A Latency-Predictable Cloud-Native Network Architecture based on XDP

Cloud computing and microservices are increasingly supplanting traditional network deployment strategies within data centers due to their inherent flexibility in infrastructure management and rapid scalability. Nevertheless, current approaches often fall short in addressing quality of service (QoS) for virtual networks, especially under conditions of intense resource competition. This shortfall prevents the fulfillment of critical services’ requirements for low latency and predictability. To mitigate this challenge, we propose a cloud-native network service architecture designed to deliver consistently low latency and predictable packet arrival times. This architecture dynamically coordinates and reserves computational resources even during high contention periods, thereby maintaining container network QoS and ensuring the stable availability of microservice applications under extreme conditions. We validated the effectiveness of our proposed solution by deploying multiple container nodes across two directly connected servers and establishing a Kubernetes cluster. By launching a large volume of tasks within a constrained time frame, we assessed the container network’s load, latency, and jitter during peak usage periods. Our results indicate that, although our solution exhibits marginally reduced performance compared to the open-source Kubernetes network plugin under low-load conditions, it significantly outperforms the plugin under high-load scenarios. Specifically, when host CPU usage surpasses 90% and memory usage exceeds 80%, the open-source plugin experiences notable packet loss and long-tail latency distributions. In contrast, our solution demonstrates an 84% reduction in jitter compared to the open-source CNI.