AutoDECK: Automated Declarative Performance Evaluation and Tuning Framework on Kubernetes-Reference-Cited by-同舟云学术

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AutoDECK: Automated Declarative Performance Evaluation and Tuning Framework on Kubernetes

Published:2022-07 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 15th International Conference on Cloud Computing (CLOUD)
language:
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Author:

Choochotkaew Sunyanan¹,Chiba Tatsuhiro¹,Trent Scott¹,Yoshimura Takeshi¹,Amaral Marcelo¹

Affiliation:

1. IBM Research,Tokyo,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9860274/9860367/09860408.pdf?arnumber=9860408

Reference19 articles.

1. Grafana: The open observability platform,2021

2. Sysbench;kopytov,2021

3. IPERF: A framework for automatic construction of performance prediction models;hsu;PFDC,1998

4. Exploring CoreMark - a benchmark maximizing simplicity and efficacy;gal-on;The Embedded Microprocessor Benchmark Consortium,2012

5. CODAIT: Center for Open Source Data and AI Technologies,2021

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1. Cloud-Native Computing: A Survey From the Perspective of Services;Proceedings of the IEEE;2024-01

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