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US9519517B2 - Data center control - Google Patents
Data center control Download PDF
US9519517B2 US12/371,355 US37135509A US9519517B2 US 9519517 B2 US9519517 B2 US 9519517B2 US 37135509 A US37135509 A US 37135509A US 9519517 B2 US9519517 B2 US 9519517B2
Active, expires 2029-04-07
US20100211669A1 (en
Mikkel Dalgas
Kristian Silberbauer
Daniel René Hagen Pedersen
Schneider Electric IT Corp
2009-02-13 Application filed by Schneider Electric IT Corp filed Critical Schneider Electric IT Corp
2009-02-13 Priority to US12/371,355 priority Critical patent/US9519517B2/en
2009-06-17 Assigned to AMERICAN POWER CONVERSION CORPORATION reassignment AMERICAN POWER CONVERSION CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: DALGAS, MIKKEL, SILBERBAUER, KRISTIAN
2009-10-07 Assigned to AMERICAN POWER CONVERSION CORPORATION reassignment AMERICAN POWER CONVERSION CORPORATION ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: PEDERSEN, DANIEL RENE HAGEN
2010-09-22 Priority claimed from US12/888,053 external-priority patent/US8560677B2/en
2015-06-30 Assigned to SCHNEIDER ELECTRIC IT CORPORATION reassignment SCHNEIDER ELECTRIC IT CORPORATION CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: AMERICAN POWER CONVERSION CORPORATION
2016-12-13 Publication of US9519517B2 publication Critical patent/US9519517B2/en
2029-04-07 Adjusted expiration legal-status Critical
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G06—COMPUTING; CALCULATING; COUNTING
G06F—ELECTRIC DIGITAL DATA PROCESSING
G06F9/00—Arrangements for program control, e.g. control units
G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
G06F9/46—Multiprogramming arrangements
G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
H—ELECTRICITY
H04—ELECTRIC COMMUNICATION TECHNIQUE
H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
H04L67/00—Network-specific arrangements or communication protocols supporting networked applications
H04L67/10—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network
H04L67/1002—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers, e.g. load balancing
H04L67/1004—Server selection in load balancing
H04L67/1008—Server selection in load balancing based on parameters of servers, e.g. available memory or workload
G06F11/00—Error detection; Error correction; Monitoring
G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
G06F11/16—Error detection or correction of the data by redundancy in hardware
G06F11/20—Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F11/202—Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements where processing functionality is redundant
G06F11/2023—Failover techniques
G06F11/203—Failover techniques using migration
G06F9/48—Program initiating; Program switching, e.g. by interrupt
G06F9/4806—Task transfer initiation or dispatching
G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
G06F9/485—Task life-cycle, e.g. stopping, restarting, resuming execution
G06F9/4856—Task life-cycle, e.g. stopping, restarting, resuming execution resumption being on a different machine, e.g. task migration, virtual machine migration
Systems and methods for data center control are provided that identify parameters of one or more data centers, where each data center includes a plurality of devices. The systems and methods receive a command to execute an application, and identify a selected data center from the one or more data centers as a location to run the application based at least in part on an evaluation of the parameters.
This application incorporates herein by reference, in its entirety, U.S. patent application Ser. No. 12/370,969 entitled "Power Supply and Data Center Control," filed on Feb. 13, 2009, and assigned to the assignee of the present application. The referenced application generally discloses systems and methods for controlling data centers.
1. Field of the Invention
At least one embodiment of the present invention relates generally to controlling facility activity, and more specifically, to managing data centers.
2. Background of the Invention
In response to increasing demands of industrial, developing, and information based economies, data centers and information technology networks continue to proliferate across the globe. This expansion has taken on various forms, including widely distributed computer networks that link together geographically disparate computing resources, as well as data centers, which provide power, cooling, and computing infrastructure to a variety of applications.
Typical data centers contain a number of racks of equipment that require power, cooling, and connections to external communications facilities. In modern data centers and network rooms, the increased density of computing equipment used in these facilities has put strains on their associated power systems. Because this computing equipment generates heat in operation, the cooling systems of these facilities are strained as well.
