How do you implement multi-tier storage strategies in cloud-native applications?

Multi-tiered storage strategy refers to dividing storage tiers (such as hot, warm, cold) based on data access frequency in cloud-native environments to optimize cost and performance. Its importance lies in balancing economy and efficiency, with application scenarios including large-scale data analysis, AI training, and other systems requiring dynamic data management.

Core components include tier definitions (e.g., high-speed SSDs for hot data, object storage for cold tiers), and features include automated data migration based on lifecycle policies. The principle is implemented through integrating Container Storage Interface (CSI) drivers, with practical applications centered on Kubernetes persistent volumes, improving resource utilization and reducing overall storage costs by over 30%.

Implementation steps: Define tiering standards and create storage classes; integrate CSI plugins such as Rook to configure lifecycle policies; deploy applications and monitor for optimization. Typical scenarios include media streaming processing, with business values including significant cost reduction (e.g., archive tier reduced to $0.01/GB per month) and ensuring high availability.