Operations | Monitoring | ITSM | DevOps | Cloud

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.

Apache Kafka is the de facto standard for event streaming use cases across industries. Many use cases can be applied to the aviation industry, too. Concepts like payment, customer experience, and manufacturing differ in detail. But in the end, it is about integrating systems and processing data in real-time at scale. For instance, omnichannel retail with Apache Kafka applies to airline, airports, global distribution systems (GDS), and other aviation industry sectors.