
IBM unveiled IBM Watson AIOps, a new offering that uses AI to automate how enterprises self-detect, diagnose and respond to IT anomalies in real time.
Watson AIOps enables organizations to introduce automation at the infrastructure level and is designed to help CIOs better predict and shape future outcomes, focus resources on higher-value work and build more responsive and intelligent networks that can stay up and running longer.
The new solution is built on the latest release of Red Hat OpenShift to run across hybrid cloud environments and works in concert with technologies at the center of today's distributed work environment, such as Slack and Box. It also works with providers of traditional IT monitoring solutions, such as Mattermost and ServiceNow.
As part of the rollout, IBM is also announcing the Accelerator for Application Modernization with AI, within the IBM's Cloud Modernization service. This new capability is designed to help clients reduce the overall effort and costs associated with application modernization. It provides a series of tools designed to optimize the end to end modernization journey, accelerating the analysis and recommendations for various architectural and microservices options. The accelerator leverages continuous learning and interpretable AI models to adapt to the client's preferred software engineering practices and stays up-to-date with the evolution of technology and platforms.
Many of the technologies underlying Watson AIOps and the Accelerator for Application Modernization were developed in IBM Research.
"What we've learned from companies all over the world is that there are three major factors that will determine the success of AI in business – language, automation and trust," said Rob Thomas, SVP, Cloud and Data Platform, IBM. "The COVID-19 crisis and increased demand for remote work capabilities are driving the need for AI automation at an unprecedented rate and pace. With automation, we are empowering next generation CIOs and their teams to prioritize the crucial work of today's digital enterprises—managing and mining data to apply predictive insights that help lead to more impactful business results and lower cost."
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