Methodology for Automating and Orchestrating Performance Evaluation of Kubernetes Container Network Interfaces
Vedran Dakić, Jasmin Redžepagić, Matej Bašić and Luka Žgrablić. Methodology for Automating and Orchestrating Performance Evaluation of Kubernetes Container Network Interfaces. Computers 13(11), 283, 2024.
Abstract
Maintaining a fast, low-latency network must be balanced in the demanding world of High-Performance Computing (HPC). Any compromise in network performance can severely affect distributed HPC applications, leading to bottlenecks that undermine the entire system’s efficiency. This paper highlights the critical need for precise and consistent evaluation of Kubernetes Container Network Interfaces (CNIs) to ensure that HPC workloads can operate at their full potential. Traditional manual methods for evaluating network bandwidth and latency are time-consuming and prone to errors, making them inadequate for the rigorous demands of HPC environments. To address this, we introduce a novel approach that leverages Ansible to automate and standardize the evaluation process across diverse CNIs, performance profiles, and configurations. By eliminating human error and ensuring replicability, this method significantly enhances the reliability of performance assessments. The Ansible playbooks we developed enable the efficient deployment, configuration, and execution of CNIs and evaluations, providing a robust framework for ensuring that Kubernetes-based infrastructures can meet the stringent performance requirements of HPC applications. This approach is vital for safeguarding the performance integrity of HPC workloads, ensuring that inadequate network configurations do not cripple them.
My contribution
The paper credits me with validation, formal analysis and investigation. I wrote the Ansible code behind it, including run_all_tests.sh, the script the paper names as the entry point of the evaluation suite, and I rendered the Grafana charts that Figures 1 and 2 are based on.
CC BY 4.0.