在细粒度负载波动下协调严格SLO与低成本
Reconciling Strict SLOs with Low Cost under Fine-Grained Load Fluctuations
Dilina Dehigama, Shyam Jesalpura, Zeyu Xu, Marton Nemeth, Shengda Zhu, Marios Kogias, Boris Grot
AI 速读 基于摘要
Spandana通过将SLO保障与成本优化解耦，在应用VM与FaaS之间逐请求调度，以在细粒度负载波动下兼顾严格SLO、高利用率与低成本。
cs.DC
查看原文摘要
Cloud-based online services face significant sub-second load fluctuations while needing to meet strict Service Level Objectives (SLOs). Cluster operators often over-provision resources to protect SLOs, sacrificing utilization and cost efficiency. Existing reactive and proactive autoscalers, serverless (FaaS) deployments, and VM/FaaS hybrid systems fail to reconcile strict SLO compliance with low cost and high utilization under fine-grained load fluctuation. We introduce Spandana, an architecture that addresses this trade off by decoupling SLO enforcement from cost optimization. A lightweight controller colocated with each application VM enforces SLOs by steering each arriving request between the VM and FaaS. Requests that can meet the SLO stay on the VM; the remaining requests are forwarded to a stock FaaS layer such as AWS Lambda. For cost optimization, Spandana's resource allocator determines the most-efficient VM provisioning by accounting for VM cost, FaaS cost, and traffic volatility, allowing the VM pool to run at high utilization. Our evaluation shows that Spandana maintains strict SLO adherence, achieves 76-86% CPU utilization, and reduces cost by 5-44% over three SOTA baselines.