Topological Analysis for Identifying Anomalies in Serverless Platforms
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.
Fields of Study & Subjects
Software System Performance and Reliability
Cloud Computing and Resource Management
Topological and Geometric Data Analysis
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 11 March 2026
- Language
- EN
- Document type
- Preprint