C.A.M.I.L.A.: A Low-Allocation Asynchronous Chaos & Adversarial Machine for Ingestion & Latency Assassination Framework for Microservices in .NET 10
Year: 2026
Type: preprint
Abstract: High-throughput microservice architectures frequently encounter catastrophic performance degradation under synthetic and real-world stress testing due to Garbage Collection (GC) pressure, runtime allocation overheads, and thread pool starvation. Traditional load-testing harnesses exacerbate this problem through the Observer Effect, introducing measurement latency and resource contention that mask critical runtime anomalies such as Heisenbugs. This paper introduces C.A.M.I.L.A. (Chaos & Adversarial Machine for Ingestion & Latency Assassination), an asynchronous, zero-allocation testing framework optimized for .NET 10. By leveraging high-performance runtime primitives including System.Threading.Channels, memory pooling via ArrayPool , value-task pipelines, and direct PostgreSQL binary import mechanisms, C.A.M.I.L.A. delivers high-density adversarial load generation while maintaining deterministic memory limits and strict $L_2$ unit-norm operational guarantees. Empirical validation on commodity hardware demonstrates sustained execution exceeding 104,280 RPS with negligible GC allocation overhead.
Author: Gamarra González, Oliver
Institution: Universidad Columbia del Paraguay
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7222966277
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