
Sign up to save your podcasts
Or


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
By Astronomer5
2020 ratings
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

32,007 Listeners

229,029 Listeners

537 Listeners

625 Listeners

146 Listeners

3,990 Listeners

25 Listeners

142 Listeners

9,922 Listeners

57,845 Listeners

5,507 Listeners

14 Listeners

8 Listeners

25 Listeners

147 Listeners