Machine learning-based orchestration of containers: A taxonomy and future directions

Z Zhong, M Xu, MA Rodriguez, C Xu… - ACM Computing Surveys …, 2022 - dl.acm.org
Containerization is a lightweight application virtualization technology, providing high
environmental consistency, operating system distribution portability, and resource isolation …

Auto-scaling techniques in container-based cloud and edge/fog computing: Taxonomy and survey

J Dogani, R Namvar, F Khunjush - Computer Communications, 2023 - Elsevier
The long-held dream of computing as a service was realized with the emergence of cloud
computing. Recently, fog and edge computing have been introduced as extensions of cloud …

{FIRM}: An intelligent fine-grained resource management framework for {SLO-Oriented} microservices

H Qiu, SS Banerjee, S Jha, ZT Kalbarczyk… - 14th USENIX symposium …, 2020 - usenix.org
User-facing latency-sensitive web services include numerous distributed,
intercommunicating microservices that promise to simplify software development and …

Machine learning-based scaling management for kubernetes edge clusters

L Toka, G Dobreff, B Fodor… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Kubernetes, the container orchestrator for cloud-deployed applications, offers automatic
scaling for the application provider in order to meet the ever-changing intensity of …

Microrank: End-to-end latency issue localization with extended spectrum analysis in microservice environments

G Yu, P Chen, H Chen, Z Guan, Z Huang… - Proceedings of the Web …, 2021 - dl.acm.org
With the advantages of flexible scalability and fast delivery, microservice has become a
popular software architecture in the modern IT industry. However, the explosion in the …

Intelligent autoscaling of microservices in the cloud for real-time applications

AA Khaleq, I Ra - IEEE Access, 2021 - ieeexplore.ieee.org
Cloud applications are becoming more containerized in nature. Developing a cloud
application based on a microservice architecture imposes different challenges including …

The power of prediction: microservice auto scaling via workload learning

S Luo, H Xu, K Ye, G Xu, L Zhang, G Yang… - Proceedings of the 13th …, 2022 - dl.acm.org
When deploying microservices in production clusters, it is critical to automatically scale
containers to improve cluster utilization and ensure service level agreements (SLA) …

CoScal: Multifaceted scaling of microservices with reinforcement learning

M Xu, C Song, S Ilager, SS Gill, J Zhao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The emerging trend towards moving from monolithic applications to microservices has
raised new performance challenges in cloud computing environments. Compared with …

GRAF: A graph neural network based proactive resource allocation framework for SLO-oriented microservices

J Park, B Choi, C Lee, D Han - … of the 17th International Conference on …, 2021 - dl.acm.org
Microservice is an architectural style that has been widely adopted in various latency-
sensitive applications. Similar to the monolith, autoscaling has attracted the attention of …

Deepscaling: microservices autoscaling for stable cpu utilization in large scale cloud systems

Z Wang, S Zhu, J Li, W Jiang… - Proceedings of the 13th …, 2022 - dl.acm.org
Cloud service providers conservatively provision excessive resources to ensure service
level objectives (SLOs) are met. They often set lower CPU utilization targets to ensure …