Migrating a National Cloud Platform for Urban Analytics: A Performance Assessment Framework The Australian Urban Research Infrastructure Network (AURIN  www.aurin.org.au) is a national platform (in Australia) for research into the urban and built environment that has been funded as part of the National Collaboration Research Infrastructure Strategy (NCRIS). The system provides secure, seamless access to over 5,000 (typically definitive) data sets from over 100 major organisations crossing government, industry and academia. The system has a rich and diverse user community with over 15,000 users and many actively using the systems on a regular basis with periodic spikes in usage, e.g. when largescale urban and built environment classes are run. AURIN has been running on dedicated hardware running VMware with redundancybackup systems running on the OpenStackbased National eResearch Collaboration Tools and Resources (NeCTAR  www.nectar.org.au) Research Cloud. In 2019, AURIN was awarded a further 18.9m for a further 5years as part of the NCRIS program. As such, there are decisions to be made on the future deployment of AURIN and whether to go fully onto a public Cloud such as NeCTAR or to continue to run on dedicated hardware. This paper explores the technical performance considerations that should underpin such a decision. We identify that even though NeCTAR performs better for most Cloud resources, it is less performant for disk operations which is essential for the majority of AURIN usecases.

A Performance Evaluation of Containers Running on Managed Kubernetes Services Containerbased virtualisation technologies are gaining more and more traction in recent years across Cloud platforms and this will likely continue in the coming years. As such, containers orchestration technologies are becoming indispensable. Kubernetes has become the de facto standard because of its robustness, maturity and rich features. To free users of the burden of having to configure and maintain complex Kubernetes infrastructures, but still make use of its functionalities, all major Cloud providers are now offering cloudnative managed Kubernetes alternatives. The goal of this paper is to investigate the performance of containers running in such hosted services. For this purpose, we conduct a series of experimental evaluations of containers to monitor the behaviour of system resources including CPU, memory, disk and network. A baseline consisting of a manually deployed Kubernetes cluster was built for comparison. In particular, we consider the Amazon Elastic Container Service for Kubernetes (EKS), Microsoft Azure Kubernetes Service (AKS) and Google Kubernetes Engine (GKE). The Australiawide NeCTAR Research Cloud was used for the baseline.