The live session is at 9:30AM PDT/12:30PM EDT/6:30PM CET. If you can not make the live event, still register to receive the recording.
Data scientists and machine learning engineers shouldn’t necessarily need to know too much about Kubernetes (K8s), yet many are interested and it can be a differentiator in the job market. So we’re here to help! This livestream will be a gentle introduction to K8s for data scientists and MLEs who want to take their production DS/ML chops to the next level.
Bryan Galvin, who works on ML infrastructure at Best Egg, and Shri Javadekar, A K8s insider and engineer at Outerbounds, join Hugo Bowne-Anderson to introduce K8s to those who want to know a bit more. In this livestream, you’ll learn:
- What K8s is and what it isn’t, why should you care;
- What a typical journey in moving from statistics, data analysis and data science to infrastructure looks like;
- The differences between K8s, Docker, and other moving parts (such as Terraform);
- How to understand the lifecycle of a K8s project;
- What the core concepts of deploying K8s workloads are;
We’ll also do some live coding and show you how to take code that you’ve prototyped locally and :
- Deploy it to a K8s cluster;
- Scale the workload;
- Schedule it!