Building Realtime Streaming Architectures

Real time is not only about client interactions. We have been using XMPP & MQTT since a long time to connect people and things together.

However, there is another use case for real time that is a little less known: real time streaming architectures. This is a design pattern that you can use to make the core of your applications or systems real time.

The principle is simple. You split components into isolated real time streaming services. These servies talk to each other through a data bus. Very often it’s Kafka, using the publish & subscribe pattern.

This approach is very powerful. You can tolerate a component being down for a short maintenance, with the confidence that your real time streaming system will catch up. The pattern is also useful to tune the computing capacity at each stage of the processing pipeline. And finally, the pattern is also popular to split services and let them evolve independently.

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These are just the technical benefits. But from a high level business perspective, it simply means that you get a more resilient system. It is able to process events in real time, serving as a basis of new innovative offerings for your customers. This leads to a significant business edge.

I had already presented back in 2017 at DotGo Conference what we we had been doing, at a technical level, to build real time streaming architectures.

Today, we are able to share more by publishing a case study. We show the type of real time streaming architecture we have been building for Colissimo, a leading postal service in France. Go ahead and read Colissimo case study.

Do not hesitate to contact us for guidance on how to build, improve, troubleshoot or rework real time streaming architectures.

Real time streaming architectures

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