The State of Machine Learning in DevOps - DZone DevOps

DevOps methodologies are increasingly generating large and diverse data sets across the entire application lifecycle -- from development, to deployment, to application performance management, and only a robust monitoring and analysis layer can truly harness this data for the ultimate DevOps goal of end-to-end automation. The recent rise of machine learning -- and related capabilities such as predictive analytics and artificial intelligence -- has started to push organizations to explore the implementation of a new data analysis model that relies on mathematical algorithms. Despite the promised benefit of helping teams optimize operations and gain more visibility into their data, adoption of machine learning into the DevOps toolbox is limited. Let's try and examine why. Let's start with understanding how machine learning can fit into and benefit the DevOps methodology.