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This paper introduces a topological model for analyzing information flows in serverless platforms, leveraging Hodge decomposition to separate flows into correctable components and persistent harmonic modes. The analysis reveals that harmonic flows are inherent structural properties arising from inter-function interactions, rather than configuration errors. Based on this, the authors propose an iterative method for analyzing inter-function flows and a remediation strategy involving "dumping effects" to contain harmonic inefficiencies.
Uncovers hidden architectural inefficiencies in serverless platforms by modeling function interactions as topological flows and identifying persistent "harmonic modes" that resist local fixes.
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.
