Transforming the Airflow UI for Cloudera’s Users with Shubham Raj
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:Shubham Rajhttps://www.linkedin.com/in/shubhamrajofficial/Cloudera | LinkedInhttps://www.linkedin.com/company/cloudera/Cloudera | Websitehttps://www.cloudera.com/Apache Airflowhttps://airflow.apache.org/2023 Airflow Summithttps://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
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22:28
Streamlining Thousands of Data Pipelines at Lyft with Yunhao Qing
Managing data pipelines at scale is not just a technical challenge. It is also an organizational one. At Lyft, success means empowering dozens of teams to build with autonomy while enforcing governance and best practices across thousands of workflows.In this episode, we speak with Yunhao Qing, Software Engineer at Lyft, about building a governed data-engineering platform powered by Airflow that balances flexibility, standardization and scale.Key Takeaways:(03:17) Supporting internal teams with a centralized orchestration platform.(04:54) Migrating to a managed service to reduce infrastructure overhead.(06:04) Embedding platform-level governance into custom components.(08:02) Consolidating and regulating the creation of custom code.(09:48) Identifying and correcting inefficient workflow patterns.(11:17) Replacing manual workarounds with native platform features.(14:32) Preparing teams for major version upgrades.(16:03) Leveraging asset-based scheduling for smarter triggers.(18:13) Envisioning GenAI and semantic search for future productivity.Resources Mentioned:Yunhao Qinghttps://www.linkedin.com/in/yunhao-qingLyft | LinkedInhttps://www.linkedin.com/company/lyft/Lyft | Websitehttps://www.lyft.com/Apache Airflowhttps://airflow.apache.org/Astronomerhttps://www.astronomer.io/Kuberneteshttps://kubernetes.io/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
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19:34
Transforming Customer Education in Data Engineering at Astronomer with Marc Lamberti
Understanding the complexities of Apache Airflow can be daunting for newcomers and seasoned data engineers. But with the right guidance, mastering the tool becomes an achievable milestone.In this episode, Marc Lamberti, Head of Customer Education at Astronomer, joins us to share his journey from Udemy instructor to driving education at Astronomer, and how he's helping over 100,000 learners demystify Airflow.Key Takeaways:(02:36) Early exposure to Airflow while addressing inefficiencies in data workflows.(04:10) Common barriers to implementing open source tools in enterprise settings.(06:18) The shift from part-time teaching to a full-time focus on Airflow education.(07:53) A modular, guided approach to structuring educational content.(09:57) The value of highlighting underused Airflow features for broader adoption.(12:35) Certifications as a method to assess readiness and uncover knowledge gaps.(13:25) Coverage of essential Airflow concepts in the Fundamentals exam.(16:07) The DAG Authoring exam’s emphasis on practical, advanced features.(20:08) A call for more visible integration of Airflow with AI workflows.Resources Mentioned:Marc Lambertihttps://www.linkedin.com/in/marclamberti/Astronomer | LinkedInhttps://www.linkedin.com/company/astronomer/Astronomer Academyhttps://academy.astronomer.io/Airflow Fundamentals Certificationhttps://www.astronomer.io/certification/DAG Authoring Certificationhttps://academy.astronomer.io/plan/astronomer-certification-dag-authoring-for-apache-airflow-examThe Complete Hands-On Introduction to Airflowhttps://www.udemy.com/course/the-complete-hands-on-course-to-master-apache-airflow/?utm_source=adwords&utm_medium=udemyads&utm_campaign=Search_DSA_Beta_Prof_la.EN_cc.ROW-English&campaigntype=Search&portfolio=ROW-English&language=EN&product=Course&test=&audience=DSA&topic=&priority=Beta&utm_content=deal4584&utm_term=_._ag_162511579404_._ad_696197165418_._kw__._de_c_._dm__._pl__._ti_dsa-1677053911088_._li_9061346_._pd__._&matchtype=&gad_source=1&gad_campaignid=21168154305&gbraid=0AAAAADROdO3MpljfP-gssiYSmDEPdhZV9&gclid=Cj0KCQjw097CBhDIARIsAJ3-nxdjZA6G5-Y0-akk6Huksy2PLb04t92J4iNfUSIbMdrSAla_tb-o2N8aArOeEALw_wcB&couponCode=PMNVD3025https://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
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22:19
Embracing Data Mesh and SQL Sensors for Scalable Workflows at lastminute.com with Alberto Crespi
The flexibility of Airflow plays a pivotal role in enabling decentralized data architectures and empowering cross-functional teams.In this episode, we speak with Alberto Crespi, Data Architect at lastminute.com, who shares how his team scales Airflow across 12 teams while supporting both vertical and horizontal structures under a data mesh approach.Key Takeaways:(02:17) Defining responsibilities within data architecture teams.(04:15) Consolidating multiple orchestrators into a single solution.(07:00) Scaling Airflow environments with shared infrastructure and DevOps practices.(10:59) Managing dependencies and readiness using SQL sensors.(14:23) Enhancing visibility and response through Slack-integrated monitoring.(19:28) Extending Airflow’s flexibility to run legacy systems.(22:28) Integrating transformation tools into orchestrated pipelines.(25:54) Enabling non-engineers to contribute to pipeline development.(27:33) Fostering adoption through collaboration and communication.Resources Mentioned:Alberto Crespihttps://www.linkedin.com/in/crespialberto/lastminute.com | Websitehttps://lastminute.comApache Airflowhttps://airflow.apache.org/dbt Labshttps://www.getdbt.com/Astronomer Cosmoshttps://github.com/astronomer/astronomer-cosmosGitLabSlackhttps://slack.com/Kuberneteshttps://kubernetes.io/Confluencehttps://www.atlassian.com/software/confluenceSlackhttps://slack.com/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
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30:09
The AI-Ready Pipeline: Reimagining Airflow at Veyer® Logistics with Anu Pabla
Innovation in orchestration is redefining how engineers approach both traditional ETL pipelines and emerging AI workloads. Understanding how to harness Airflow’s flexibility and observability is essential for teams navigating today’s evolving data landscape.In this episode, Anu Pabla, Principal Engineer at The ODP Corporation, joins us to discuss her journey from legacy orchestration patterns to AI-native pipelines and why she sees Airflow as the future of AI workload orchestration.Key Takeaways:(03:43) Engaging with external technology communities fosters innovation.(05:05) Mentoring early-career engineers builds confidence in a complex tech landscape.(07:51) Orchestration patterns continue to evolve with modern data needs.(08:41) Managing AI workflows requires structured and flexible orchestration.(10:35) High-quality, meaningful data remains foundational across use cases.(15:08) Community-driven open source tools offer lasting value.(16:59) Self-healing systems support both legacy and AI pipelines.(20:20) Orchestration platforms can drive future AI-native workloads.Resources Mentioned:Anu Pablahttps://www.linkedin.com/in/atomicap/The ODP Corporationhttps://www.linkedin.com/company/the-odp-corporation/The ODP Corporation | Websitehttps://www.theodpcorp.com/homepageApache Airflowhttps://airflow.apache.org/LlamaIndexhttps://www.llamaindex.ai/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
About The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI
Welcome to The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI— the podcast where we keep you up to date with insights and ideas propelling the Airflow community forward.
Join us each week, as we explore the current state, future and potential of Airflow with leading thinkers in the community, and discover how best to leverage this workflow management system to meet the ever-evolving needs of data engineering and AI ecosystems.
Podcast Webpage: https://www.astronomer.io/podcast/
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