The largest cost for application delivery is labor, and the enterprise cloud reduces that labor through standardized automation tools. But workloads change quickly, and the process of keeping up with application configuration and deployment changes is complex and prone to errors. The result is often service interruptions, wasted cloud resources and performance bottlenecks — which lead directly to higher labor costs.
Enter Machine Learning (ML). ML-guided automation lets you manage an enterprise cloud data center with a smaller IT team and can detect and report unexpected infrastructure events using a variety of reports, dashboards and widgets.
Join Mel Beckman for this webinar which will cover: - The best ML algorithms for IT automation
- A brief overview of machine learning in the IT management context
- The best kinds of data to feed into ML time-series models
- How competing ML models run to optimize automation processes
- Real-world examples of ML-driven enterprise cloud automation
This webinar is provided by:
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