logo
episode-header-image
Apr 2022
38m 14s

Accelerate And Simplify Cloud Native Dev...

Tobias Macey
About this episode

Summary

Cloud native architectures have been gaining prominence for the past few years due to the rising popularity of Kubernetes. This introduces new complications to development workflows due to the need to integrate with multiple services as you build new components for your production systems. In order to reduce the friction involved in developing applications for cloud native environments Michael Schilonka created Gefyra. In this episode he explains how it connects your local machine to a running Kubernetes environment so that you can rapidly iterate on your software in the context of the whole system. He also shares how the Django Hurricane plugin lets your applications work closely with the Kubernetes process model.

Announcements

  • Hello and welcome to Podcast.__init__, the podcast about Python’s role in data and science.
  • When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With the launch of their managed Kubernetes platform it’s easy to get started with the next generation of deployment and scaling, powered by the battle tested Linode platform, including simple pricing, node balancers, 40Gbit networking, dedicated CPU and GPU instances, and worldwide data centers. Go to pythonpodcast.com/linode and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show!
  • So now your modern data stack is set up. How is everyone going to find the data they need, and understand it? Select Star is a data discovery platform that automatically analyzes & documents your data. For every table in Select Star, you can find out where the data originated, which dashboards are built on top of it, who’s using it in the company, and how they’re using it, all the way down to the SQL queries. Best of all, it’s simple to set up, and easy for both engineering and operations teams to use. With Select Star’s data catalog, a single source of truth for your data is built in minutes, even across thousands of datasets. Try it out for free and double the length of your free trial today at pythonpodcast.com/selectstar. You’ll also get a swag package when you continue on a paid plan.
  • Your host as usual is Tobias Macey and today I’m interviewing Michael Schilonka about Gefyra and what is involved with developing applications for Kubernetes environments

Interview

  • Introductions
  • How did you get introduced to Python?
  • Can you describe what Gefyra is and the story behind it?
  • What are the challenges that Kubernetes introduces to the development process?
    • What are some of the strategies that developers might use for developing and testing applications that are deployed to Kubernetes environments?
  • What are the use cases that Gefyra is focused on enabling?
    • What are some of the other tools or platforms that Gefyra might replace or supplement?
  • What are the services that need to be present in the K8s cluster to enable Gefyra’s functionality?
  • Can you describe how Gefyra is implemented?
    • How have the design and goals of the project changed since you first started working on it?
  • What is the process for getting Gefyra set up between a K8s cluster and a developer’s laptop?
  • Can you describe what the developer’s workflow looks like when using Gefyra?
    • How do you avoid collisions/resource contention among a team of developers who are working on the same project?
  • What are some of the ways that developing for Kubernetes influences the architectural and design decisions for a project?
  • What are some of the additional practices or systems that you have found to be beneficial for accelerating development in cloud-native environments?
  • What are the most interesting, innovative, or unexpected ways that you have seen Gefyra used?
  • What are the most interesting, unexpected, or challenging lessons that you have learned while working on Gefyra?
  • When is Gefyra the wrong choice?
  • What do you have planned for the future of Gefyra?

Keep In Touch

Picks

Links

The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA

Up next
Dec 2022
Update Your Model's View Of The World In Real Time With Streaming Machine Learning Using River
Preamble This is a cross-over episode from our new show The Machine Learning Podcast, the show about going from idea to production with machine learning. Summary The majority of machine learning projects that you read about or work on are built around batch processes. The model i ... Show More
1h 16m
Dec 2022
Declarative Machine Learning For High Performance Deep Learning Models With Predibase
Preamble This is a cross-over episode from our new show The Machine Learning Podcast, the show about going from idea to production with machine learning. Summary Deep learning is a revolutionary category of machine learning that accelerates our ability to build powerful inference ... Show More
59m 22s
Nov 2022
Build Better Machine Learning Models With Confidence By Adding Validation With Deepchecks
Preamble This is a cross-over episode from our new show The Machine Learning Podcast, the show about going from idea to production with machine learning. Summary Machine learning has the potential to transform industries and revolutionize business capabilities, but only if the mo ... Show More
47m 37s
Recommended Episodes
Feb 2025
#495: OSMnx: Python and OpenStreetMap
On this episode, I’m joined by Dr. Jeff Boeing, an assistant professor at the University of Southern California whose research spans urban planning, spatial analysis, and data science. We explore why OpenStreetMap is such a powerful source of global map data—and how Jeff’s Python ... Show More
1h 1m
Sep 2021
An Exploration Of The Data Engineering Requirements For Bioinformatics
Summary Biology has been gaining a lot of attention in recent years, even before the pandemic. As an outgrowth of that popularity, a new field has grown up that pairs statistics and compuational analysis with scientific research, namely bioinformatics. This brings with it a uniqu ... Show More
55m 10s
May 2022
Insights And Advice On Building A Data Lake Platform From Someone Who Learned The Hard Way
Summary Designing a data platform is a complex and iterative undertaking which requires accounting for many conflicting needs. Designing a platform that relies on a data lake as its central architectural tenet adds additional layers of difficulty. Srivatsan Sridharan has had the ... Show More
58m 11s
Mar 2021
Data Quality Management For The Whole Team With Soda Data
Summary Data quality is on the top of everyone’s mind recently, but getting it right is as challenging as ever. One of the contributing factors is the number of people who are involved in the process and the potential impact on the business if something goes wrong. In this episod ... Show More
58 m
Aug 2024
The Evolution of DataOps: Insights from DataKitchen's CEO
Summary In this episode of the Data Engineering Podcast, host Tobias Macey welcomes back Chris Berg, CEO of DataKitchen, to discuss his ongoing mission to simplify the lives of data engineers. Chris explains the challenges faced by data engineers, such as constant system failures ... Show More
53m 30s
Feb 2025
The Future of Data Engineering: AI, LLMs, and Automation
Summary In this episode of the Data Engineering Podcast Gleb Mezhanskiy, CEO and co-founder of DataFold, talks about the intersection of AI and data engineering. He discusses the challenges and opportunities of integrating AI into data engineering, particularly using large langua ... Show More
59m 39s
Feb 2024
Using Trino And Iceberg As The Foundation Of Your Data Lakehouse
Summary A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Multiple open source projects and vendors have been working together to make this vision a reality. In this ... Show More
58m 46s
Aug 2018
258: A Foot in the Door
This week, we debut the new show format! First, Marshall formally introduces himself, and we answer a listener's question about how to get their foot in the UX door. Then we cover a few headlines, fight about stock vs. third-party apps, and share a couple cool things. If you have ... Show More
38m 51s
Aug 2019
Building Tools And Platforms For Data Analytics
Summary Data engineers are responsible for building tools and platforms to power the workflows of other members of the business. Each group of users has their own set of requirements for the way that they access and interact with those platforms depending on the insights they are ... Show More
48m 7s
Dec 2024
The Art of Database Selection and Evolution
Summary In this episode of the Data Engineering Podcast Sam Kleinman talks about the pivotal role of databases in software engineering. Sam shares his journey into the world of data and discusses the complexities of database selection, highlighting the trade-offs between differen ... Show More
59m 56s