Abstract:
Serverless workflows have emerged in Function-as-a-Service (FaaS) platforms to represent the operational structure of traditional applications. With latency propagation effects becoming increasingly prominent, step-wise resource tuning is required to address Service-Level-Objectives (SLOs). Modern processors’ allowance for fine-grained Dynamic Voltage and Frequency Scaling (DVFS), coupled with serverless workflows’ intermittent nature, presents a unique opportunity to reduce power while meeting SLOs. We introduce Ωkypous, an SLO-driven DVFS framework for serverless workflows. Ωkypous employs a grey-box model that predicts functions’ execution latency and power under different Core and Uncore frequency combinations. Based on these predictions and the timing slacks between workflow functions, Ωkypous uses a closed-loop control mechanism to dynamically adjust Core and Uncore frequencies, reducing power consumption without compromising predefined end-to-end latency constraints. Our evaluation on real-world traces from Azure demonstrates an average power consumption reduction of 16% compared to state-of-the-art power management frameworks, while consistently maintaining low SLO violation rates (1.8%), even when operating under power caps.
DOI: 10.1109/TC.2026.3665984