Quantifying Autoscaler Vulnerabilities: An Empirical Study of Resource Misallocation Induced by Cloud Infrastructure Faults
Gijun Park

TL;DR
This study empirically examines how various cloud infrastructure faults distort autoscaling metrics, leading to resource misallocations and increased costs, and offers insights for designing more fault-tolerant autoscaling policies.
Contribution
It provides a systematic empirical analysis of fault impacts on autoscaling, highlighting the differential effects of fault types and scaling strategies on resource provisioning accuracy.
Findings
Storage faults cause up to $258 monthly extra costs.
Routing anomalies lead to under-provisioning.
Horizontal autoscaling is more sensitive to transient faults.
Abstract
Resource autoscaling mechanisms in cloud environments depend on accurate performance metrics to make optimal provisioning decisions. When infrastructure faults including hardware malfunctions, network disruptions, and software anomalies corrupt these metrics, autoscalers may systematically over- or under-provision resources, resulting in elevated operational expenses or degraded service reliability. This paper conducts controlled simulation experiments to measure how four prevalent fault categories affect both vertical and horizontal autoscaling behaviors across multiple instance configurations and service level objective (SLO) thresholds. Experimental findings demonstrate that storage-related faults generate the largest cost overhead, adding up to $258 monthly under horizontal scaling policies, whereas routing anomalies consistently bias autoscalers toward insufficient resource…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSoftware System Performance and Reliability · Cloud Computing and Resource Management · Software-Defined Networks and 5G
