67 posts tagged with "New Features"

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.

RabbitMQ Streams Overview introduced streams, a new feature in RabbitMQ 3.9. This post covers how client applications should connect to RabbitMQ nodes to get the most benefit from streams when the stream protocol is in use.

Streams are optimized for high throughput scenarios, that's why technical details like data locality are critical to get the best out of your RabbitMQ cluster. Client libraries can handle most of the details, but a basic understanding of how things work under the hood is essential when a setup involves extra layers like containers and load balancers. Keep reading if you want to learn more about streams and avoid some headaches when deploying your first stream applications!

RabbitMQ Streams Overview introduced streams, a new feature in RabbitMQ 3.9. This post continues by showing how to use streams with the Java client. We will write our first application that publishes messages to a stream, and then consumes them.

RabbitMQ 3.9 introduces a new type of data structure: streams. Streams unlock a set of use cases that could have been tedious to implement with "traditional" queues. Let's discover in this post how streams expand the capabilities of RabbitMQ.

If you want to be notified when your RabbitMQ deployments have a problem, now you can set up the RabbitMQ monitoring and alerting that we have made available in the RabbitMQ Cluster Operator repository. Rather than asking you to follow a series of steps for setting up RabbitMQ monitoring & alerting, we have combined this in a single command. While this is a Kubernetes-specific quick-start, and you can use these Prometheus alerts outside of Kubernetes, the setup will require more consideration and effort on your part. We share the quick & easy approach, open source and free for all.