JAX London, 4–7 October 2021
The Conference for Java & Software Innovation

From DevOps to MLOps

This talk originates from the archive. To the CURRENT program
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Tuesday, October 6 2020
12:00 - 12:45

Machine Learning is hot but organisations are struggling to run it in live and MLOps is not easy to master. DevOps skills are needed but in more than just the usual DevOps ways. The key reasons are that the development/delivery workflow is different and the kind of software artifacts involved are different. We will explore the differences and look at emerging open source projects in order to appreciate why the DevOps for machine learning space is growing and the needs that it addresses.

Getting a better picture of MLOps will help us in lots of ways. It will help us evaluate Machine Learning Operations (MLOps) tools and platforms. We’ll come to understand the specific needs for governance, versioning and monitoring in machine learning. We’ll get a sense for the range of MLOps use-cases and better understand how to scope Machine Learning projects.

Behind the Tracks

Software Architecture & Design
Software innovation & more
Architecture structure & more
Agile & Communication
Methodologies & more
Emerging Technologies
Everything about the latest technologies
DevOps & Continuous Delivery
Delivery Pipelines, Testing & more
Cloud & Modern Infrastructure
Everything about new tools and platforms
Big Data & Machine Learning
Saving, processing & more