As the type, size, and complexity of data centers grow, so do the costs associated with their operation. These costs include energy cost associated with power usage, the cost for acquiring electronic devices and infrastructure, the cost of associated cooling or heat dissipation systems, and the salary of maintenance and administration staff.
At least some aspects and embodiments of the present invention are directed to systems and methods for data center control. One or more networks can link together a plurality of data centers. An associated controller can monitor the activity and parameters of data centers as well as their components and devices. The parameters can be evaluated to identify a data center or a device thereof that is suited to execute an application.
At least one aspect is directed to a computer implemented method for data center control. The computer implemented method identifies parameters of a plurality of data centers, where each data center includes a plurality of devices. The computer implemented method receives a command to execute an application, and identifies a selected data center from the plurality of data centers as a location to run the application based at least in part on an evaluation of the parameters.
In one embodiment, the computer implemented method can identify requirements of an application, and can identify the data center based at least in part on an evaluation of the requirements. The method can detect a failure of an application at a data center, and in response, may identify another data center as the location to run the application. The method can determine a first data center capacity based in part on an evaluation of first data center cooling or power characteristics, provide information indicative of the first data center capacity to a device associated with a second data center, and can receive a request to execute, on a device in the first data center, an application provided by the second data center or an associated device.
In various embodiments, at least two of the plurality of data centers can be connected by a network, and the method can monitor parameters of network infrastructure equipment that forms at least part of the network. The method can also add a physical server to a cluster of virtual servers of the data center, and can distribute at least a portion of the application to the cluster of virtual servers. The application can be provided to a virtual server of a data center, and the method can disable at least one of an uninterruptible power supply, a server, network equipment, or a cooling unit, each of which can be associated with at least one data center parameter. The method can receive a warning message from a first data center or subsystem thereof, and can transfer an application from a first data center to a second data center.
In various embodiments, the method identifies system requirements to execute an application, and time shifts execution of an application based on an evaluation of data center parameters and the system requirements. The method can identify a server in a data center as having capacity sufficient to execute an application, provide the application to the server, and instruct the server to execute the application. In one embodiment, the method generates a request to add hardware to the data center. The method can indicate that the data center has excess capacity, and the method can distribute all or part of the application to at least one data center.
At least one other aspect is directed to a data center activity control system. The system includes a data center controller associated with a network. The data center controller is configured to identify parameters of a plurality of data centers associated with the network, where each data center includes a plurality of devices. The data center controller is configured evaluate the parameters to identify a selected data center from the plurality of data centers as a location to run an application.
In various embodiments, the data center controller is configured to identify requirements of an application, and further configured to identify the data center as the location to run the application based at least in part on an evaluation of the requirements of the application. Requirements of the application may include application power consumption, application redundancy, application run time, or a time period in which an application is scheduled to run, and the application may be fault tolerant or redundant. In some embodiments, the data center controller is configured to receive a command to execute the application, and the data center controller can identify the data center as the location to run the application responsive to a failure to execute the application at a different data center. The data center controller can determine a first data center capacity based on an evaluation of first data center cooling or power characteristics. The data center controller can provide information indicating the first data center capacity to a device associated with a second data center, and the data center controller can receive a request to execute, on a device in a data center, an application provided by a device associated with another data center.
In various embodiments, the system includes a network having network infrastructure equipment associated with one or more data centers, and the data center controller can monitor parameters of the network infrastructure equipment. In some embodiments, the data center controller is configured to distribute at least a portion of an application to a cluster of virtual servers of a data center, and can provide an application to a cluster of virtual servers located in a data center. The data center controller can disable data center equipment such as an uninterruptable power supply, a server, network equipment, a computer, or a cooling unit.
In various embodiments, the data center controller is configured to receive a warning message from a first data center or subsystem thereof, and to transfer a first application from the first data center to a second data center. The data center controller can identify system requirements to execute an application, and can time shift execution of an application based at least in part on the system requirements. The data center controller can provide the application to a server in a data center, for execution by the server, and the data center controller can generate a request to add hardware to one or more of the data centers. The data center controller can indicate that a data center has excess capacity based on an evaluation of data center parameters, and the data center controller can distribute at least a portion of an application to at least one data center based at least in part on an evaluation, by the data center controller, of data center parameters.
