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On the Analysis of Inter-Relationship between Auto-Scaling Policy and QoS of FaaS Workloads.

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Aquila: Efficient In-Kernel System Call Telemetry for Cloud-Native Environments.

Juyong Shin1, Jisu Kim1, Jaehyun Nam2

  • 1Department of AI-Based Convergence, Dankook University, 152, Jukjeon-ro, Suji-gu, Yongin-si 16890, Republic of Korea.

Sensors (Basel, Switzerland)
|November 13, 2025
PubMed
Summary

Aquila, a new system call telemetry framework, enhances cloud-native monitoring by reducing overhead and improving reliability. It provides richer context for analyzing complex workload behaviors, overcoming limitations of existing eBPF-based systems.

Keywords:
cloud-native securityeBPF monitoringsystem call telemetry

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Area of Science:

  • Computer Science
  • Cloud Computing
  • Systems Engineering

Background:

  • System call telemetry is crucial for understanding cloud-native runtime behavior.
  • Existing eBPF-based monitors face challenges with high overhead, unreliable delivery, and limited contextual information.
  • These limitations hinder scalability and complicate the analysis of complex workload activities.

Purpose of the Study:

  • To introduce Aquila, a novel lightweight telemetry framework designed for efficiency, reliability, and semantic fidelity in system call monitoring.
  • To address the scalability and reliability issues of current eBPF-based telemetry solutions.
  • To enhance the contextual information available for system call analysis in cloud-native environments.

Main Methods:

  • Aquila utilizes a dual-path kernel pipeline to separate metadata from attributes, optimizing event processing.
  • Implements priority-aware buffering and explicit drop detection for improved event retention and overload visibility.
  • Enriches kernel traces with Kubernetes metadata in user space for semantic mapping of system calls to cloud resources.

Main Results:

  • Aquila demonstrates improved scalability under representative workloads compared to existing approaches.
  • The framework significantly reduces event loss, enhancing telemetry stream reliability.
  • Aquila provides enhanced semantic completeness of system call telemetry, aiding in the analysis of complex behaviors.

Conclusions:

  • Aquila offers a more efficient, reliable, and semantically rich solution for system call telemetry in cloud-native infrastructures.
  • The framework effectively overcomes the limitations of existing eBPF-based monitoring tools.
  • Aquila facilitates better understanding and analysis of runtime behavior in complex cloud environments.