Cost Optimization Strategies for Private Clouds with Machine Learning-Based Workload Prediction

Learn essential cost optimization strategies for private cloud environments through this 21-minute conference talk that explores machine learning-based workload prediction techniques. Discover fundamental machine learning time series prediction models for workload forecasting and various cost optimization approaches based on predicted workloads. Explore proactive resource provisioning using AI, dynamic resource scaling and allocation, identification and release of underutilized resources, and optimization of storage and network costs. Gain insights into system stability and reliability considerations that arise when implementing these advanced optimization strategies. The presentation, delivered in Korean, includes detailed slides and practical implementation guidance for achieving maximum productivity with limited resources in private cloud infrastructures.