An international company managing a large fleet of on-premises servers needs a predictive maintenance solution to detect potential server failures using monitoring data (CPU/memory consumption). The incident data is unlabeled.
The suggested answer is C. Before investing in complex model training or manual data labeling, testing a simple heuristic in a production environment allows for quick validation and iterative improvement, ensuring the chosen approach is practical and effective.
You work on an operations team at an international company that manages a large fleet of on-premises servers located in few data centers around the world. Your team collects monitoring data from the servers, including CPU/memory consumption. When an incident occurs on a server, your team is responsible for fixing it. Incident data has not been properly labeled yet. Your management team wants you to build a predictive maintenance solution that uses monitoring data from the VMs to detect potential failures and then alerts the service desk team. What should you do first?
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