MLops: Making sense of a hot mess

by | Aug 1, 2022 | Technology

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The MLops market may still be hot when it comes to investors. But for enterprise end users, it may seem like a hot mess. 

The MLops ecosystem is highly fragmented, with hundreds of vendors competing in a global market that was estimated to be $612 million in 2021 and is projected to reach over $6 billion by 2028. But according to Chirag Dekate, a VP and analyst at Gartner Research, that crowded landscape is leading to confusion among enterprises about how to get started and what MLops vendors to use. 

“We are seeing end users getting more mature in the kind of operational AI ecosystems they’re building – leveraging Dataops and MLops,” said Dekate. That is, enterprises take their data source requirements, their cloud or infrastructure center of gravity, whether it’s on-premise, in the cloud or hybrid, and then integrate the right set of tools. 

But it can be hard to pin down the right set of tools.

“In most cases, we are tracking close to 300-plus MLops companies – each claims to offer MLops, but they offer piecemeal capabilities,” said Dekate.

Some might offer a feature store, for example, while others might offer a model training environment or model deployment capabilities.

“Some of the most common questions we get asked are, ‘Where do we start?’ ‘How do we scale?’ ‘How do we navigate the vendor mix?’” he said. “Should they start with a platform approach, essentially leveraging Amazon SageMaker, Microsoft Azure, or Google Vertex? Or should they piece together a custom tool chain where they partner with different solution providers or a startup ecosystem?” 

Chirag Dekate

Different MLops approaches can work

MLops emerged as a set of best practices less than a decade …

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