At least one other aspect is directed to a computer readable medium having stored thereon sequences of instructions. The sequences of instructions include instructions, when executed by a processor, that cause the processor to identify parameters of a plurality of data centers, where each data center includes a plurality of devices. The instructions cause the processor to receive a command to execute an application, and to identify a selected data center from the plurality of data centers as a location to run the application based at least in part on an evaluation of the parameters.
In various embodiments, the instructions cause the processor to identify requirements of an application, and to identify a data center as a location to run an application based at least in part on an evaluation of the requirements. The instructions can cause the processor to detect a failure of an application at a data center. In one embodiment, the instructions can cause the processor to determine a first data center capacity based on first data center cooling or power characteristics, to provide information indicating first data center capacity to a second data center or associated device, and to receive a request to execute, on a device in the first data center, an application provided by a device associated with the second data center.
The instructions can cause the processor to monitor parameters of network infrastructure equipment that form at least part of a network, and can cause the processor to add a physical server to virtual servers of the data center, and distribute at least a portion of the application to one or more of the virtual servers. The instructions can cause the processor to provide the application to a virtual server located in the data center, and instructions can cause the processor to disable, responsive to an evaluation of data center parameters, one or more of an uninterruptable power supply, a server, network equipment, and a cooling unit.
In various embodiments, the instructions can cause the processor to receive a warning message from a first data center, and to transfer an application from the first data center to the second data center. The instructions can cause the processor to identify system requirements to execute the application, and to time shift execution of the application based on an evaluation of the system requirements. The instructions can cause the processor to identify equipment in the data center as having capacity sufficient to execute the application, to provide the application to the equipment, and to instruct the equipment to execute the application. The instructions can cause the processor to generate a request to add hardware to a data center, to indicate that a data center has excess capacity based on an evaluation of data center parameters, or to distribute at least a portion of the application to at least one data center based at least in part on an evaluation of data center parameters.
Other aspects, embodiments, and advantages of these exemplary aspects and embodiments will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, illustrating the principles of the invention by way of example only. It is to be understood that the foregoing information and the following detailed description include illustrative examples of various aspects and embodiments, and are intended to provide an overview or framework for understanding the nature and character of the claimed aspects and embodiments. The drawings, together with the remainder of the specification, serve to explain principles and operations of the described and claimed aspects and embodiments.
The accompanying drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component that is illustrated in various figures is represented by a like numeral. For purposes of clarity, not every component may be labeled in every drawing. The foregoing and other objects, features, and advantages of the systems and methods disclosed herein will be more fully understood from the following description of various embodiments, when read together with the accompanying drawings, in which:
FIG. 1 is a top view depicting an example of a data center in accordance with an embodiment;
FIG. 2 is a block diagram depicting an example of a data center control system in accordance with an embodiment;
FIG. 4 is a block diagram depicting an example of server configuration in one or more data centers in accordance with an embodiment;
FIG. 5 is a block diagram depicting an example of server configuration in a data center in accordance with an embodiment;
FIG. 6 is a flow chart illustrating an example method of data center control in accordance with an embodiment;
FIG. 7 is a functional block diagram of a computer system in accordance with an embodiment; and
FIG. 8 is a functional block diagram of a storage system in accordance with an embodiment.
The systems and methods described herein are not limited in their application to the details of construction and the arrangement of components set forth in the description or illustrated in the drawings. The invention is capable of other embodiments and of being practiced or of being carried out in various ways. Also, the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of "including" "comprising" "having" "containing" "involving" and variations thereof herein, is meant to encompass the items listed thereafter and equivalents thereof as well as additional items.
Various aspects and embodiments are directed to data center control. Characteristics of one or more data centers can be identified, monitored, and controlled by one or more data center controllers via a network. The data centers can be geographically disparate, and can have different characteristics and components. Data center controllers can evaluate characteristics of the data centers and applications that can be executed by data center components. These evaluations can include, for example, assessments of data center supply, (e.g., available data center processing capacity) or demand (e.g., parameters of applications that may be provided by data centers for execution). Based at least in part on these evaluations, a data center controller can direct an application to one or more data centers for execution.
