Optimizing Large-Scale Deployments at LinkedIn with Rahul Gade

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

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Our Skin: A Personal Discovery Podcast

1
You Are Your Longest Relationship: Artist DaQuane Cherry on Psoriasis, Art, and Self-Care 32:12

منذ 20 يومًا32:12

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إعجاب

احب

32:12

DaQuane Cherry was once the kid who wore a hoodie to hide skin flare-ups in school. Now he’s an artist and advocate helping others feel seen. He reflects on his psoriasis journey, the power of small joys, and why loving yourself first isn’t a cliché—it’s essential. Plus, a deep dive into the history of La Roche-Posay’s legendary spring. See omnystudio.com/listener for privacy information.…

منذ عام واحد 27:47

MP3•منزل الحلقة

Scaling deployments for a billion users demands innovation, precision and resilience. In this episode, we dive into how LinkedIn optimizes its continuous deployment process using Apache Airflow. Rahul Gade, Staff Software Engineer at LinkedIn, shares his insights on building scalable systems and democratizing deployments for over 10,000 engineers.

Rahul discusses the challenges of managing large-scale deployments across 6,000 services and how his team leverages Airflow to enhance efficiency, reliability and user accessibility.

Key Takeaways:

(01:36) LinkedIn minimizes human involvement in production to reduce errors.

(02:00) Airflow powers LinkedIn’s Continuous Deployment platform.

(05:43) Continuous deployment adoption grew from 8% to a targeted 80%.

(11:25) Kubernetes ensures scalability and flexibility for deployments.

(12:04) A custom UI offers real-time deployment transparency.

(16:23) No-code YAML workflows simplify deployment tasks.

(17:18) Canaries and metrics ensure safe deployments across fabrics.

(20:45) A gateway service ensures redundancy across Airflow clusters.

(24:22) Abstractions let engineers focus on development, not logistics.

(25:20) Multi-language support in Airflow 3.0 simplifies adoption.

Resources Mentioned:

Rahul Gade -

https://www.linkedin.com/in/rahul-gade-68666818/

LinkedIn -

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

Apache Airflow -

https://airflow.apache.org/

Kubernetes -

https://kubernetes.io/

Open Policy Agent (OPA) -

https://www.openpolicyagent.org/

Backstage -

https://backstage.io/

Apache Airflow Survey -

https://astronomer.typeform.com/airflowsurvey24

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

63 حلقات

#Tech #Airflow

Optimizing Large-Scale Deployments at LinkedIn with Rahul Gade

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

published منذ عام واحد

MP3•منزل الحلقة

Rahul discusses the challenges of managing large-scale deployments across 6,000 services and how his team leverages Airflow to enhance efficiency, reliability and user accessibility.

Key Takeaways:

(01:36) LinkedIn minimizes human involvement in production to reduce errors.

(02:00) Airflow powers LinkedIn’s Continuous Deployment platform.

(05:43) Continuous deployment adoption grew from 8% to a targeted 80%.

(11:25) Kubernetes ensures scalability and flexibility for deployments.

(12:04) A custom UI offers real-time deployment transparency.

(16:23) No-code YAML workflows simplify deployment tasks.

(17:18) Canaries and metrics ensure safe deployments across fabrics.

(20:45) A gateway service ensures redundancy across Airflow clusters.

(24:22) Abstractions let engineers focus on development, not logistics.

(25:20) Multi-language support in Airflow 3.0 simplifies adoption.

Resources Mentioned:

Rahul Gade -

https://www.linkedin.com/in/rahul-gade-68666818/

LinkedIn -

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

Apache Airflow -

https://airflow.apache.org/

Kubernetes -

https://kubernetes.io/

Open Policy Agent (OPA) -

https://www.openpolicyagent.org/

Backstage -

https://backstage.io/

Apache Airflow Survey -

https://astronomer.typeform.com/airflowsurvey24

#AI #Automation #Airflow #MachineLearning

63 حلقات

#Tech #Airflow

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The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
The Future of Airflow Telemetry at Metyis with Bolke de Bruin 21:55

