Parallelizing packet processing in container overlay networks

Abstract

Container networking, which provides connectivity among containers on multiple hosts, is crucial to building and scaling container-based microservices. While overlay networks are widely adopted in production systems, they cause significant performance degradation in both throughput and latency compared to physical networks. This paper seeks to understand the bottlenecks of in-kernel networking when running container overlay networks. Through profiling and code analysis, we find that a prolonged data path, due to packet transformation in overlay networks, is the culprit of performance loss. Furthermore, existing scaling techniques in the Linux network stack are ineffective for parallelizing the prolonged data path of a single network flow.We propose Falcon, a fast and balanced container networking approach to scale the packet processing pipeline in overlay networks. Falcon pipelines software interrupts associated with different network devices of a single flow on multiple cores, thereby preventing execution serialization of excessive software interrupts from overloading a single core. Falcon further supports multiple network flows by effectively multiplexing and balancing software interrupts of different flows among available cores. We have developed a prototype of Falcon in Linux. Our evaluation with both micro-benchmarks and real-world applications demonstrates the effectiveness of Falcon, with significantly improved performance (by 300% for web serving) and reduced tail latency (by 53% for data caching).

Characterizing network performance of single-node large-scale container deployments

“…This performance trend is due to two reasons: first, many containers share a core with a high ratio, which naturally causes them to get a smaller slice of the CPU. Second, the number of interrupts and context switches on the CPU is high under the high ratio that incurs a high management overhead [2], [20]. Fig.…”

“…Normally, each microservice runs on a separate container [1], [2]. In addition, to make the microservices model more profitable, cloud providers often co-locate them on a single (virtual) host, thus achieving high server utilization.…”