Topological Analysis for Identifying Anomalies in Serverless Platforms

TL;DR

This paper introduces a topological model using Hodge decomposition to analyze and identify structural anomalies in serverless platforms, revealing persistent harmonic flows as inherent system properties rather than errors.

Contribution

The paper presents a novel topological framework for serverless systems, including an iterative analysis method and remediation strategies like dumping effects to improve system efficiency.

Findings

Harmonic flows are natural structural features, not errors.

The topological model uncovers latent architectural structures.

Dumping effects can mitigate harmonic inefficiencies.

Abstract

The information flows in serverless platforms are complex and non-conservative. This is a direct result of how independently deployed functions interact under the platform coarse-grained control mechanisms. To manage this complexity, we introduce a topological model for serverless services. Using Hodge decomposition, we can separate observed operational flows into two distinct categories. They include components that can be corrected locally and harmonic modes that persist at any scale. Our analysis reveals that these harmonic flows emerge naturally from different types of inter-function interactions. They should be understood as structural properties of serverless systems, not as configuration errors. Building on this insight, we present an iterative method for analyzing inter-function flows. This method helps deriving practical remediation strategies. One such strategy is the introduction of "dumping effects" to contain harmonic inefficiencies, offering an alternative to completely restructuring the service's topological model. Our experimental results confirm that this approach can uncover latent architectural structures.