In the era of DevOps, IT leaders are under constant pressure to be more responsive to changing business needs. However, the cost of failed IT changes can be high. While you may know that some deployed changes will fail, what you often don’t know is which ones — until it’s too late. In fact, a recent Gartner study estimates that 80% of major incidents are change-related. Finally, new approaches are breaking through, based on a rigorous application of Machine Learning (ML) and predictive analytics.

How can you reduce change risk while retaining the agility of DevOps?

Learn how to apply AI / ML techniques to increase your systems’ stability while delivering the speed of innovation your customers expect.

In this webinar get insights on how to:

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