How do you implement cloud-native application load balancing across services?

Cloud-native application load balancing refers to the dynamic distribution of traffic between services to ensure high availability and scalability, avoiding single points of failure. Its importance lies in improving application performance and resource efficiency. Application scenarios include microservice architectures and containerized deployments, such as e-commerce platforms handling high concurrent requests.

Core components include service discovery mechanisms (such as Kubernetes' Service API) and traffic management tools (such as Ingress controllers). Features include dynamic routing, health checks, and automatic scaling, with principles based on DNS or IP load balancing. In practical applications, for example, Kubernetes service objects automatically distribute traffic, and the impacts include simplifying operation and maintenance, enhancing elasticity, and increasing system throughput.

Implementation steps: Deploy microservice instances (via Kubernetes Deployment); create Service objects, define selectors to associate Pods to provide internal load balancing; configure Ingress controllers (such as Nginx or Istio) to manage external traffic routing. A typical scenario is an API gateway distributing HTTP requests. Business value includes reducing latency, increasing availability, and optimizing cost efficiency.