Service Function Chaining (SFC) establishes service paths where intermediate nodes execute network functions in a specified order. Integrating Cloud-Native (CN) technologies enhances SFC's agility, flexibility, scalability, and fault tolerance by leveraging Cloud-native/Containerized Network Functions (CNFs) and their orchestration. Network Service Mesh (NSM) extends Kubernetes' networking capabilities and enables effective NSM-based CN-SFC implementations. Several studies have shown NSM based CN-SFC(NSM-SFC) improves deployment time, end-to-end latency, and failure recovery. However, automatic SFC scaling for dynamic load fluctuations remains underexplored. In this paper, we propose Horizontal SFC Autoscaler (HSA) for NSM-SFC, which dynamically adjusts the number of exclusive service paths based on service demand. HSA integrates Kubernetes' autoscaling function, Horizontal Pod Autoscaler (HPA), with NSM's Topologically-aware Scale from Zero (TSZ) mechanism to achieve path-level autoscaling. Unlike the conventional TSZ, which ties CNFs to specific deployment nodes, HSA ensures exclusive service paths by as sociating CNFs with their respective NSM clients, uniquely identified to maintain path exclusivity. Experiments demonstrate that HSA efficiently scales resources to meet demand and improves fault isolation by creating disjoint service paths. We also reveal that the current TSZ mechanism requires improvement to reduce recovery time.

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Takanori Hara, Masahiro Sasabe, Horizontal Autoscaler for Network Service Mesh Based Cloud-Native Service Function Chaining, IEICE Transactions on Communications, E109-B(11), pp.1-11, November 2026.