Most Active Speaker

Julien Jakubowski

Julien Jakubowski

Developer Advocate @StreamNative

Developer Advocate @StreamNative

Lille, France


Julien Jakubowski is a Developer Advocate at StreamNative with over 20+ years of experience as a developer, staff engineer, and consultant. He has built several complex systems with distributed, scalable, and event-driven architecture for various industrial sectors such as retail, finance, and manufacturing.

Julien delivers talks at conferences on software engineering, including Devoxx, JCon, Conf42, VoxxedDays, Berlin Buzzwords, and Java User Groups, among others.

Julien is located in France. He's also one of the founders and leaders of the Ch'ti JUG - Java User Group of Lille, France.

Julien Jakubowski est developer advocate chez StreamNative.

Il a une vingtaine d’années d’expérience en tant que développeur, tech lead et consultant. Il a construit plusieurs systèmes complexes à architecture distribuée, scalables et event-driven, dans des domaines variés : retail, banque, assurance, industrie…

Julien est speaker à différentes conférences techniques (Devoxx, VoxxedDays, Berlin Buzzwords, JUGs, GDG, Agile Tours…), Julien est également l’un des fondateurs et leaders du Ch’ti JUG - Java User Group de Lille.


  • Most Active Speaker 2023

Area of Expertise

  • Information & Communications Technology


  • Apache Pulsar
  • Apache Kafka
  • Data Streaming
  • Event Streaming
  • messaging
  • Software Quality
  • java
  • Spring
  • People Management


Apache Pulsar: Finally an Alternative to Kafka? en fr

Today, when you think about building event-driven and real-time applications, the words that come to you spontaneously are probably: RabbitMQ, ActiveMQ, or Kafka. These are the solutions that dominate this landscape. But have you ever heard of Apache Pulsar?

After a brief presentation of the fundamental concepts of messaging, you'll discover the Apache Pulsar features that enable you to build amazing event-driven applications.
You'll learn the following:
- how Apache Pulsar architecture differs from other brokers
- how it enables scaling processing power & data independently, quickly, and with no hassle
- how it guarantees high durability of messages across nodes and different data centers
- how it covers the use cases of both RabbitMQ & Kafka while involving a single broker
- how to integrate Pulsar with your existing application portfolio
- and more

Apache Pulsar : enfin une alternative à Kafka ? en fr

Aujourd'hui, quand on pense à créer des applications event-driven et temps réel, les mots qui viennent spontanément sont : RabbitMQ, ActiveMQ ou encore Kafka. Ce sont les solutions qui dominent ce paysage. Mais pour créer des applications événementielles exigeantes, il y a une alternative qui monte : Apache Pulsar.

Après un bref rappel des concepts du messaging, vous découvrirez les caractéristiques-clé de Pulsar. Vous apprendrez notamment :

- comment Pulsar permet de dépasser certaines limites qu'on peut rencontrer avec d'autres brokers
- comment il permet de scaler rapidement et sans prise de tête
- comment il garantit une excellente durabilité des messages
- en quoi il est pertinent en tant que plateforme de streaming et de messagerie unifiée
- comment l'intégrer à votre existant compatible avec Kafka ou RabbitMQ
- un aperçu de la communauté open-source autour de Pulsar

Hands-on event-sourcing sorcery en

Event sourcing consists of storing data changes history as a sequence of events. This sequence can then be replayed to rebuild the current state of the data.

This pattern brings several benefits, which we will discover in this session.

But it also comes with challenges. For example: how to scale? How to store event history for a long time and at a reasonable cost? How do we address these challenges when our existing apps are based on Apache Kafka?

In this talk, we will start with a recap of the fundamental principles of event sourcing.

Then we will have an overview of the challenges with implementing event-sourcing with Apache Kafka, and how Apache Pulsar helps overcome some of these challenges.

Throughout this talk, we will not only discuss theory but also engage in practical application. We will practice event-sourcing witchcraft with Pulsar and Java to assist a thriving magic potion business in scaling its operations!

Data streaming design patterns every developer should know en

Welcome to the thrilling adventure of data streaming, which allows you to juggle mountains of real-time data and make lightning-fast informed decisions!

Perhaps you've already dabbled with Kafka or Pulsar in your data streaming projects. That's a great start, but hold on tight: stream processing comes with challenges like delivering a message exactly once, processing in parallel, fault tolerance, and more.

After briefly revisiting what data streaming is and its applications, we'll delve into the essential patterns you need to know to get off on the right foot in this fascinating world. We'll dodge cunning traps and turn obstacles into opportunities.

Don't worry, we won't just stick to theory! We'll ground our discussion in concrete examples.

By the end of this talk, you'll be better equipped to overcome the challenges and build solid real-time data processing applications.

How to build a cloud-native messaging & streaming platform on Kubernetes en fr

In the dynamic field of data streaming and messaging, prominent solutions like RabbitMQ and Kafka have established themselves as leaders. However, the challenges of managing these solutions in a Kubernetes environment are significant.

This presentation commences with a concise overview of the essential principles of messaging.

It further investigates the challenges inherent in deploying messaging and streaming platforms within cloud environments, covering topics such as:
- Limitations encountered by traditional message brokers and data streaming platforms in Kubernetes.
- Strategies for independently, swiftly, and seamlessly scaling processing power and data.
- Ensuring robust message durability across a range of nodes and data centers.

To conclude, the presentation outlines the available strategies and solutions for implementing such a platform.

Comment construire une plateforme de data streaming et messaging sur Kubernetes en fr

Dans le domaine du messaging et du data streaming, des solutions telles que RabbitMQ et Kafka se sont imposées comme leaders. Cependant, les défis liés à la gestion de ces solutions dans un environnement Kubernetes sont importants.

Cette présentation commence par un aperçu concis des principes essentiels du messaging et du data streaming.

Elle décrit ensuite les défis inhérents au déploiement de plateformes de messaging et de data streaming dans des environnements cloud, couvrant des sujets tels que :
- Les limites rencontrées par les brokers de messages traditionnels et les plateformes de streaming de données dans Kubernetes.
- Des stratégies pour scaler indépendamment, rapidement et de manière transparente le processing et le stockage.
- Garantir la durabilité des messages grâce à une redondance des noeuds mais également une redondance des data-centers/régions (géo-réplication).

Pour conclure, la présentation décrit les stratégies et solutions disponibles pour la mise en œuvre d'une telle plateforme sur Kubernetes.

JDevSummit IL '24 Sessionize Event

April 2024 Tel Aviv, Israel

Open Source Analytics Conference 2023 Sessionize Event

December 2023

JCON WORLD 2023 Sessionize Event

November 2023

Porto Tech Hub Conference 2023 Sessionize Event

October 2023 Porto, Portugal

Mêlée Tech - Mêlée Numérique 2023 Sessionize Event

September 2023 Toulouse, France

Pulsar Virtual Summit Europe 2023 Sessionize Event

May 2023

Dev Test Days 2020 Sessionize Event

October 2020 Rennes, France

Agile Grenoble 2019 Sessionize Event

November 2019 Grenoble, France

Agile Tour Lille 2019 Sessionize Event

October 2019 Lille, France

Julien Jakubowski

Developer Advocate @StreamNative

Lille, France


Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.

Jump to top