Abstract: Verification of placement of equipment that has been installed in a rack of a data center is performed by obtaining data indicating a placement location of equipment to be installed in a rack of the data center, and verifying that the equipment has been installed in the installed rack unit position that corresponds to the placement location, based upon an equipment height measurement. Related methods, devices, and computer program products are provided.

Abstract: A method includes performing operations as follows on a processor: receiving a geographic reference signal, generating location information responsive to the geographic reference signal, defining a portion of a floor surface area of a data center based on the location information, specifying a usage status of the portion of the floor surface area of the data center, and updating a floor plan of the data center based on the usage status of the portion of the floor surface area.

Abstract: Collaborative space planning for a data center is provided. Methods include receiving, into a collaboration server that provides a collaborative environment for a plurality of data center personnel to participate in data center design operations, data corresponding to a data center modification operation from one of the plurality of data center personnel, sending the data corresponding to the data center modification operation to other ones of the plurality of data center personnel from the collaboration server, receiving, into the collaboration server, supplemental data corresponding to the data center modification from one of the other ones of plurality of data center personnel and sending the supplemental data to the plurality of data center personnel from the collaboration server responsive to receiving the supplemental data.

Abstract: A resource management node includes a processor and a memory coupled to the processor. The memory includes computer readable program code that when executed by the processor causes the processor to perform operations. The operations can include, for each of a plurality of guest virtual machines (VMs), determining operational resources of physical host machines available in a distributed computing system that are needed to provide the guest VM. A placement scenario for placing the guest VMs on the physical host machines and placing the physical host machines in cabinets of a distributed computing system is generated. An amount of infrastructure of the distributed computing system used by the placement scenario is determined. A determination is made whether the placement scenario satisfies a defined rule for how much infrastructure of the distributed computing system can be used.

Abstract: Collaborative space planning for a data center is provided. Methods include receiving, into a collaboration server that provides a collaborative environment for a plurality of data center personnel to participate in data center design operations, data corresponding to a data center modification operation from one of the plurality of data center personnel, sending the data corresponding to the data center modification operation to other ones of the plurality of data center personnel from the collaboration server, receiving, into the collaboration server, supplemental data corresponding to the data center modification from one of the other ones of plurality of data center personnel and sending the supplemental data to the plurality of data center personnel from the collaboration server responsive to receiving the supplemental data.

Abstract: A method includes performing operations as follows on a processor: receiving a geographic reference signal, generating location information responsive to the geographic reference signal, defining a portion of a floor surface area of a data center based on the location information, specifying a usage status of the portion of the floor surface area of the data center, and updating a floor plan of the data center based on the usage status of the portion of the floor surface area.

Abstract: Verification of placement of equipment that has been installed in a rack of a data center is performed by obtaining data indicating a placement location of equipment to be installed in a rack of the data center, and verifying that the equipment has been installed in the installed rack unit position that corresponds to the placement location, based upon an equipment height measurement. Related methods, devices, and computer program products are provided.

Abstract: A resource management node includes a processor and a memory coupled to the processor. The memory includes computer readable program code that when executed by the processor causes the processor to perform operations. The operations can include identifying an unproductive group of guest virtual machines (VMs) that satisfy a defined rule for being unproductive on an first group of physical host machines based on infrastructure of a distributed computing system used by the first group of the physical host machines to host the guest VMs. A relocation scenario is generated for relocating the unproductive group of the guest VMs from the first group of the physical host machines to a second group of the physical host machines. An effect of the relocation scenario on infrastructure usage of the distributed computing system is estimated.

Abstract: A resource management node includes a processor and a memory coupled to the processor. The memory includes computer readable program code that when executed by the processor causes the processor to perform operations. The operations can include, for each of a plurality of guest virtual machines (VMs), determining operational resources of physical host machines available in a distributed computing system that are needed to provide the guest VM. The operations can further include determining an amount of infrastructure of a distributed computing system used by a defined placement of physical host machines in racks of the distributed computing system.

Abstract: Some embodiments disclosed herein are directed to a resource management node having a processor and memory coupled to the processor. The memory includes computer readable program code that when executed by the processor causes the processor to perform operations. The operations include, for each of a plurality of guest virtual machines (VMs) of a VM cluster provided by computer operations of a physical machine among a plurality of physical machines within a distributed computing system, determining a productivity metric for the guest VM based on resources of the physical machine that are used by the guest VM. The operations further include for each of the guest VMs, determining, based on the productivity metric for the guest VM, an infrastructure value that indicates how much infrastructure of the distributed computing system is attributed to providing the guest VM.

Abstract: A resource management node includes a processor and a memory coupled to the processor. The memory includes computer readable program code that when executed by the processor causes the processor to perform operations. The operations can include, for each of a plurality of guest virtual machines (VMs), determining operational resources of physical host machines available in a distributed computing system that are needed to provide the guest VM. The operations can further include determining an amount of infrastructure of a distributed computing system used by a defined placement of physical host machines in racks of the distributed computing system.

Abstract: Some embodiments disclosed herein are directed to a resource management node having a processor and memory coupled to the processor. The memory includes computer readable program code that when executed by the processor causes the processor to perform operations. The operations include, for each of a plurality of guest virtual machines (VMs) of a VM cluster provided by computer operations of a physical machine among a plurality of physical machines within a distributed computing system, determining a productivity metric for the guest VM based on resources of the physical machine that are used by the guest VM. The operations further include for each of the guest VMs, determining, based on the productivity metric for the guest VM, an infrastructure value that indicates how much infrastructure of the distributed computing system is attributed to providing the guest VM.

Abstract: A resource management node includes a processor and a memory coupled to the processor. The memory includes computer readable program code that when executed by the processor causes the processor to perform operations. The operations can include, for each of a plurality of guest virtual machines (VMs), determining operational resources of physical host machines available in a distributed computing system that are needed to provide the guest VM. A placement scenario for placing the guest VMs on the physical host machines and placing the physical host machines in cabinets of a distributed computing system is generated. An amount of infrastructure of the distributed computing system used by the placement scenario is determined. A determination is made whether the placement scenario satisfies a defined rule for how much infrastructure of the distributed computing system can be used.

Abstract: A resource management node includes a processor and a memory coupled to the processor. The memory includes computer readable program code that when executed by the processor causes the processor to perform operations. The operations can include identifying an unproductive group of guest virtual machines (VMs) that satisfy a defined rule for being unproductive on an first group of physical host machines based on infrastructure of a distributed computing system used by the first group of the physical host machines to host the guest VMs. A relocation scenario is generated for relocating the unproductive group of the guest VMs from the first group of the physical host machines to a second group of the physical host machines. An effect of the relocation scenario on infrastructure usage of the distributed computing system is estimated.