منذ 6 أيام21:55

21:55

Telemetry has the potential to guide the future of Airflow, but only if it’s implemented transparently and with community trust. In this episode, we’re joined by Bolke de Bruin , Director at Metyis and a long-time Airflow PMC member. Bolke discusses how telemetry has been handled in the past, why it matters now and what it will take to get it right. Key Takeaways: (03:20) The role of foundations in establishing credibility and sustainability. (04:52) Why data collection is critical to open-source project direction. (07:24) Lessons learned from previous approaches to user data collection. (10:23) The current state of telemetry in the project. (10:53) Community trust as a prerequisite for technical implementation. (12:54) The importance of managing sensitive data within trusted ecosystems. (16:37) Ethical considerations in balancing participation and access. (18:45) Forward-looking ideas for improving workflow design and usability. Resources Mentioned: Bolke de Bruin https://www.linkedin.com/in/bolke/ Metyis | LinkedIn https://www.linkedin.com/company/metyis/ Metyis | Website http://www.metyis.com Apache Airflow https://airflow.apache.org/ Airflow Summit https://airflowsummit.org/ Airflow Dev List https://lists.apache.org/list.html?dev@airflow.apache.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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

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Transforming the Airflow UI for Cloudera’s Users with Shubham Raj 22:28

منذ 13 يومًا22:28

22:28

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 team built a drag-and-drop DAG editor for non-coders, contributions which helped shape the Airflow 3.0 Ul and introduced features like external XCom control and bulk APls. 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 Raj https://www.linkedin.com/in/shubhamrajofficial/ Cloudera | LinkedIn https://www.linkedin.com/company/cloudera/ Cloudera | Website https://www.cloudera.com/ Apache Airflow https://airflow.apache.org/ 2023 Airflow Summit 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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Streamlining Thousands of Data Pipelines at Lyft with Yunhao Qing 19:34

منذ 16 يومًا19:34

19:34

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 Qing https://www.linkedin.com/in/yunhao-qing Lyft | LinkedIn https://www.linkedin.com/company/lyft/ Lyft | Website https://www.lyft.com/ Apache Airflow https://airflow.apache.org/ Astronomer https://www.astronomer.io/ Kubernetes https://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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Transforming Customer Education in Data Engineering at Astronomer with Marc Lamberti 22:19

منذ 27 يومًا22:19

22:19

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 Lamberti https://www.linkedin.com/in/marclamberti/ Astronomer | LinkedIn https://www.linkedin.com/company/astronomer/ Astronomer Academy https://academy.astronomer.io/ Airflow Fundamentals Certification https://www.astronomer.io/certification/ DAG Authoring Certification https://academy.astronomer.io/plan/astronomer-certification-dag-authoring-for-apache-airflow-exam The Complete Hands-On Introduction to Airflow https://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=PMNVD3025 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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Embracing Data Mesh and SQL Sensors for Scalable Workflows at lastminute.com with Alberto Crespi 30:09

منذ 5 weeks30:09

30:09

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 Crespi https://www.linkedin.com/in/crespialberto/ lastminute.com | Website https://lastminute.com Apache Airflow https://airflow.apache.org/ dbt Labs https://www.getdbt.com/ Astronomer Cosmos https://github.com/astronomer/astronomer-cosmos GitLab Slack https://slack.com/ Kubernetes https://kubernetes.io/ Confluence https://www.atlassian.com/software/confluence Slack https://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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
The AI-Ready Pipeline: Reimagining Airflow at Veyer® Logistics with Anu Pabla 23:21

منذ 6 weeks23:21

23:21

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 Pabla https://www.linkedin.com/in/atomicap/ The ODP Corporation https://www.linkedin.com/company/the-odp-corporation/ The ODP Corporation | Website https://www.theodpcorp.com/homepage Apache Airflow https://airflow.apache.org/ LlamaIndex https://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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Streamlining AI and ML Operations at IBM with BJ Adesoji and Ryan Yackel 24:44

منذ 7 weeks24:44

24:44

The orchestration layer is foundational to building robust AI- and ML-powered data pipelines, especially in complex hybrid enterprise environments. IBM’s partnership with Astronomer reflects a strategic alignment to simplify and scale Airflow-based workflows across industries. In this episode, we’re joined by IBM ’s Senior Product Manager, BJ Adesoji , and GTM PM and Growth Leader , Ryan Yackel . We discuss how IBM customers are using Airflow in production, the challenges they face at scale and what the new IBM–Astronomer collaboration unlocks. Key Takeaways: (03:09) The growing importance of orchestration tools in enterprise environments. (04:48) How organizations are expanding orchestration beyond traditional use cases. (05:24) Common patterns across industries adopting orchestration platforms. (07:16) Why orchestration is essential for supporting business-critical workloads. (10:00) The role of orchestration in compliance and regulatory processes. (13:02) Challenges enterprises face when managing orchestration infrastructure. (14:58) Opportunities to simplify and centralize orchestration at scale. (19:11) The value of integrating orchestration with broader data toolchains. (20:54) How AI is shaping the future of orchestrated data workflows. Resources Mentioned: BJ Adesoji https://www.linkedin.com/in/bj-soji/ Ryan Yackel https://www.linkedin.com/in/ryanyackel/ IBM | LinkedIn https://www.linkedin.com/company/databand-ai/ IBM Databand https://www.ibm.com/products/databand IBM DataStage https://www.ibm.com/products/datastage IBM watsonx.governance https://www.ibm.com/products/watsonx-governance IBM Knowledge Catalog https://www.ibm.com/products/knowledge-catalog Apache Airflow https://airflow.apache.org/ watsonx Orchestrate https://www.ibm.com/products/watsonx-orchestrate Domino https://domino.ai/ Astronomer https://www.astronomer.io/ Snowflake https://www.snowflake.com/en/ dbt Labs https://www.getdbt.com/ Amazon SageMaker https://aws.amazon.com/sagemaker/ Cloudera https://www.cloudera.com/ MongoDB https://www.mongodb.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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Inside the Custom Framework for Managing Airflow Code at Wix with Gil Reich 31:02

