How DevOps Can Use Operational Data Science to See into the Cloud

(Bluebay/Shutterstock) As system architecture moves to the cloud, understanding the impacts of new code releases and points of failure requires a whole new approach. The increase in agility, bandwidth, and security has been matched by an increase in complexity. DevOps strategies need intelligence from real-time operational metrics to keep a product in optimal condition. Effective system maintenance requires visibility into a maze of interdependent operations. The need to direct DevOps efforts with dynamic operational intelligence has led to the emergence of a hybrid field: Operational Data Science. Ask any CTO or CIO about DevOps and data science, and they’ll say that smart enterprises are investing in expertise for both skill sets. The DevOps approach has made IT more responsive to business needs, helping departments improve faster and more collaboratively. Big…


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