Embodiments described herein may be used to design, manage and retrofit a data center, such as data center 100, which is illustrated in FIG. 1. Data center 100 may include various resources, equipment, or devices that support or ensure data center equipment functionality. Examples of data center 100 resources include power, cooling, physical space, weight support, remote equipment control capability, physical and logical security and physical and logical network connectivity. Power data center resources may include power distribution resources, such as transformers, power distribution units, outlets, and power available for distribution, such as utility power supplied to data center 100, power generated by an onsite generator and power supplied by power distribution units. Physical space resources in data center 100 may include data center floor space and rack U space. Cooling resources in data center 100 may include cooling distribution capacity and cooling generation capacity. Physical security resources in data center 100 may include security cameras and door locks. Logical network connectivity resources in data center 100 may include Virtual Local Area Networks, Domain Name Services, and Dynamic Host Configuration Protocol Services. Physical network connectivity resources may include network cabling and patch panels. Remote equipment control capability resources in data center 100 may include Keyboard Video Mouse services.
It should be appreciated that data center 100 is a representative data center and various embodiments described herein are not limited to data centers such as data center 100. Various other data centers and facilities may be used that, for example, do not include raised floors. Data center 100 or other data centers may be used with facilities that house more, less, or different equipment, or equipment other than computing equipment, including telecommunications facilities and other facilities. In one embodiment, data center 100 includes a computer supported by a subsystem. Data center 100 may, but need not be a dedicated space or room. Further, data center equipment layouts need not be neatly arranged as illustrated in FIG. 1.
Data center 100 can include rows 102, cooling units 104, and at least one raised floor 106. Rows 102 can include at least one rack 108, which in operation can draw cool air from the front of rack 108 and return warm air to the rear or top of rack 108. In one embodiment, rack 108 may contain U space positions designed to house rack mounted data center equipment, such as, for example, servers, computers, cooling equipment, or network connectivity equipment.
In one embodiment, rows 102 of data center 100 can be positioned to create alternating cold aisles and hot aisles. As illustrated in the embodiment of FIG. 1, aisles 110 are hot aisles and aisles 112 are cold aisles. To provide cooling to racks 108, in front of each rack 108 in cold aisle 112, perforated floor tiles 114 can be used to provide cooling air from under raised floor 106. In data center 100, in addition to the perforated floor tiles 114, raised floor 106 may include solid floor tiles. Cooling units 104 can provide cool air to the area under raised floor 106 and can receive warm air from a space adjacent the ceiling of the data center.
In one embodiment, in addition to or in place of cooling units 104, in-row cooling units, such as those available from American Power Conversion (APC) Corporation of West Kingston, R.I. may be used. In one embodiment, half-rack in-row cooling units may be used with, for example, a width of twelve inches, which is approximately half of that of a standard data center rack.
Data centers 100 may include a plurality of different types of servers. For example, a server may be a physical server, a dedicated server, or a virtual server. A physical server generally includes hardware where an operating system is run. A dedicated server generally includes a service application running on a physical server. For example, a dedicated server may include a web service or file transfer protocol (FTP) service on an operating system, where the service application can be coupled to the physical server. A virtual server can include a service that is independent of physical server hardware. For example, a virtual server may include a partitioning of a physical server into multiple servers, each having the appearance and capabilities as if they were running on their own dedicated server. In one embodiment, there can be one dedicated server operating system per physical server and multiple virtual servers per physical server. A virtual server can run concurrent with (e.g., on top of) a dedicated server.
FIG. 2 is a block diagram of a data center control system 200 in accordance with an embodiment. In one embodiment, system 200 includes at least one data center 100. A plurality of data centers 100 can be associated with each other via at least one network 205 and at least one data center controller 210. Network 205 can include at least one network of interconnected computers such as the Internet, any wide, local, metro, wireless, telephone, cellular, satellite, or other area networks, or combinations thereof. Network 205 may include network infrastructure equipment such as servers, routers, nodes, or switches, for example. In one embodiment, data center 100 components interconnect with each other or with data center controller 210 via at least one network 205. Servers in data center 100 and network infrastructure devices of network 205 may be grouped into network zones or clusters so that network 205 security remains intact during and after server additions or changes.
