Uploaded August 2026 | Updated September 2026, 2 weeks ago
[EuroPython 2026 - S1 on 2026-07-16]
🎤 *Navigating waters of background jobs and queues in Python as of 2026 by Sebastian Buczyński*
🔗 https://ep2026.europython.eu/session/navigating-waters-of-background-jobs-and-queues-in-python-as-of-2026
📝 Abstract:
Should you use Kafka or RabbitMQ? Which Python library is the right fit? Is Celery still alive and kicking in 2026, or has Temporal taken over the world while we weren't watching? Perhaps we should all migrate to FastStream—or are the native background tasks in your web framework all you really need?
There have never been so many possibilities when choosing how to queue and distribute work. This talk provides a comprehensive comparison of the modern Python ecosystem. We will explore where each tool shines, how they perform under pressure, and—crucially—when a specific tool is a poor match and should be avoided.
Using two real-world case studies, we will showcase the capabilities of each library. You will be able to evaluate the developer experience and how debugging works for each solution. You’ll walk out with an ultimate decision chart, equipped to choose the perfect stack for your next project.
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: creativecommons.org/licenses/by-nc-sa/4.0
[EuroPython 2026 - S1 on 2026-07-16]
🎤 *Navigating waters of background jobs and queues in Python as of 2026 by Sebastian Buczyński*
🔗 https://ep2026.europython.eu/session/navigating-waters-of-background-jobs-and-queues-in-python-as-of-2026
📝 Abstract:
Should you use Kafka or RabbitMQ? Which Python library is the right fit? Is Celery still alive and kicking in 2026, or has Temporal taken over the world while we weren't watching? Perhaps we should all migrate to FastStream—or are the native background tasks in your web framework all you really need?
There have never been so many possibilities when choosing how to queue and distribute work. This talk provides a comprehensive comparison of the modern Python ecosystem. We will explore where each tool shines, how they perform under pressure, and—crucially—when a specific tool is a poor match and should be avoided.
Using two real-world case studies, we will showcase the capabilities of each library. You will be able to evaluate the developer experience and how debugging works for each solution. You’ll walk out with an ultimate decision chart, equipped to choose the perfect stack for your next project.
---
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License: creativecommons.org/licenses/by-nc-sa/4.0
