AI Ops and the Self-Optimization of Resources

VISH JAKKA | November 26, 2018

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AI Ops includes the ability to dynamically optimize infrastructure resources through a holistic approach. Cisco Workload Optimization Manager is an important component in our strategy of delivering enhanced customer benefits through AI Ops. Cisco is executing a strategy to consistently enhance the customer benefits we deliver through AI-driven Operations (AI Ops). This blog is the latest in a series that describes our strategy, our open architecture, and how we are implementing each of the benefits. In the first blog in this series we defined four categories of benefits from AI Ops: Improved user experience, Proactive support and maintenance, Self-optimization of resources, Predictive operational analytics, Multi-Dimensional AI Ops Strategy, Vendors use the terms AI, machine learning and AI Ops in a variety of ways. Their focus is primarily on hardware. Our strategy for delivering the customer benefits of AI Ops is a broader architectural vision. This vision includes infrastructure, workloads, and enhanced customer support in on-premises and cloud environments. Cisco’s strategy incorporates an open API framework and integrations with Cisco and partner platforms.

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