Sponsor
NSF CNS grant 1911012
Robust Performance Guarantee of Containerized Microservices in the Cloud
NSF CNS Core: Small project developing performance models and resource management solutions for large-scale containerized microservices.
Overview
Performance assurance for complex cloud services
Large-scale web services such as Netflix and Spotify are increasingly built with modular microservices that can be deployed, updated, and scaled independently. The complexity of interactions across many services, combined with contention for shared hardware resources in cloud datacenters, makes performance management difficult. This project develops performance models and resource-management techniques that help cloud platforms provide robust performance guarantees.
Participants
- Palden Lama, PI, Department of Computer Science, UTSA
- Peng Kang, PhD student, Department of Computer Science, UTSA
- Xue Li, PhD student, Department of Computer Science, UTSA
- Shahzaib Zaveri, undergraduate research assistant, UTSA
- Jordan Molone, undergraduate research assistant, UTSA
Products
Publications and outputs
SLO-aware Virtual Rebalancing for Edge Stream Processing
Peng Kang, Palden Lama and Samee U. Khan. PDF
Robust Resource Scaling of Containerized Microservices with Probabilistic Machine Learning
Peng Kang and Palden Lama. PDF
Robust performance modeling of containerized microservices with probabilistic machine learning
Peng Kang and Palden Lama. PDF