Source: devops.com
The Promise of AI for DevOps in 2021Category: Data, artificial-intelligence
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DevOps is a natural target for AI-driven efficiencies, as it involves frequently repeated processes that generate mountains of data. It seems reasonable to expect that, like other domains that require decisions to be made based on large volumes of data, AI will play an important role in DevOps, too.
But machine learning (ML) techniques bring with them the promise of teasing out inherent characteristics that underpin the data, and that are often impossible for humans to observe. There are two main points in the DevOps process where large amounts of data are generated, and where machine learning would be most useful when applied: testing and release and monitoring.
DevOps is a natural target for AI-driven efficiencies, as it involves frequently repeated processes that generate mountains of data. It seems reasonable to expect that, like other domains that require decisions to be made based on large volumes of data, AI will play an important role in DevOps, too.
But machine learning (ML) techniques bring with them the promise of teasing out inherent characteristics that underpin the data, and that are often impossible for humans to observe. There are two main points in the DevOps process where large amounts of data are generated, and where machine learning would be most useful when applied: testing and release and monitoring.
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