Hybrid Testing Solutions for Autonomous Driving at Bosch with Jens Scheffler and Christian Schilling

The Data Flowcast: Mastering Airflow for Data Engineering & AI

The Data Flowcast: Mastering Airflow for Data Engineering & AI

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Living together in a group is a strategy many animals use to survive and thrive. And a big part of what makes that living situation successful is listening. In this episode, we explore the collaborative world of the naked mole-rat. Threshold is nonprofit, listener-supported, and independently produced. You can support Threshold by donating today . To stay connected, sign up for our newsletter . Operation frog sound! Send us your frog sounds for an upcoming episode. We want you to go out, listen for frogs and toads, and record them. Just find someone croaking, and hit record on your phone. It doesn’t matter if there’s background noise. It doesn’t even matter if you’re not sure whether or not you’re hearing an amphibian—if you think you are, we would love to get a recording from you. Please also say your name and where you are in the world, and then email the recording to us at outreach@thresholdpodcast.org…

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Testing autonomous vehicles demands precision, scalability and powerful orchestration tools — enter Apache Airflow, a key component of Bosch’s cutting-edge testing framework. In this episode, we sit down with Jens Scheffler, Test Execution Cluster Technical Architect, and Christian Schilling, Product Owner Open Loop Testing Automated Driving, both at Bosch, to explore how Bosch harnesses Airflow to streamline complex testing scenarios. They share insights on scaling workflows, integrating hybrid infrastructures and ensuring vehicle safety through rigorous automated testing.

Key Takeaways:

(01:35) Airflow orchestrates millions of test hours for autonomous systems.

(03:15) Jens scales distributed systems with Kubernetes for job orchestration.

(06:02) Airflow runs hundreds of tests simultaneously.

(06:44) Virtual testing reduces costs and on-road trials.

(12:19) Unified APIs and GUIs streamline operations.

(15:05) Self-service setups empower Bosch teams.

(18:00) Physical hardware integration ensures real-world timing.

(20:30) Dynamic task mapping scales workflows efficiently.

(25:22) Open-source contributions improve stability.

(31:06) Edge and Celery executors power Bosch's hybrid scheduling.

Resources Mentioned:

Jens Scheffler -

https://www.linkedin.com/in/jens-scheffler/

Christian Schilling -

https://www.linkedin.com/in/christian-schilling-a5078831a/

Bosch -

https://www.linkedin.com/company/bosch/

Apache Airflow -

https://airflow.apache.org/

Kubernetes -

https://kubernetes.io

GitHub -

https://github.com

Edge Executor -

https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/executor/index.html

Thanks for listening to “The Data Flowcast: Mastering Airflow for Data Engineering & AI.” If you enjoyed this episode, please leave a 5-star review to help get the word out about the show. And be sure to subscribe so you never miss any of the insightful conversations.

#AI #Automation #Airflow #MachineLearning

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The Data Flowcast: Mastering Airflow for Data Engineering & AI