RabbitMQ has, for a long time, been one of the most popular message brokers in the world. Last year, streams were introduced and today RabbitMQ can be used to support many use cases, whether it is as a message broker, for message streams, or doing both in unison. This blog will explain why RabbitMQ fits well into most messaging-streaming scenarios and why it’s an excellent choice. But before we jump into that, let’s cover some basics around event streaming.

In this article, we will analyze what are the metrics for monitoring Kafka performance and why it is important to constantly monitor them. We will also look at the process of monitoring metrics for Kafka using Hosted Graphite by MetricFire. To learn more about MetricFire, book a demo with the MetricFire team or sign up for the free trial.

Designing a production service environment around Apache Kafka that delivers low latency and zero-data loss at scale is non-trivial. Indeed, it’s the holy grail of messaging systems. In this blog post, I’ll outline some of the fundamental service design considerations that you’ll need to take into account in order to get your service architecture to measure up. Let’s start with the basics.

Do you want to use Kafka? Or do you need a message broker and queues? While they can seem similar, they have different purposes. I’m going to explain the differences, so you don’t try to brute force patterns and concepts in Kafka that are better used with a message broker.