منذ 8 weeks31:02

31:02

Efficient orchestration and maintainability are crucial for data engineering at scale. Gil Reich , Data Developer for Data Science at Wix , shares how his team reduced code duplication, standardized pipelines, and improved Airflow task orchestration using a Python-based framework built within the data science team. In this episode, Gil explains how this internal framework simplifies DAG creation, improves documentation accuracy, and enables consistent task generation for machine learning pipelines. He also shares lessons from complex DAG optimization and maintaining testable code. Key Takeaways: (03:23) Code duplication creates long-term problems. (08:16) Frameworks bring order to complex pipelines. (09:41) Shared functions cut down repetitive code. (17:18) Auto-generated docs stay accurate by design. (22:40) On-demand DAGs support real-time workflows. (25:08) Task-level sensors improve run efficiency. (27:40) Combine local runs with automated tests. (30:09) Clean code helps teams scale faster. Resources Mentioned: Gil Reich https://www.linkedin.com/in/gilreich/ Wix | LinkedIn https://www.linkedin.com/company/wix-com/ Wix | Website https://www.wix.com/ DS DAG Framework https://airflowsummit.org/slides/2024/92-refactoring-dags.pdf Apache Airflow https://airflow.apache.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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Modernizing Legacy Data Systems With Airflow at Procter & Gamble with Adonis Castillo Cordero 22:13

منذ 9 weeks22:13

22:13

Legacy architecture and AI workloads pose unique challenges at scale, especially in a global enterprise with complex data systems. In this episode, we explore strategies to proactively monitor and optimize pipelines while minimizing downstream failures. Adonis Castillo Cordero , Senior Automation Manager at Procter & Gamble , joins us to share actionable best practices for dependency mapping, anomaly detection and architecture simplification using Apache Airflow. Key Takeaways: (03:13) Integrating legacy data systems into modern architecture. (05:51) Designing workflows for real-time data processing. (07:57) Mapping dependencies early to avoid pipeline failures. (09:02) Building automated monitoring into orchestration frameworks. (12:09) Detecting anomalies to prevent performance bottlenecks. (15:24) Monitoring data quality to catch silent failures. (17:02) Prioritizing responses based on impact severity. (18:55) Simplifying dashboards to highlight critical metrics. Resources Mentioned: Adonis Castillo Cordero https://www.linkedin.com/in/adoniscc/ Procter & Gamble | LinkedIn https://www.linkedin.com/company/procter-and-gamble/ Procter & Gamble | Website http://www.pg.com Apache Airflow https://airflow.apache.org/ OpenLineage https://openlineage.io/ Azure Monitor https://azure.microsoft.com/en-us/products/monitor/ AWS Lookout for Metrics https://aws.amazon.com/lookout-for-metrics/ Monte Carlo https://www.montecarlodata.com/ Great Expectations https://greatexpectations.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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Building an End-to-End Data Observability System at Netflix with Joseph Machado 38:54

