According to a recent press release, “XebiaLabs, the recognized leader in enterprise-class DevOps and Continuous Delivery software tools, today announced the first predictive risk solution for DevOps that warns teams of delays and risks in the software delivery process. Using a new DevOps Prediction Engine, the XebiaLabs DevOps Platform’s Risk Prediction Module combines machine learning with a proprietary algorithm to give teams a “weather forecast” for their releases before those releases even start to run. It’s hard for DevOps teams to predict factors that will delay releases or cause them to fail—and teams are often surprised by failures after release processes have already started, leaving them scrambling to roll back changes and resolve errors.”
The release goes on, “The XebiaLabs DevOps Prediction Engine highlights potential bottlenecks before release processes start, so Release Managers, Developers, and DevOps Engineers can take preventative action, adjust timelines, and keep the business in the loop. Powerful predictive risk analysis enables DevOps teams to answer questions such as: What are the chances this release will fail, and what can we do about it? Is this release likely to be delayed, and by how long? How likely is a team member to skip specific release tasks, and why? What caused releases like this one to fail or be delayed in the past?”
It adds, “XebiaLabs already provides customizable risk scoring that identifies warning signs during a release process to indicate when it is not on track. Now, the company has added a new Risk Forecast Function to the XebiaLabs DevOps Platform. Powered by a machine learning-based DevOps Prediction Engine, it offers the following capabilities: (1) Risk alerts that warn the team when a release is likely to be delayed or to fail, before the release pipeline starts running, so they can take preventative action. (2) A comprehensive Risk Forecast view that summarizes predicted delays and failures for every task in the release process, so teams can drill down into the specific parts of the process that are likely to cause issues.”
Read more at Business Wire.
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