An introduction to Apache Kafka

The Reactive Manifesto states that responsive systems have the properties of being resilient and elastic. One way to achieve this, is having our applications deployed multiple times next to each other. In case one instance goes down, there will be other ones to take up its task, giving more resilience to the system. In case … Continue reading "An introduction to Apache Kafka"

Read More

Backpressure in Project Reactor: Saving your Subscribers from drowning

One of the main mechanisms behind Reactive Programming is backpressure. In this article we’ll take a look at the concept, and some of the advantages it creates when working with Reactive Streams. The concept of backpressure in Reactive Streams is as elegant as it is powerful. It will enable the use of slow Consumers within … Continue reading "Backpressure in Project Reactor: Saving your Subscribers from drowning"

Read More

Flux Caching in Project Reactor: Replaying past data

In the article Flux Sharing in Project Reactor: From one to many we looked at how we can attach multiple Fluxes to an initial Flux by sharing it, to create multiple substreams from our original Reactive stream. This offers quite a bit of extra power. We can “feed” data to different subsystems that can consume … Continue reading "Flux Caching in Project Reactor: Replaying past data"

Read More

Flux Sharing in Project Reactor: From one to many

Reactive Applications often require Reactive Streams to be subscribed to by multiple Subscribers at the same time. For example when the same information streams needs to be used by different components in the application, or when we want to let the data stream to different users. Especially in real-time applications this can be a huge … Continue reading "Flux Sharing in Project Reactor: From one to many"

Read More