How do you implement rate limiting in microservices architecture?

Rate limiting is a mechanism to control request rates, used to prevent overload in microservice systems. In microservice architectures, rate limiting is crucial as it ensures service stability and avoids cascading failures. Application scenarios include API gateways handling external requests and inter-service communication to cope with sudden traffic surges and DDoS attacks.

Key components of rate limiting include algorithms such as token bucket or leaky bucket, and configuration parameters like requests per second limits. Its features include dynamically adjustable thresholds and integration with monitoring tools. In practical applications, rate limiting is implemented through service meshes like Istio, improving system reliability and fair resource allocation.

Implementation steps: 1. Select a strategy such as the token bucket algorithm and configure a gateway like Nginx; 2. Integrate client libraries such as Resilience4j into microservices; 3. Monitor traffic using Prometheus to adjust thresholds. Business values include preventing service disruptions, ensuring SLA compliance, and optimizing user experience.