Topological Analysis for Identifying Anomalies in Serverless Platforms
This work addresses the problem of managing complex, non-conservative information flows in serverless platforms for developers and operators, offering incremental improvements in analysis and remediation strategies.
The paper tackled the complexity of information flows in serverless platforms by introducing a topological model using Hodge decomposition to separate flows into correctable and harmonic components, revealing that harmonic flows are structural properties and presenting an iterative method with strategies like 'dumping effects' to manage inefficiencies without full restructuring.
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.