While the output of certain RabbitMQ CLI commands uses the term “slave” to refer to mirrored queues, RabbitMQ has disavowed this term, as has Datadog. When collecting RabbitMQ metrics, you can take advantage of RabbitMQ’s built-in monitoring tools and ecosystem of plugins. In this post, we’ll introduce these RabbitMQ monitoring tools and show you how you can use them in your own messaging setup.
RabbitMQ is a message broker, a tool for implementing a messaging architecture. Some parts of your application publish messages, others consume them, and RabbitMQ routes them between producers and consumers. The broker is well suited for loosely coupled microservices. If no service or part of the application can handle a given message, RabbitMQ keeps the message in a queue until it can be delivered.
Mattermost v7.9 is generally available today. With this latest release, we’ve added Boards System and Team admin access and Compliance APIs. High-level access and management for all boards in a workspace helps maintain control of team collaboration, leading to a more effective and secure team environment. See the changelog for more details.
Mission-focused teams that operate in contingency environments – think military branches, the intelligence community, NASA – increasingly depend on collaboration software. They need to share information quickly, nimbly, and securely. And they want to carry that out in contextual channels that enable them to see the right content at the right time to make informed, accurate decisions.
Apache Kafka has come a long way since its initial development at LinkedIn in 2010 and its release as an open-source project the following year. Over the past decade, it has grown from a humble messaging bus used to power internal applications into the world's most popular streaming data platform. Its evolution is remarkable, and it has taken the industry by storm, quickly becoming a go-to solution for data streaming and processing.
With the dawn of microservices and serverless, event-driven architectures have become the way to go when building a new system in the cloud. This approach has allowed for greater scalability, as the system can easily adapt and respond to changes in traffic or demand without having to overhaul the entire architecture. Additionally the Event-driven approach means your application is mainly concerned with routing event data to the right services.
Earlier this month, we announced a rebrand to meshIQ and in this blog we will highlight the reasons behind the rebrand and what you can expect going forward.
