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Hi, we’re Tim Berglund, Adi Polak, and Viktor Gamov and we’re excited to bring you the Confluent Developer podcast (formerly “Streaming Audio.”) Our hand-crafted weekly episodes feature in-depth interviews with our community of software developers (actual human beings - not AI) talking about some of the most interesting challenges they’ve faced in their careers. We aim to explore the conditions that gave rise to each person’s technical hurdles, as well as how their experiences transformed their understanding and approach to building systems.
Whether you’re a seasoned open source data streaming engineer, or just someone who’s interested in learning more about Apache Kafka®, Apache Flink® and real-time data, we hope you’ll appreciate the stories, the discussion, and our effort to bring you a high-quality show worth your time.

Can you use Apache Kafka® and Python together? What’s the current state of Python support? And what are the best options to get started? In this episode, Dave Klein joins Kris to talk about all things Kafka and Python: the libraries, the tools, and the pros & cons. He also talks about the new course he just launched to support Python programmers entering the event-streaming world.Dave has been an active member of the Kafka community for many years and noticed that there were a lot of Kafka resources for Java but few for Python. So he decided to create a course to help people get started using Python and Kafka together.Historically, Java has had the most documentation, and people have often missed how good the Python support is for Kafka users. Python and Kafka are an ideal fit for machine learning applications and data engineering in general. Yet there are a lot of use cases for building, streaming, and machine learning pipelines. In fact, someone conducted a survey to find out what languages were most popular in the Kafka community and Python came in second after Java. That’s how Dave got the idea to create a course for newbies.In this course, Dave combines video lectures with code-heavy exercises to give developers a taste of what the code looks like, how to structure it, a preview of the shape of the code, and the structure of the classes and the functions so you can get hands-on practice using the library. He also covers building a producer and a consumer and using the admin client. And, of course, there is a module that covers working with the schemas supported by the Kafka library.Dave explains that Python opens up a world of opportunity and is ripe for expansion. So if you are ready to dive in, head over to developer.confluent.io to learn more about Dave’s course.EPISODE LINKSBlog: Getting Started with Python for Apache KafkaCourse: Introduction to Apache Kafka for Python DevelopersStep-by-step guide: Building a Python client application for KafkaCoding in MotionBuilding and Designing Events and Event Streams with Apache KafkaWatch the video version of this podcastKris Jenkins’ TwitterStreaming Audio Playlist Join the Confluent CommunityLearn more with Kafka tutorials, resources, and guides at Confluent DeveloperSEASON 2 Hosted by Tim Berglund, Adi Polak and Viktor Gamov Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed Music by Coastal Kites Artwork by Phil Vo 🎧 Subscribe to Confluent Developer wherever you listen to podcasts. ▶️ Subscribe on YouTube, and hit the 🔔 to catch new episodes. 👍 If you enjoyed this, please leave us a rating. 🎧 Confluent also has a podcast for tech leaders: "Life Is But A Stream" hosted by our friend, Joseph Morais.

In this episode, Kris interviews Doron Porat, Director of Infrastructure at Yotpo, and Liran Yogev, Director of Engineering at ZipRecruiter (formerly at Yotpo), about their experiences and strategies in dealing with data modeling at scale.Yotpo has a vast and active data lake, comprising thousands of datasets that are processed by different engines, primarily Apache Spark™. They wanted to provide users with self-service tools for generating and utilizing data with maximum flexibility, but encountered difficulties, including poor standardization, low data reusability, limited data lineage, and unreliable datasets.The team realized that Yotpo's modeling layer, which defines the structure and relationships of the data, needed to be separated from the execution layer, which defines and processes operations on the data.This separation would give programmers better visibility into data pipelines across all execution engines, storage methods, and formats, as well as more governance control for exploration and automation.To address these issues, they developed YODA, an internal tool that combines excellent developer experience, DBT, Databricks, Airflow, Looker and more, with a strong CI/CD and orchestration layer.Yotpo is a B2B, SaaS e-commerce marketing platform that provides businesses with the necessary tools for accurate customer analytics, remarketing, support messaging, and more.ZipRecruiter is a job site that utilizes AI matching to help businesses find the right candidates for their open roles.EPISODE LINKSCurrent 2022 Talk: Next Gen Data Modeling in the Open Data PlatformData Mesh 101Data Mesh Architecture: A Modern Distributed Data ModelWatch the video version of this podcastKris Jenkins’ TwitterStreaming Audio Playlist Join the Confluent CommunityLearn more with Kafka tutorials, resources, and guides at Confluent DeveloperLive demo: Intro to Event-Driven Microservices with ConfluentUse PODCAST100 to get an additional $100 of free Confluent Cloud usage (details)SEASON 2 Hosted by Tim Berglund, Adi Polak and Viktor Gamov Produced and Edited by Noelle Gallagher, Peter Furia and Nurie Mohamed Music by Coastal Kites Artwork by Phil Vo 🎧 Subscribe to Confluent Developer wherever you listen to podcasts. ▶️ Subscribe on YouTube, and hit the 🔔 to catch new episodes. 👍 If you enjoyed this, please leave us a rating. 🎧 Confluent also has a podcast for tech leaders: "Life Is But A Stream" hosted by our friend, Joseph Morais.