DevOps Pro Europe 2022

May 30 - June 3

Workshops

Online

May 24 - 26

Conference

Online

Michael J. Garbade

Positon: CEO/Founder

Company: Education Ecosystem

Country: US

Biography

Garbade is the CEO/Founder Education Ecosystem. He has worked at Amazon, GE, Rebate Networks, Y-combinator. Serial Entrepreneur. Experienced with raising venture funding. He speaks English and German as mother tongues. He holds a Masters in Business Administration and Physics, and a PhD in venture capital Financing.

He is a Python, Django and DevOps Engineer. He writes technical and business articles in leading blogs like Opensource.com, Dzone.com, Cybrary, Businessinsider, Entrepreneur.com, TechinAsia, Coindesk and Cointelegraph. He is a frequent speaker and panelist at tech and blockchain conferences around the globe. He serves as a start-up mentor at Accel Springer Accelerator, NY Edtech Acccelerator, Seedstars and Learnlaunch Accelerator. He loves hackathons and serves as a technical Judge on hackathon panels. 

Talk

Kubernetes for MLOps: How to Scale Enterprise Machine Learning, Deep Learning, Artificial Intelligence

Enterprises continue to develop interest in Machine Learning, Deep Learning and Artificial Intelligence, dedicating huge resources to ML/DL and AI projects. As the projects grow in size and scale, it has become critical that they build sustainable processes for model development and deployment.

Containers are a foundational technology for both DevOps and Machine Learning Operations (MLOps). They provide a core piece of functionality that allows a given piece of code—whether a notebook, an experiment, or a deployed model—to run anywhere. This presentation explores the role that the container orchestration system Kubernetes plays in supporting MLOps.

In the talk, Michael will demonstrate how Kubernetes, a container orchestration technology provides a lot of options to customize deployments and supports deployment of complex architectures.

The presentation will help engineers and organizations with on-premise production to automate their processes and environments. It will also help to show how DevOps and MLOps projects can be much more robust in resource placement.

Session Keywords

🔑 AI
🔑 Kubernetes
🔑 Scalability