We're excited to announce the latest version of VMware Tanzu RabbitMQ, a product that has become invaluable to developers and business teams alike. With its popularity in the world of messaging and streaming, Tanzu RabbitMQ is a preferred choice for those seeking robust, scalable, and dependable communication solutions. Significant developments in the new Tanzu RabbitMQ 1.6 build on the success of our previous release and push the envelope of what RabbitMQ can deliver. This new version reflects our ongoing commitment to innovation in Tanzu RabbitMQ. Here are some highlights of what you can expect.
What’s new in Tanzu RabbitMQ 1.6
Support for MQTTv5
The previous release of Tanzu RabbitMQ saw some significant improvements to the performance of the simple and lightweight Message Queuing Telemetry Transport (MQTT) protocol used extensively in IoT applications. By streamlining the way that Tanzu RabbitMQ handles the connection process for MQTT, it is now possible for the most popular message broker to handle millions of IoT connections.
Now, Tanzu RabbitMQ supports the newest version, MQTTv5, which brings a whole raft of additional features specific to this protocol. To start, MQTTv5 is better suited for large-scale deployments. When combined with RabbitMQ Streams, messages can be sent to millions of devices more efficiently than before. Additionally, there is improved session management, support for user properties, and extended error reporting. These features allow for more fine-grain control over message properties and behaviors, making it a more versatile and extensible protocol compared to MQTTv3.
Filtering for RabbitMQ Streams
Since the launch of Streams in RabbitMQ, we have seen a steady growth in the adoption of this highly performant message transport mechanism. Not only do Streams provide the ability to route high volumes of data, but they can be partitioned into topics to make the consumption easier for client applications using Super Streams.
New in Tanzu RabbitMQ is the ability to filter a Stream, lightening the load on client applications at the same time as saving network bandwidth. In high-throughput message topologies, it is common for microservices to become overburdened and, in extreme cases, cease to be very micro at all. Filtering for Streams is particularly helpful in this type of application. However, since Streams are bloom-filter based, they do not replace the need for client-side filtering logic altogether. Like many messaging implementations, a degree of pragmatism is needed.
Introduction of message containers
Tanzu RabbitMQ 1.6 also sees the debut of message containers. These form the basis of a protocol-agnostic core that offers greater flexibility for users looking to leverage protocols other than AMQP 0.9.1. Previously, all non-AMQP 0.9.1 messages were handled via a proxy, which increased the processing overhead and had the potential to lose some metadata. However, with message containers, messages are wrapped and preserved throughout the routing of Tanzu RabbitMQ and are only reconstructed back into their original format when consumed. With this method, metadata is preserved where possible—but obviously, if consuming in a different protocol to that which published a message, a compromise in metadata mapped is needed.
Integrating event-driven architectures across disparate systems can be very complex, especially if legacy protocols are in play. Message containers allow users to consume messages from legacy systems (e.g., older protocols such as MQTTv3) and integrate them into a more modern microservice architecture without having to rewrite consuming clients from scratch. This protocol-agnostic core also means that Tanzu RabbitMQ has become even more flexible and has the potential to adopt many more protocols in the future.
New metadata store
This release of Tanzu RabbitMQ is an important milestone in the rollout plan for the new metadata store, Khepri, which will replace the existing Mnesia distributed metadata store. Based on the proven raft algorithm, Khepri makes it easier to reason about things like network partitions. It makes a clear consistent choice, rather than leaving that choice up to the user, thus improving the stability and predictability of the metadata store.
Improvements to memory footprint
Finally, we have also improved the memory footprint for the robust Quorum Queue and conventional Classic Queues v2. This benefit can enable better resource efficiency, cost savings, enhanced performance, and greater overall stability.
FIPS and security
Tanzu RabbitMQ 1.6 also introduces new security features. Most notably, it is FIPS 140-2 (Federal Information Processing Standard) compliant.
Learn more
All of these new and updated features are part of our ongoing effort to make VMware Tanzu RabbitMQ the most versatile and popular message broker for event-driven architectures.
