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Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis

, , , , , , , , , , , und . Companion of the 15th ACM/SPEC International Conference on Performance Engineering, Seite 72–76. New York, NY, USA, Association for Computing Machinery, (2024)

Zusammenfassung

As the market for cloud computing continues to grow, an increasing number of users are deploying applications as microservices. The shift introduces unique challenges in identifying and addressing performance issues, particularly within large and complex infrastructures. To address this challenge, we propose a methodology that unveils temporal performance deviations in microservices by clustering containers based on their performance characteristics at different time intervals. Showcasing our methodology on the Alibaba dataset, we found both stable and dynamic performance patterns, providing a valuable tool for enhancing overall performance and reliability in modern application landscapes.

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