Dec 5, 2021
This article aims to discuss data contracts in the context of event processing applications. We will follow a short example: The Dumpling App! The post also looks at that concept through specific technologies. Pub/Sub message schemas is a relatively recent feature, so let’s take it for a spin in that article.
Jun 1, 2020
The abstract in French 🇫🇷:
Le serving de modèle de Machine Learning pour la prédiction en temps réel présente des défis tant en Data Engineering qu’en Data Science. Comment construire un pipeline moderne qui permet de réaliser des prédictions en continu ? Dans le cas d’un exercice supervisé, comment allier tracing et tracking des performances ?
Apr 9, 2020
On your journey to build event stream and real-time applications you have probably heard about Confluent Cloud:
[…] a fully managed, cloud-native event streaming platform powered by Apache Kafka.
The team behind this service is putting a lot of efforts to provide a smooth and complete experience in working with Apache Kafka in the cloud.
Jun 4, 2019
The abstract (in French 🇫🇷):
L’ Auto Scaling c’est l’argument phare d’un bon nombre de technologies en Data Engineering. Parmi les outils du moment, on retrouve Kafka-Streams. Avec sa forte intégration au bus de message Apache Kafka, il est pensé pour être un framework distribué capable de passer à l’échelle. Pourtant, dans la pratique, sa seule utilisation est limitée.
Apr 15, 2019
There are many reasons for working on community contributions such as a blog post, a demo, or a talk. Sometimes, you produce those contributions to share something that you’ve learned at work. But sometimes, the contribution itself can be a way to learn and experiment something new. I was in the second case when I worked on the article Kafka Streams: a road to Autoscaling via Kubernetes.
Nov 20, 2018
The abstract:
Apache Kafka’s Streams API lets us process messages from different topics with very low latency. Messages may have different formats, schemas and may even be serialised in different ways. What happens when an undesirable message comes in the flow? When an error occurs, real-time applications can’t always wait for manual recovery and need to handle such failures.