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Data Management and Storage

How do you handle database optimization in cloud-native environments?

Cloud-native environments combine containerization and Kubernetes to enable elastic deployment and automated management of applications. Database optimization is crucial in this environment to ensure high performance and high availability, especially in microservice architectures and high-concurrency scenarios such as e-commerce or IoT applications.

The core includes selecting cloud-native database services (e.g., AWS RDS or Cloud SQL), optimizing query performance, index design, and managing states with Kubernetes StatefulSets. Features like auto-scaling, load balancing, and monitoring integration (via Prometheus) enhance response efficiency and data reliability, supporting large-scale distributed systems.

Processing steps: 1. Evaluate and select DBaaS to optimize storage. 2. Optimize SQL and indexes to reduce latency. 3. Configure auto-scaling policies. 4. Implement backup and disaster recovery solutions. 5. Integrate monitoring tools to adjust performance. Value: Increase throughput by over 30%, save cloud resource costs, and strengthen business continuity.

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