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.
Does everyone in your team ask you which database table they should use? Or if you can help them with their SQL query? If so, check out Select Star! It’s an automated data discovery portal that can save you hours of time every week.
From analyzing your metadata, query logs, and dashboard activities, Select Star will automatically document your datasets. For every table in Select Star, you can find out where the data originated from, which dashboards are built on top of it, who’s using the data 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 in data is built in minutes, even across thousands of datasets.
Try it out for free at pythonpodcast.com/selectstar. If you’re a Podcast.__init__ subscriber, we’ll double the length of your free trial and send you a swag package when you continue on a paid plan.
Do you want to try out some of the tools and applications that you heard about on Podcast.__init__? Do you have a side project that you want to share with the world? With Linode’s managed Kubernetes platform it’s now even easier to get started with the latest in cloud technologies. With the combined power of the leading container orchestrator and the speed and reliability of Linode’s object storage, node balancers, block storage, and dedicated CPU or GPU instances, you’ve got everything you need to scale up. Go to pythonpodcast.com/linode today and get a $100 credit to launch a new cluster, run a server, upload some data, or… And don’t forget to thank them for being a long time supporter of Podcast.__init__!
- 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
- 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
- kubernetes.el – Kubernetes interface for Emacs
- Kopf framework
- Django Hurricane
- Sidecar Pattern
- Kubernetes Patterns book
- 12 Factor App
- Kubernetes Operator
- Kubernetes CRD (Custom Resource Definition