How do you optimize cloud-native applications for cost efficiency?

Cloud-native applications are designed specifically for cloud environments, based on architectures such as containers and microservices, enabling elastic scaling and improved efficiency. Cost optimization is crucial as it can significantly reduce cloud resource expenditures, making it suitable for businesses with highly fluctuating workloads (e.g., e-commerce promotions). Its value lies in enhancing return on investment and supporting sustainable growth.

Core optimizations include three aspects: first, resource management (such as Kubernetes HPA auto-scaling, resource request/limit configurations) to avoid over-provisioning; second, efficiency improvement (using Spot instances, open-source tool Prometheus for monitoring); third, architectural optimization (serverless, image slimming). Practical applications involve automatically shutting down idle resources and optimizing storage types to reduce redundant costs.

Implementation steps are divided into four phases: first, identify resource waste points through monitoring tools (e.g., Grafana); second, adjust container resource quotas and replica counts; third, adopt a mixed instance strategy (reserved instances + Spot); finally, conduct continuous testing and iteration. Business benefits include reducing cloud bills by over 30% while maintaining performance and reliability.