.
RabbitMQ Streams provides server-side offset tracking for consumers. This features allows a consuming application to restart consuming where it left off in a previous run. This post covers the semantics of offset tracking and how it is implemented in the stream Java client.
RabbitMQ Streams Overview introduced streams, a new feature in RabbitMQ 3.9 and RabbitMQ Streams First Application provided an overview of the programming model with the stream Java client. This post covers how to deduplicate published messages in RabbitMQ Streams.
As deduplication is a critical and intricate concept, the post will walk you through this mechanism step by step, from a naive and somewhat broken publishing application to an optimized and reliable implementation.
