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How Covestro Turns Airflow Into a Simulation Toolbox with Anja Mackenzie

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Manage episode 520323668 series 2948506
Indhold leveret af The Data Flowcast. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Data Flowcast eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Building scalable, reproducible workflows for scientific computing often requires bridging the gap between research flexibility and enterprise reliability.

In this episode, Anja MacKenzie, Expert for Cheminformatics at Covestro, explains how her team uses Airflow and Kubernetes to create a shared, self-service platform for computational chemistry.

Key Takeaways:

00:00 Introduction.

06:19 Custom scripts made sharing and reuse difficult.

09:29 Workflows are manually triggered with user traceability.

10:38 Customization supports varied compute requirements.

12:48 Persistent volumes allow tasks to share large amounts of data.

14:25 Custom operators separate logic from infrastructure.

16:43 Modified triggers connect dependent workflows.

18:36 UI plugins enable file uploads and secure access.

Resources Mentioned:

Anja MacKenzie

https://www.linkedin.com/in/anja-mackenzie/

Covestro | LinkedIn

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

Covestro | Website

https://www.covestro.com

Apache Airflow

https://airflow.apache.org/

Kubernetes

https://kubernetes.io/

Airflow KubernetesPodOperator

https://airflow.apache.org/docs/apache-airflow-providers-cncf-kubernetes/stable/operators.html

Astronomer

https://www.astronomer.io/

Airflow Academy by Marc Lamberti

https://www.udemy.com/user/lockgfg/?utm_source=adwords&utm_medium=udemyads&utm_campaign=Search_DSA_GammaCatchall_NonP_la.EN_cc.ROW-English&campaigntype=Search&portfolio=ROW-English&language=EN&product=Course&test=&audience=DSA&topic=&priority=Gamma&utm_content=deal4584&utm_term=_._ag_169801645584_._ad_700876640602_._kw__._de_c_._dm__._pl__._ti_dsa-1456167871416_._li_9061346_._pd__._&matchtype=&gad_source=1&gad_campaignid=21341313808&gbraid=0AAAAADROdO1_-I2TMcVyU8F3i1jRXJ24K&gclid=Cj0KCQjwvJHIBhCgARIsAEQnWlC1uYHIRm3y9Q8rPNSuVPNivsxogqfczpKHwhmNho2uKZYC-y0taNQaApU2EALw_wcB

Airflow Documentation

https://airflow.apache.org/docs/

Airflow Plugins

https://airflow.apache.org/docs/apache-airflow/1.10.9/plugins.html

Thanks for listening to “The Data Flowcast: Mastering Apache Airflow® for Data Engineering and 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

  continue reading

82 episoder

Artwork
iconDel
 
Manage episode 520323668 series 2948506
Indhold leveret af The Data Flowcast. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Data Flowcast eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Building scalable, reproducible workflows for scientific computing often requires bridging the gap between research flexibility and enterprise reliability.

In this episode, Anja MacKenzie, Expert for Cheminformatics at Covestro, explains how her team uses Airflow and Kubernetes to create a shared, self-service platform for computational chemistry.

Key Takeaways:

00:00 Introduction.

06:19 Custom scripts made sharing and reuse difficult.

09:29 Workflows are manually triggered with user traceability.

10:38 Customization supports varied compute requirements.

12:48 Persistent volumes allow tasks to share large amounts of data.

14:25 Custom operators separate logic from infrastructure.

16:43 Modified triggers connect dependent workflows.

18:36 UI plugins enable file uploads and secure access.

Resources Mentioned:

Anja MacKenzie

https://www.linkedin.com/in/anja-mackenzie/

Covestro | LinkedIn

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

Covestro | Website

https://www.covestro.com

Apache Airflow

https://airflow.apache.org/

Kubernetes

https://kubernetes.io/

Airflow KubernetesPodOperator

https://airflow.apache.org/docs/apache-airflow-providers-cncf-kubernetes/stable/operators.html

Astronomer

https://www.astronomer.io/

Airflow Academy by Marc Lamberti

https://www.udemy.com/user/lockgfg/?utm_source=adwords&utm_medium=udemyads&utm_campaign=Search_DSA_GammaCatchall_NonP_la.EN_cc.ROW-English&campaigntype=Search&portfolio=ROW-English&language=EN&product=Course&test=&audience=DSA&topic=&priority=Gamma&utm_content=deal4584&utm_term=_._ag_169801645584_._ad_700876640602_._kw__._de_c_._dm__._pl__._ti_dsa-1456167871416_._li_9061346_._pd__._&matchtype=&gad_source=1&gad_campaignid=21341313808&gbraid=0AAAAADROdO1_-I2TMcVyU8F3i1jRXJ24K&gclid=Cj0KCQjwvJHIBhCgARIsAEQnWlC1uYHIRm3y9Q8rPNSuVPNivsxogqfczpKHwhmNho2uKZYC-y0taNQaApU2EALw_wcB

Airflow Documentation

https://airflow.apache.org/docs/

Airflow Plugins

https://airflow.apache.org/docs/apache-airflow/1.10.9/plugins.html

Thanks for listening to “The Data Flowcast: Mastering Apache Airflow® for Data Engineering and 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

  continue reading

82 episoder

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