Infrastructure Manager is now available through the EOSC Marketplace

The Infrastructure Manager service (IM), developed by the Grupo de Grid y Computación de Altas Prestaciones (GRyCAP) of the Universitat Politècnica de Valencia in Spain, is now available through the EOSC Marketplace.

IM can deploy complex and customized virtual infrastructures on multiple back-ends including EOSC cloud compute services such as EGI Compute Cloud as well as on-premises and public clouds. IM allows researchers to automate the deployment, configuration, software installation, monitoring and update of virtual infrastructures described in a document following the OASIS TOSCA specification.

The service makes user applications cloud agnostic and it features DevOps capabilities, based on Ansible, to enable the installation and configuration of all the required applications, providing the user with a fully functional virtual infrastructure.

Miguel Caballer, researcher at GRyCAP, says:

"IM was developed to help researchers to easily deploy and configure virtual infrastructures, enabling them to focus on their own applications and reducing the vendor lock-in of cloud back-ends."

IM was released by GRyCAP on 2014 and it has been enhanced in several European and national projects, such as INDIGO-DataCloud, adding new features, such as TOSCA support. IM is one of the core components of the INDIGO PaaS layer.

IM is currently used by different research communities as DODAS, ECAS/ENES, it is a core service in the EGI VMOps Dashboard and it has been adopted in several European projects, such as ATMOSPHERE and DEEP-Hybrid Datacloud. IM was also adopted by the industry as a core service for cloud orchestrators.

Sandro Fiore, Head of the Data Science and Learning Research Team (CMCC Advanced Scientific Computing Division), adds:

I have successfully exploited IM in several contexts! As an highlight, in the EU H2020 INDIGO-DataCloud project, thanks to IM, I easily and flexibly set up big data analytics clusters in the cloud to support distributed climate data analysis workflows.