A Hodge-Based Framework for Service Operational Analysis in Serverless Platforms

2026-03-09

AI Summary

This study addresses the inefficiency in serverless platforms caused by complex, non-conservative information flows among functions. It introduces Hodge decomposition—a novel application in this domain—to construct a service topology model that decomposes observed operational flows into locally correctable components and globally persistent harmonic modes. The work demonstrates that harmonic flows are intrinsic structural characteristics of the system rather than artifacts of misconfiguration, and leverages this insight to propose new optimization mechanisms such as the “dumping effect.” By constructing service flow spectra and performing harmonic analysis, the approach effectively identifies architectural-level performance bottlenecks, thereby validating its efficacy in uncovering structural inefficiencies and guiding targeted performance optimizations.

Technology Category

• Machine Learning: Hardware-aware ML
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In this paper we propose a method for analyzing services deployed in serverless platforms. These services typically consists of orchestrated functions that can exhibit complex and non-conservative information flows due to the interaction of independently deployed functions under coarse-grained control mechanisms. We introduce a topological model of serverless services and make use of the Hodge decomposition to partition observed operational flows into locally correctable components and globally persistent harmonic modes. Our analysis shows that harmonic flows naturally arise from different kind of interactions among functions and should be interpreted as structural properties of serverless systems rather than configuration errors. We present a systematic methodology for analyzing inter-function flows and deriving actionable remediation strategies, including dumping effects to contain the effects of harmonic inefficiencies as an alternative to completely restructure the topological model of the service. Experimental results confirm that the proposed approach can uncover latent architectural structures leading to inefficiencies.

Problem

• serverless platforms
• service operational analysis
• information flows
• harmonic inefficiencies
• function interactions

Innovation

• Hodge decomposition
• serverless platforms
• topological modeling
• harmonic flows
• operational analysis