AI-Driven Cloud Resource and Energy Consumption Dataset

This dataset was developed as part of a capstone project titled "AI-Driven Optimization in Hybrid Cloud Environments". It contains time-series logs of resource consumption and energy usage from simulated and real-world hybrid cloud clusters.

The dataset is designed to support the development and evaluation of machine learning models for:

Resource allocation

Energy efficiency optimization

Workload forecasting

Sustainable cloud computing

Data is organized into training, validation, and testing sets, covering CPU usage, memory consumption, network traffic, request rates, latency, energy draw, and financial costs. The dataset reflects typical behavior across test, staging, and production environments and aims to enable energy savings of up to 30% and cost reductions of 25%.

This resource supports academic and industrial research in AI, cloud sustainability, FinOps, and dynamic infrastructure scaling.