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pedrogk committed Aug 7, 2024
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timeslot: 29
gridarea: "12/4/13/5"
images:
- /images/sessions/2024/ai-reality-check.jpg
- /images/sessions/2024/empowering-teams.jpg
---

Does your organization feel like the responsibility to write Airflow DAGs, handle the Airflow infrastructure administration, debug failing tasks, and keep up with new features and best practices is too much for too few people? Perhaps you only have one data team that owns all of that; or you have too many teams that have too many permissions into other teams' DAGs.
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timeslot: 37
gridarea: "14/4/15/5"
images:
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- /images/sessions/2024/maxime-preset.jpg
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In the past 18 months, artificial intelligence has not just entered our workspaces – it has taken over. As we stand at the crossroads of innovation and automation, it's time for a candid reflection on how AI has reshaped our professional lives, and to talk about where it's been a game changer, where it's falling short, and what's about to shift dramatically in the short term.
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timeslot: 51
gridarea: "6/4/7/5"
images:
- /images/sessions/2024/comparing-executors.jpg
- /images/sessions/2024/doublecloud.jpg
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With recent works in the direction of Executor Decoupling and interest in Hybrid Execution, we find it's still quite common for Airflow users to use the old-time rule of thumbs like "Don't Use Airflow with LocalExecutor in production", "If your scheduler lags, split your DAGs over two separate Airflow Clusters", and so on. In our talk, we will show a deep dive comparison between various Execution models Airflow support and hopefully update understanding of their efficiency and limitations.
14 changes: 14 additions & 0 deletions content/speakers/spencer-tollefson/_index.md
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title: "Spencer Tollefson"
date: 2024-08-07T15:20:09-05:00
images:
- /images/speakers/spencer-tollefson.jpg
designation: Team Lead, Data Engineering at Rakuten Kobo
twitter:
linkedin: https://linkedin.com/in/stollefson1
github:
events:
- 2024
---

I love being tasked with a complex problem and designing and implementing solutions to solve them. I'm technically focused, an individual contributor at heart, but also manage a data engineering team. I administer Airflow clusters that various teams use, and strive to work with the business side to understand how Airflow can be used to simplify everyone else's lives.
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