2min chapter

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Why is MLOps Hard in an Enterprise? // Maria Vechtomova & Basak Eskili // MLOps Podcast #159

MLOps.community

CHAPTER

The Differences Between MLOps and DevOps

The data part makes all the difference here because even if your code didn't change, your data did change and errors may appear. So getting access to production data in development environment might be very important for data science products. Another one is checking for the quality monitoring. Check for the quality of your model when it's deployed. There are also some type of health checks that you need to perform. And if you don't have those checks in place, you just wouldn't know because, well, from the software point of view, everything is just fine. so these two differences are the biggest ones.

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