منذ 10 weeks38:54

38:54

Building reliable data pipelines starts with maintaining strong data quality standards and creating efficient systems for auditing, publishing and monitoring. In this episode, we explore the real-world patterns and best practices for ensuring data pipelines stay accurate, scalable and trustworthy. Joseph Machado , Senior Data Engineer at Netflix , joins us to share practical insights gleaned from supporting Netflix’s Ads business as well as over a decade of experience in the data engineering space. He discusses implementing audit publish patterns, building observability dashboards, defining in-band and separate data quality checks, and optimizing data validation across large-scale systems. Key Takeaways: . (03:14) Supporting data privacy and engineering efficiency within data systems. (10:41) Validating outputs with reconciliation checks to catch transformation issues. (16:06) Applying standardized patterns for auditing, validating and publishing data. (19:28) Capturing historical check results to monitor system health and improvements. (21:29) Treating data quality and availability as separate monitoring concerns. (26:26) Using containerization strategies to streamline pipeline executions. (29:47) Leveraging orchestration platforms for better visibility and retry capability. (31:59) Managing business pressure without sacrificing data quality practices. (35:46) Starting simple with quality checks and evolving toward more complex frameworks. Resources Mentioned: Joseph Machado https://www.linkedin.com/in/josephmachado1991/ Netflix | LinkedIn https://www.linkedin.com/company/netflix/ Netflix | Website https://www.netflix.com/browse Start Data Engineering https://www.startdataengineering.com/ Apache Airflow https://airflow.apache.org/ dbt Labs https://www.getdbt.com/ Great Expectations https://greatexpectations.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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Why Developer Experience Shapes Data Pipeline Standards at Next Insurance with Snir Israeli 30:28

منذ 11 weeks30:28

30:28

Creating consistency across data pipelines is critical for scaling engineering teams and ensuring long-term maintainability. In this episode, Snir Israeli , Senior Data Engineer at Next Insurance , shares how enforcing coding standards and investing in developer experience transformed their approach to data engineering. He explains how implementing automated code checks, clear documentation practices and a scoring system helped drive alignment across teams, improve collaboration and reduce technical debt in a fast-growing data environment. Key Takeaways: (02:59) Inconsistencies in code style create challenges for collaboration and maintenance. (04:22) Programmatically enforcing rules helps teams scale their best practices. (08:55) Performance improvements in data pipelines lead to infrastructure cost savings. (13:22) Developer experience is essential for driving adoption of internal tools. (19:44) Dashboards can operationalize standards enforcement and track progress over time. (22:49) Standardization accelerates onboarding and reduces friction in code reviews. (25:39) Linting rules require ongoing maintenance as tools and platforms evolve. (27:47) Starting small and involving the team leads to better adoption and long-term success. Resources Mentioned: Snir Israeli https://www.linkedin.com/in/snir-israeli/ Next Insurance | LinkedIn https://www.linkedin.com/company/nextinsurance/ Next Insurance | Website https://www.nextinsurance.com/ Apache Airflow https://airflow.apache.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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Data Quality and Observability at Tekmetric with Ipsa Trivedi 22:49

منذ 12 weeks22:49

22:49

Airflow’s adaptability is driving Tekmetric’s ability to unify complex data workflows, deliver accurate insights and support both internal operations and customer-facing services — all within a rapidly growing startup environment. In this episode, Ipsa Trivedi , Lead Data Engineer at Tekmetric , shares how her team is standardizing pipelines while supporting unique customer needs. She explains how Airflow enables end-to-end data services, simplifies orchestration across varied sources and supports scalable customization. Ipsa also highlights early wins with Airflow, its intuitive UI and the team's roadmap toward data quality, observability and a future self-serve data platform. Key Takeaways: (02:26) Powering auto shops nationwide with a unified platform. (05:17) A new data team was formed to centralize and scale insights. (07:23) Flexible, open source and made to fit — Airflow wins. (10:42) Pipelines handle anything from email to AWS. (12:15) Custom DAGs fit every team’s unique needs. (17:01) Data quality checks are built into the plan. (18:17) Self-serve data mesh is the end goal. (19:59) Airflow now fits so well, there's nothing left on the wishlist. Resources Mentioned: Ipsa Trivedi https://www.linkedin.com/in/ipsatrivedi/ Tekmetric | LinkedIn https://www.linkedin.com/company/tekmetric/ Tekmetric | Website https://www.tekmetric.com/ Apache Airflow https://airflow.apache.org/ AWS RDS https://aws.amazon.com/free/database/?trk=fc551e06-56b0-418c-9ddd-5c9dba18569b&sc_channel=ps&ef_id=CjwKCAjwzMi_BhACEiwAX4YZULS4jV2Xpnpcac_Q3eS9BAg-klKUDyCt6XSdOul8BLHkmWzFFh4NXRoCGhQQAvD_BwE:G:s&s_kwcid=AL!4422!3!548989592596!e!!g!!amazon%20sql%20database!11543056228!112002958549&gclid=CjwKCAjwzMi_BhACEiwAX4YZULS4jV2Xpnpcac_Q3eS9BAg-klKUDyCt6XSdOul8BLHkmWzFFh4NXRoCGhQQAvD_BwE Astro by Astronomer https://www.astronomer.io/product/ 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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Introducing Apache Airflow® 3 with Vikram Koka and Jed Cunningham 27:28

