Kubernetes is a framework that aims to simplify the work of running applications in production, but it forces you to adopt new patterns for debugging and resolving issues in your systems. Robusta is aimed at making that a more pleasant experience for developers and operators through pre-built automations, easy debugging, and a simple means of creating your own event-based workflows to find, fix, and alert on errors in production. In this episode Natan Yellin explains how the project got started, how it is architected and tested, and how you can start using it today to keep your Python projects running reliably.
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 Natan Yellin about Robusta,
- How did you get introduced to Python?
- Can you describe what Robusta is and the story behind it?
- What are some of the challenges that teams face when running their systems in Kubernetes?
- How does Robusta help address those difficulties?
- How does Robusta compare to e.g. Rookout?
- What are some of the ways that Robusta is able to provide specific insights for Python applications?
- Can you describe how Robusta is implemented?
- What are some of the most challenging engineering tasks that you have had to work through while building Robusta?
- How have the capabilities and components evolved from when you started working on it?
- What is the workflow for integrating Robusta into a Kubernetes environment and a team’s maintenance processes?
- What are some examples of the kinds of questions that Robusta can help answer out of the box?
- What are some tasks that Robusta facilitates which require manual exploration?
- What are the interfaces available for customizing and extending the functionality of Robusta?
- What is involved in adding a new automation capability to Robusta?
- How have you approached the design of the tool to make it ergonomic and intuitive so that it doesn’t contribute to the stresses of dealing with errors in production?
- Given that it is a tool to help resolve problems in production infrastructure, how have you worked to ensure its reliability and resilience?
- What is the governance and sustainability model for Robusta?
- What are the most interesting, innovative, or unexpected ways that you have seen Robusta used?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on Robusta?
- When is Robusta the wrong choice?
- What do you have planned for the future of Robusta?
Keep In Touch
- Kubernetes: Up And Running (affiliate link)
- Kubernetes for SysAdmins Youtube video by Kelsey Hightower
- Learn to delegate
- Thank you for listening! Don’t forget to check out our other show, the Data Engineering Podcast for the latest on modern data management.
- Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
- If you’ve learned something or tried out a project from the show then tell us about it! Email firstname.lastname@example.org) with your story.
- To help other people find the show please leave a review on iTunes and tell your friends and co-workers
- Objective C
- Google AppEngine
- OOM Killer
- Bin Packing/Knapsack Problem
- Kubernetes Pods
- VSCode Debugger
- Helm – Kubernetes package manager
- Why Profiler