In various embodiments, data center controller 210 can be located within one or more data centers 100, or remotely located external to data centers 100. For example, data center controller 210 may be located external to data center 100 and connected to data center 100 via network 205. In one embodiment data center controller 210 includes a device such as a processor, microchip, or circuit to identify, manage, and control data center characteristics. In one embodiment, data center controller 210 can receive data related to at least one data center 100. For example, data center controller 210 may receive, measure, or monitor data indicative of data center 100 temperature, capacity, power or current draw, or other data indicating an operational state of data center 100 or its components. In one embodiment, data center controller 210 can simulate data center 100 operation. In this embodiment, data center characteristics may be based on simulated or estimated—as opposed to measured—data center conditions such as temperature, capacity, or energy data. This simulated data may be either generated or received by data center controller 210.
Data center controller 210 may also contain data indicating maximum tolerances or capacities of data center 100. In one embodiment, at least one database 215 stores data indicating tolerances or maximum capacity of data center 100. Database 215 may be part of data center controller 210 or may be located elsewhere and accessible to data center controller 210 via, for example network 205. Database 215 may include data from more than one data center 100. In one embodiment, each data center 100 includes at least one database 215 that stores data indicating data center 100 information, such as tolerance or capacity ranges. Data center controller 210 in one embodiment may include an InfraStruXure® managing platform available from American Power Conversion Corporation® of West Kingston, R.I.
In one embodiment, data center controller 210 evaluates real-time or near real time data from one or more data centers 100. For example, data center controller 210 can determine if data center 100 is operating at capacity. Data center controller 210 can also determine or receive information indicating the operational state of individual devices, components, or subsystems of data center 100. For example, data center 100 may include a plurality of servers. Via network 205, data center 100 may provide data to data center controller 210 indicating that a particular server in data center 100 is not operating at capacity and therefore may be capable of executing additional applications.
In one embodiment, data center 100 includes one or more subsystems. Examples of subsystems include one or more equipment subsystems 220, power generation subsystems 225, uninterruptable power supply subsystems 230, cooling subsystems 235, security subsystems 240, energy storage subsystems 245, and communications subsystems 250. Subsystems generally include one or more data center 100 devices tasked with a function. For example, as illustrated in the embodiments of FIGS. 1 and 2, cooling subsystem 235 may include one or more cooling units 104 tasked with regulating data center 100 temperature. In another example, equipment subsystem 220 may include servers or other logic devices that perform computing functions.
In one embodiment, communications subsystem 250 includes computer hardware that provides data to at least one data center controller 210 via network 205. For example communications subsystem 250 may indicate that data center 100 is operating at 80% of its capacity based at least in part on, for example, a cooling capacity analysis performed on data center 100. In another example, communications subsystem 250 may indicate that a particular device, such as a server from equipment subsystem 220, is operating at 45% of its processing capacity. In this example, the server may be available for further processing operations. In one embodiment, communications subsystem 250 can provide to data center controller 210 maximum, minimum, or tolerance and operational data of data center 100, its associated subsystems, or individual data center components or devices. Communications subsystem 250 may also indicate that data center 100 has or does not have sufficient physical space for the insertion of additional components. In one embodiment, communications subsystem 250 includes at least one database 215.
Communications subsystem 250 may also indicate the status of data center 100 or its associated subsystems in general. For example, communication subsystem 250 may indicate that a power failure has occurred. A power failure may be due to a failure of the local power grid or a malfunction of a device or subsystem of data center 100, for example. Communications subsystem 250 may then provide information to data center controller 210 indicating that a power failure has occurred.
In one embodiment data center controller 210 continuously or periodically receives or monitors information about one or more data centers 100. From this information, data center controller 210 can determine the operational status, range, and tolerance of data centers 100 as a whole, as well as their individual devices (e.g., servers) or subsystems. Based at least in part on the received or monitored information, data center controller 210 may then reallocate applications between one or more data centers 100, identify one or more data centers 100 as a location to run an application, or identify a location in data center 100 as a location to add new hardware or a virtual server that can be used to run an application. In one embodiment, the received information includes simulated or estimated data center information.