منذ 13 weeks27:28

27:28

The Airflow 3.0 release marks a significant leap forward in modern data orchestration, introducing architectural upgrades that improve scalability, flexibility and long-term maintainability. In this episode, we welcome Vikram Koka , Chief Strategy Officer at Astronomer , and Jed Cunningham , Principal Software Engineer at Astronomer , to discuss the architectural foundations, new features and future implications of this milestone release. They unpack the rationale behind DAG versioning and task execution interface, explain how Airflow now integrates more seamlessly within broader data ecosystems and share how these changes lay the groundwork for multi-cloud deployments, language-agnostic workflows and stronger enterprise security. Key Takeaways: (02:28) Modern orchestration demands new infrastructure approaches. (05:02) Removing legacy components strengthens system stability. (06:26) Major releases provide the opportunity to reduce technical debt. (08:31) Frontend and API modernization enable long-term adaptability. (09:36) Event-based triggers expand integration possibilities. (11:54) Version control improves visibility and execution reliability. (14:57) Centralized access to workflow definitions increases flexibility. (21:49) Decoupled architecture supports distributed and secure deployments. (26:17) Community collaboration is essential for sustainable growth. Resources Mentioned: Astronomer Website https://www.astronomer.io Apache Airflow https://airflow.apache.org/ Git Bundle https://git-scm.com/book/en/v2/Git-Tools-Bundling FastAPI https://fastapi.tiangolo.com/ React https://react.dev/ 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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
Airflow in Action: Powering Instacart's Complex Ecosystem 25:14

منذ 14 weeks25:14

25:14

The evolution of data orchestration at Instacart highlights the journey from fragmented systems to robust, standardized infrastructure. This transformation has enabled scalability, reliability and democratization of tools for diverse user personas. In this episode, we’re joined by Anant Agarwal , Software Engineer at Instacart , who shares insights into Instacart's Airflow journey, from its early adoption in 2019 to the present-day centralized cluster approach. Anant discusses the challenges of managing disparate clusters, the implementation of remote executors, and the strategic standardization of infrastructure and DAG patterns to streamline workflows. Key Takeaways: (03:49) The impact of external events on business growth and technological evolution. (04:31) Challenges of managing decentralized systems across multiple teams. (06:14) The importance of standardizing infrastructure and processes for scalability. (09:51) Strategies for implementing efficient and repeatable deployment practices. (12:17) Addressing diverse user personas with tailored solutions. (14:47) Leveraging remote execution to enhance flexibility and scalability. (18:36) Benefits of transitioning to a centralized system for organization-wide use. (20:57) Maintaining an upgrade cadence to stay aligned with the latest advancements. (23:35) Anticipation for new features and improvements in upcoming software versions. Resources Mentioned: Anant Agarwal https://www.linkedin.com/in/anantag/ Instacart | LinkedIn https://www.linkedin.com/company/instacart/ Instacart | Website https://www.instacart.com Apache Airflow https://airflow.apache.org/ AWS Amazon https://aws.amazon.com/ecs/ Terraform https://www.terraform.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 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…

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

1
From ETL to Airflow: Transforming Data Engineering at Deloitte Digital with Raviteja Tholupunoori 27:42

منذ 15 weeks27:42

27:42

Data orchestration at scale presents unique challenges, especially when aiming for flexibility and efficiency across cloud environments. Choosing the right tools and frameworks can make all the difference. In this episode, Raviteja Tholupunoori, Senior Engineer at Deloitte Digital , joins us to explore how Airflow enhances orchestration, scalability and cost efficiency in enterprise data workflows. Key Takeaways: (01:45) Early challenges in data orchestration before implementing Airflow. (02:42) Comparing Airflow with ETL tools like Talend and why flexibility matters. (04:24) The role of Airflow in enabling cloud-agnostic data processing. (05:45) Key lessons from managing dynamic DAGs at scale. (13:15) How hybrid executors improve performance and efficiency. (14:13) Best practices for testing and monitoring workflows with Airflow. (15:13) The importance of mocking mechanisms when testing DAGs. (17:57) How Prometheus, Grafana and Loki support Airflow monitoring. (22:03) Cost considerations when running Airflow on self-managed infrastructure. (23:14) Airflow’s latest features, including hybrid executors and dark mode. Resources Mentioned: Raviteja Tholupunoori https://www.linkedin.com/in/raviteja0096/?originalSubdomain=in Deloitte Digital https://www.linkedin.com/company/deloitte-digital/ Apache Airflow https://airflow.apache.org/ Grafana https://grafana.com/solutions/apache-airflow/monitor/ Astronomer Presents: Exploring Apache Airflow® 3 Roadshows https://www.astronomer.io/events/roadshow/ 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 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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