How do you implement resource quotas and limits in cloud-native applications?

Implementing resource quotas and limits in a cloud-native environment involves managing the allocation caps of computing resources (such as CPU and memory) through tools like Kubernetes. This ensures cluster stability and multi-tenant fairness, preventing a single application from exhausting resources and causing system disruptions, and is applicable to production environments of microservice architectures and managed services.

Core mechanisms include ResourceQuota objects defining namespace-level quotas, Pod's Requests (minimum guaranteed resources), and Limits (maximum resource usage). Based on the resource isolation principle implemented by cgroups, parameters such as CPU cores and memory GiB/MiB are applied through YAML configuration files. Practical impacts include improved resource utilization, guaranteed service quality, and automatic handling of resource conflicts.

Implementation steps: 1. Create a ResourceQuota object, specifying namespace quotas such as total CPU; 2. Define Requests and Limits parameters for Pods to control resource boundaries. Business values include cost optimization and prevention of service disruptions; typical scenarios include elastic scaling deployments in microservice load balancing.