3 citations · 5 across the 4 of their papers we have counts for
6 papers
Sage: Using Unsupervised Learning for Scalable Performance Debugging in Microservices
Yu Gan, Mingyu Liang, Sundar Dev +2
Cloud applications are increasingly shifting from large monolithic services to complex graphs of loosely-coupled microservices. Despite the advantages of modularity and elasticity…
uqSim: Scalable and Validated Simulation of Cloud Microservices
Yanqi Zhang, Yu Gan, Christina Delimitrou
Current cloud services are moving away from monolithic designs and towards graphs of many loosely-coupled, single-concerned microservices. Microservices have several advantages, in…
An Open-Source Benchmark Suite for Cloud and IoT Microservices
Yu Gan, Yanqi Zhang, Dailun Cheng +21
Cloud services have recently started undergoing a major shift from monolithic applications, to graphs of hundreds of loosely-coupled microservices. Microservices fundamentally chan…
Leveraging Deep Learning to Improve the Performance Predictability of Cloud Microservices
Yu Gan, Yanqi Zhang, Kelvin Hu +4
Performance unpredictability is a major roadblock towards cloud adoption, and has performance, cost, and revenue ramifications. Predictable performance is even more critical as clo…
The Architectural Implications of Microservices in the Cloud
Yu Gan, Christina Delimitrou
Cloud services have recently undergone a shift from monolithic applications to microservices, with hundreds or thousands of loosely-coupled microservices comprising the end-to-end…
Seer: Leveraging Big Data to Navigate the Increasing Complexity of Cloud Debugging
Yu Gan, Meghna Pancholi, Dailun Cheng +3
Performance unpredictability in cloud services leads to poor user experience, degraded availability, and has revenue ramifications. Detecting performance degradation a posteriori h…