Ticket support in cloud services involves technical engineers using expert tools to resolve customer queries—% a process closely resembling information integration. To enhance both operational efficiency and resolution accuracy, we propose DualLane, a novel parallel dual-path planning architecture designed for AI agents. This framework adaptively manages the highly skewed frequency distribution characteristic of real-world user queries. For low-frequency long-tail scenarios, the slow path employs a two-stage planning mechanism that decouples task decomposition from parameter generation, effectively optimizing dependency propagation and reducing context complexity. In contrast, for high-frequency routine scenarios, the fast path bypasses expensive LLM-based full-plan generation by utilizing pre-validated execution templates, thereby improving response accuracy and reducing latency. After more than one year of extensive deployment in Alibaba Cloud's ECS production environment, DualLane has demonstrated remarkable robustness and stability. Offline benchmarks indicate a high accuracy rate of 96.5%, accompanied by superior latency performance. Crucially, online metrics reveal a median plan-execution latency of merely 4.2 seconds, with an agent-induced error rate maintained at a low 7.1%. These results underscore the practical viability and effectiveness of adaptive dual-path planning in large-scale, interactive AIOps systems.
Haoyu Wang, Wenxuan Ma, Bing Hu et al.· Proceedings of the 32nd ACM...· 0 citations
The transition to Data Processing Unit (DPU)-centric architectures has become the de-facto standard in modern cloud networks, enabling infrastructure offload and improved host resource utilization. However, the fixed hardware limits of DPUs increasingly fail to keep pace with the rapid growth of host compute density and network-intensive workloads. As a result, when DPU resources are saturated, host compute capacity often remains underutilized due to insufficient network provisioning. This paper presents Spillway, a unified vSwitching fabric that decouples virtual switching capacity from static DPU hardware limits. Spillway introduces a DPU-host hybrid data plane that repurposes idle host CPU resources to process spillover traffic when the DPU becomes the bottleneck. Unlike traditional software switching, Spillway activates host-based forwarding selectively through a unified resource scheduler, incurring no overhead under normal operating conditions. To ensure production viability, Spillway enforces strict performance isolation across heterogeneous data planes. Experimental results from a large-scale deployment show that, under bursty traffic workloads, Spillway improves single-node connection processing capacity by up to 90% with negligible interference to co-located applications.
Xiaochong Jiang, Dian Fan, Yilong Lv et al.· Proceedings of the ACM SIGCO...· 0 citations