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|Developer(s)||openQRM Community / openQRM Enterprise|
 / 2 September 2013
|Written in||PHP, C, Shell script|
|Platform||Hypervisors (Xen, KVM, VMware ESXi) and other solutions (Linux-VServer, VirtualBox, OpenVZ)|
It provides a complete Automated Workflow Engine for all Bare-Metal and VM deployment, as well as for all IT subsystems, enableing professional management and monitoring of your data center & cloud capacities.
The openQRM platform manages a data center's infrastructure to build private, public and hybrid infrastructure as a service clouds. openQRM orchestrates storage, network, virtualization, monitoring, and security implementations technologies to deploy multi-tier services (e.g. compute clusters) as virtual machines on distributed infrastructures, combining both data center resources and remote cloud resources, according to allocation policies.
The openQRM platform emphasizes a separation of hardware (physical servers and virtual machines) from software (operating system server-images). Hardware is treated agnostically as a computing resource which should be replaceable without the need to reconfigure the software.
P2V (physical to virtual), V2P (virtual to physical), and V2V (virtual to virtual) migration are possible as well as transitioning from one virtualization technology to another with the same VM
openQRM is sponsored by openQRM Enterprise GmbH, a company located in Bonn, Germany. The openQRM Enterprise Edition is the commercially backed, extended product for professional users offering reliable support options and access to additional features. Users combine the services required. Simply integrate additional technologies and services through a large variety of plug-ins to exactly fit the use-case (OpenvSwitch, KVM, ESXi, OpenStack, AWS EC2, MS Azure, etc.). Over 50 plug-ins are available for openQRM Enterprise.
- Private/Hybrid Cloud Computing Platform
- Manages physical and virtualized server systems
- Integrates with all major open and commercial storage technologies
- Supports management of systems running Windows, Linux, OpenSolaris or *BSD
- Major hypervisors/containers supported: KVM, XEN, Citrix XenServer, VMWare ESX(i), lxc, OpenVZ and VirtualBox
- Support for Hybrid Cloud setups using additional Amazon AWS, Eucalyptus, Ubuntu UEC cloud resources
- Supports P2V, P2P, V2P, V2V Migrations and High-Availability
- Integrates with the best Open Source management tools - like puppet, nagios/Icinga or collectd
- Over 50 plugins for extended features and integration with your infrastructure
- Self-Service Portal for end-users - provision new servers and application stacks in minutes!
- Integrated billing system that maps CCU/h (Cloud Computing Units) to real currency
openQRM was initially released by the Qlusters company and went open-source in 2004. Qlusters ceased operations, while openQRM was left in the hands of the openQRM community. In November 2008, the openQRM community released version 4.0 which included a complete port of the platform from Java to PHP/C/Perl/Shell.
Release 5.3.8 on 30.01.2018
5.3.8 openQRM release for Community and for Enterprise.
Dependencies have been updated to ensure compatibility to the latest Linux distributions. There is also an enhanced check for PHP versions in place as well as full support for PHP 7. While openQRM fully supports PHP7, some integrated technologies have not yet completed up this step. In this case Magento, Mantis and I-do-it Integration may still require PHP 5.
The new openQRM 5.3.8 is tested on: Debian 8/9, Ubuntu 16.x + 17.x and Centos 7.
The 5.3.5 Community Release includes updated package dependencies.
The 5.3.2 Community Release includes enhanced package dependencies for latest Ubuntu, Debian, CentOS and removed rpmforge repository dependencies.
The 5.3.1 Community Release includes important security updates, bugfixes and enhancements, especially for the KVM and Cloud plug-ins.
- "openQRM Features and Functionality". OpenNebula documentation. Retrieved 13 October 2011.
- R. Moreno-Vozmediano, R. S. Montero, and I. M. Llorente. "Multi-Cloud Deployment of Computing Clusters for Loosely-Coupled MTC Applications", Transactions on Parallel and Distributed Systems. Special Issue on Many Task Computing (in press, doi:10.1109/TPDS.2010.186)
- R. S. Montero, R. Moreno-Vozmediano, and I. M. Llorente. "An Elasticity Model for High Throughput Computing Clusters", J. Parallel and Distributed Computing (in press, DOI: 10.1016/j.jpdc.2010.05.005)