Containers are lightweight OS-level virtualization. In recent years, container-based virtualization for applications has gained immense popularity thanks to the success of technologies like Docker. Container management is one of the key challenges of adopting this technology. As a result, management middleware like Kubernetes, Mesos, etc., are witnessing widespread adoption in the industry today. While Containers as technology have reached an acceptable level of maturity, we see today that most of the challenges hindering the full-scale adoption of this technology lie in the limitation of the existing middleware managing containerized workloads. Problems around scalability, security, high availability, disaster recovery, and compliance are still active research areas that require innovative solutions. 

The aim of this workshop is to shed light on the main challenges and solutions of running containerized workloads in clustered environments.

The ninth workshop on container technologies and container clouds solicits contributions in this area from researchers and practitioners in both academia and industry. The workshop welcomes submissions describing unpublished research, position papers as well as deployment experiences on various topics related to containers as outlined below:

Topics of interest include but are not limited to: 

• Analyzing Scalability and performance of container management middleware (K8s, Docker, OpenShift,...)

• MLOps and using containers for processing ML workloads

• Use cases for containers in Machine Learning workloads 

• Security, isolation, and performance of containers in shared environments

• Network architectures for multi-host container deployments

• Orchestration models for cloud-scale deployments

• High availability systems for containerized workloads

• Leveraging hardware support for containers and containerized workloads

• Migrating and optimizing traditional workloads for containers

• Operational issues surrounding the management of large clusters of containers

• Container use cases and challenges for HPC, Big Data, and IoT applications

• Leveraging cognitive techniques for container management

• Performance enhancement of containers

• Use cases of using containers such as serverless computing and PaaS

• Comparative studies between different middleware for managing containers

• Comparative studies between containers, uni-kernels, and any other virtualization technologies 

• Other topics relevant to containers management 

Submissions:

Accepted papers should be no longer than 6 pages in the standard ACM format. Note that at least one author on each accepted workshop paper must hold a full pre-conference registration. As in previous years, the Middleware conference will provide companion proceedings including all workshop papers, which will be available in the ACM Digital Library. This is subject to the availability of a camera-ready version by October 27, 2023. Please upload your papers in PDF form to hotCRP. 

Submissions will be judged on novelty, relevance, clarity of presentation, and correctness.  Authors of accepted submissions are required to present their work. Accepted papers and abstracts will be made available on the conference website at least one week before the workshop so that the participants can come prepared having read the papers. Accepted submissions will be published via ACM Digital Library

• For the authors of accepted papers, you will be contacted by the main conference with a specific URL for your camera-ready submission.

Important dates (tentative):

• Paper submissions:  September 15, September 25, 2023 

• Notification of acceptance: October 10, 2023 , October 15, 2023

• Camera-ready version: October 27, 2023

• Workshop date: December 11, 2023

Program (each talk is scheduled for 25 minutes):  Monday, December 11, 13:30 - 15:00  
- Container Sizing for Microservices with Dynamic Workloads by Online Optimization 

- Understanding Container Isolation: An Investigation of Performance Implications of Container Runtimes 

- Towards Optimal Preemptive GPU Time-Sharing for Edge Model Serving 

Organization:

Workshop Chairs:

Ali Kanso – Microsoft

Abdelouahed Gherbi, Ecole de Technologie Superieure, Montreal, Canada

Steering Committee:

Seetharami R. Seelam – IBM T. J. Watson Research Center

Ricardo Aravena – Rakuten

Chen Wang - IBM T. J. Watson Research Center

Publicity Chair:

Ke Wang - Google

Program Committee Chair:

Chen Wang - IBM T. J. Watson Research Center

Program Committee (To Be Confirmed):

Eddy Truyen, KU Leuven, Belgium

Yosr Jarraya, Ericsson, Canada

Marco Cello, Pregmune, United States of America

Abdelouahed Gherbi, Ecole de Technologie Superieure, Montreal, Canada

Aleksander Slominsky, IBM Research, United States of America

Laaziz Lahloo, Ecole de Technologie Superieure, Montreal, Canada

Mike Spritzer, IBM Research, United States of America

Ali Kanso, Microsoft,  United States of America

Rolando Martins, Ecole de Technologie Superieure, Montreal, Canada

Chen Wang, IBM Research, United States of America

Guillaume Rosinosky, UCLouvain,  Belgium

Christoph Doblander, Microsoft, United States of America

Yogesh Barve,  Vanderbilt University, United States of America