Towards Efficient Diagnosis of Performance Bottlenecks in Microservice-Based Applications (Work In Progress paper)-Reference-Cited by-同舟云学术

Towards Efficient Diagnosis of Performance Bottlenecks in Microservice-Based Applications (Work In Progress paper)

Published:2024-05-07 Issue: Volume:00 Page:40-46
ISSN:
Container-title:Companion of the 15th ACM/SPEC International Conference on Performance Engineering
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Author:

Belkhiri Adel¹^ORCID,Ben Attia Maroua²^ORCID,Gohring De Magalhaes Felipe¹^ORCID,Nicolescu Gabriela¹^ORCID

Affiliation:

1. École Polytechnique de Montréal, Montreal, Canada

2. Humanitas Solutions, Montreal, Canada

Funder

MITACS of Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3629527.3651432

Reference29 articles.

1. Marcelo Amaral, Tatsuhiro Chiba, Scott Trent, Takeshi Yoshimura, and Sunyanan Choochotkaew. 2022. MicroLens: A Performance Analysis Framework for Microservices Using Hidden Metrics With BPF. 2022 IEEE 15th International Conference on Cloud Computing (CLOUD) 00 (2022), 230--240.

2. Dan Ardelean, Amer Diwan, and Chandra Erdman. 2018. Performance Analysis of Cloud Applications. In 15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18), Vol. 00. USENIX Association, Renton, WA, 405--417.

3. An automated, cross-layer instrumentation framework for diagnosing performance problems in distributed applications

4. Transparent Trace Annotation for Performance Debugging in Microservice-oriented Systems (Work In Progress Paper)

5. Yang Cai, Biao Han, Jinshu Su, and Xiaoyan Wang. 2021. TraceModel: An Automatic Anomaly Detection and Root Cause Localization Framework for Microservice Systems. 2021 17th International Conference on Mobility, Sensing and Networking (MSN) 00 (2021), 512--519.