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Transforming the Airflow UI for Cloudera’s Users with Shubham Raj
Manage episode 493626634 series 2053958
Contributing to open-source projects can be daunting, but it can also unlock unexpected innovation. This episode showcases how one engineer’s journey with Apache Airflow led to impactful UI enhancements and infrastructure solutions at scale. Shubham Raj, Software Engineer II at Cloudera, shares how his contributions helped shape Airflow 3.0, including an intuitive drag-and-drop DAG editor and a new REST API endpoint for managing XComs.
Key Takeaways:
(02:30) Day-to-day responsibilities building platforms that simplify orchestration.
(05:27) Factors that make onboarding into large open-source projects accessible.
(07:35) The value of improved user interfaces for task state visibility and control.
(09:49) Enabling faster debugging by exposing internal data through APIs.
(13:00) Balancing frontend design goals with backend functionality.
(14:19) Creating workflow editors that lower the barrier to entry.
(16:54) Supporting a variety of task types within a visual DAG builder.
(19:32) Common infrastructure challenges faced by orchestration users.
(20:37) Addressing dependency management across distributed environments.
Resources Mentioned:
https://www.linkedin.com/in/shubhamrajofficial/
Cloudera | LinkedIn
https://www.linkedin.com/company/cloudera/
Cloudera | Website
https://www.cloudera.com/
https://airflow.apache.org/
https://airflowsummit.org/
https://www.astronomer.io/events/roadshow/london/
https://www.astronomer.io/events/roadshow/new-york/
https://www.astronomer.io/events/roadshow/sydney/
https://www.astronomer.io/events/roadshow/san-francisco/
https://www.astronomer.io/events/roadshow/chicago/
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 #MachineLearning
64 episodes
Transforming the Airflow UI for Cloudera’s Users with Shubham Raj
The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI
Manage episode 493626634 series 2053958
Contributing to open-source projects can be daunting, but it can also unlock unexpected innovation. This episode showcases how one engineer’s journey with Apache Airflow led to impactful UI enhancements and infrastructure solutions at scale. Shubham Raj, Software Engineer II at Cloudera, shares how his contributions helped shape Airflow 3.0, including an intuitive drag-and-drop DAG editor and a new REST API endpoint for managing XComs.
Key Takeaways:
(02:30) Day-to-day responsibilities building platforms that simplify orchestration.
(05:27) Factors that make onboarding into large open-source projects accessible.
(07:35) The value of improved user interfaces for task state visibility and control.
(09:49) Enabling faster debugging by exposing internal data through APIs.
(13:00) Balancing frontend design goals with backend functionality.
(14:19) Creating workflow editors that lower the barrier to entry.
(16:54) Supporting a variety of task types within a visual DAG builder.
(19:32) Common infrastructure challenges faced by orchestration users.
(20:37) Addressing dependency management across distributed environments.
Resources Mentioned:
https://www.linkedin.com/in/shubhamrajofficial/
Cloudera | LinkedIn
https://www.linkedin.com/company/cloudera/
Cloudera | Website
https://www.cloudera.com/
https://airflow.apache.org/
https://airflowsummit.org/
https://www.astronomer.io/events/roadshow/london/
https://www.astronomer.io/events/roadshow/new-york/
https://www.astronomer.io/events/roadshow/sydney/
https://www.astronomer.io/events/roadshow/san-francisco/
https://www.astronomer.io/events/roadshow/chicago/
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 #MachineLearning
64 episodes
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