arXiv subjects

Ehsan Ataie

Publications and source records attributed to Ehsan Ataie.

3 recordsLinked to original sources

arXiv2026

Optimizing OpenFaaS on Kubernetes: Comparative Analysis of Language Runtimes and Cluster Distributions

Serverless computing, particularly Function-as-a-Service (FaaS), has revolutionized cloud computing by abstracting infrastructure management and enabling dynamic resource allocation. This paper examines the performance and compatibility of OpenFaaS, an open-source serverless platform, when deployed on various Kubernetes distributions, including Kubeadm, K3s, MicroK8s, and K0s. Moreover, leveraging the CloudLab infrastructure, this study examines the impact of Python, Go, and Node$.$js programming languages on the performance of Kubernetes-enabled OpenFaaS, specifically when these languages are used to develop functions deployed on the platform. The performance is evaluated and analyzed under various levels of concurrent invocations using several usage-level metrics, such as throughput and CPU usage, as well as responsiveness metrics, such as delay. According to our findings, Go consistently outperforms Python and Node$.$js in terms of throughput and CPU usage, making it the ideal runtime for serverless applications. Among the Kubernetes distributions, K3s and Kubeadm exhibit superior performance, with Kubeadm maintaining low latency and efficient CPU usage, and K3s demonstrating high throughput. This study provides valuable insights into optimizing the Kubernetes-enabled OpenFaaS platform, highlighting the strengths and trade-offs of different Kubernetes distributions and language runtimes.

cs.DC↗

arXiv2024

Kubernetes in Action: Exploring the Performance of Kubernetes Distributions in the Cloud

Kubernetes has emerged as a leading open-source platform for container orchestration, allowing organizations to efficiently manage and deploy containerized applications at scale. This paper investigates the performance of four Kubernetes distributions, namely Kubeadm, K3s, MicroK8s, and K0s when running OpenFaaS as a containerized service on a cluster of computing nodes on CloudLab. For this purpose, experiments are conducted to examine the performance of two virtualization modes, namely HVM and PV, supported by Xen as the underlying hypervisor. Moreover, two container runtimes that are integrated with Kubernetes, namely Docker, and Containerd, are examined to assess their performance on both disk-intensive and CPU-intensive workloads. After determining the appropriate underlying Xen mode and container runtime, the Kubernetes distributions are set up and their performance is measured using various metrics, such as request rate, CPU utilization, and scaling behavior.

cs.DC↗

arXiv2024

Experimental Assessment of Containers Running on Top of Virtual Machines

Over the past two decades, the cloud computing paradigm has gradually attracted more popularity due to its efficient resource usage and simple service access model. Virtualization technology is the fundamental element of cloud computing that brings several benefits to cloud users and providers, such as workload isolation, energy efficiency, server consolidation, and cost reduction. This paper examines the combination of operating system-level virtualization (containers) and hardware-level virtualization (virtual machines). To this end, the performance of containers running on top of virtual machines is experimentally compared with standalone virtual machines and containers based on different hardware resources, including the processor, main memory, disk, and network in a real testbed by running the most commonly used benchmarks. Paravirtualization and full virtualization as well as type 1 and type 2 hypervisors are covered in this study. In addition, three prevalent containerization platforms are examined.

cs.DC↗