For example, a first data center 100 may be operating at greater than 90% of its maximum cooling capacity. This information may be provided from communication subsystem 250 to data center controller 210. A second data center 100 may be operating at 30% of its maximum cooling capacity, and this information may be provided to data center controller 210 as well. In this example, data center controller 210, having identified the cooling capacity parameters of first and second data centers 100, may determine that second data center 100 can run an application that is currently run by first data center 100. Data center controller 210 may then instruct transfer of an application from first data center 100 to second data center 100. In this example, transferring an application from a first data center 100 to a second data center reduces first data center activity, which may lower the temperature of the first data center 100, and increase the available cooling capacity and available power capacity.
In one embodiment, data center controller 210 can identify one of data centers 100 as a location to execute a new application. For example, one or more data centers 100 may be operating at various capacities with respect to temperature, power, or other parameters. Data center controller 210 can evaluate the operating conditions of one or more data centers 100 to determine a data center 100 suited to execute a new application. In various embodiments, the determination can be based on any combination of temperature, power, current, cooling, energy, security or other data center 100 parameters such as location. For example, two data centers 100 may be drawing substantially the same amount of power, but may be located in different geographical locations. Data center controller 210 may identify one of these two data centers 100 as a location to execute the new application because, for example, data center controller 210 evaluates information indicating that energy costs at the second location are less than energy costs at the first location. In this example, both data centers 100 may be capable of executing the new application, however energy costs make data center 100 at the second location a more suitable location in this example.
It should be appreciated that energy costs and other external factors need not be determinative when data center controller 210 identifies a location to run an application. Data center controller 210 may evaluate combinations of operational data (e.g., real time data), data center parameters (e.g., power consumption, cooling capacity, efficiency, reliability, redundancy, backup run time, tolerances of data centers 100, their subsystems, or individual components), as well as external factors, (e.g., local energy, security, or labor costs) of one or more data centers 100 to identify one or more data centers 100 as a location to run an application. Data center controller 210 may evaluate combinations of simulated data, such as simulated power consumption, simulated cooling capacity, simulated efficiency, simulated redundancy, and simulated backup run time of one or more data centers 100, their subsystems, or individual components.
In FIG. 3 there is illustrated an example data center control system 200. In one embodiment, data center controller 210 provides an overview of data center 100 operation in real time, and during planned events such as routine maintenance, or unplanned events such as power outages or other unplanned disruptions. In one embodiment, data center controller 210 includes a change and capacity manager 305 that may determine data center 100 power and cooling characteristics as described in U.S. patent application Ser. No 11/342,300 filed Jan. 27, 2006, entitled Methods and Systems for Managing Facility Power and Cooling, which is incorporated herein by reference in its entirety. Change and capacity manager 305 may determine the capacity of data centers 100. For example, change and capacity manager 305 may include a processor or logic device such as a circuit or microcontroller that identifies data center capacity. In one embodiment communications subsystem 250 provides to change and capacity manager 305 information regarding data center 100 capacity. For example, change and capacity manager 305 may indicate real time capacity of data center 100. A display may provide this information to a technician or person charged with data center 100 management.
At least one equipment capacity and status manager 310 can sample or monitor data center 100 equipment to determine an operational state (e.g., status) and operational range (e.g., capacity) of data center 100 equipment such as servers. For example, equipment capacity and status manager 310 may indicate that a virtual server in a particular rack of data center 100 is operating at 95% capacity. In another example, with reference to FIGS. 1 and 3, equipment capacity and status manager 310 may determine that cooling unit 104 is operating at 100% capacity, or that, for example, cooling unit 104 has been operating at greater than 90% capacity for a determined amount of time. In one embodiment, equipment and capacity manager 310 provides information to change and capacity manager 305 for further evaluation.
Data center controller 210 may also include at least one server and network manager 315, referred to for convenience as server manager 315. In one embodiment, server manager 315 manages and monitors performance criteria for physical, dedicated, or virtual servers located in data center 100. For example, server manager 315 may monitor server performance and determine that a server is operating at a certain percentage of its processing capacity. In one embodiment server manager 315 maintains and configures network equipment so that servers are located within a particular network, cluster, or zone. Server manager 315 may also indicate that a server is to be added to one or more data centers 100, removed from one or more data centers 100, or moved from one data center 100 to another data center 100.
In one embodiment, server manager 315 can include a redundant application running on multiple virtual servers. For example, an application may have a redundancy requirement for backup purposes. Examples of such applications include payroll, accounting, security, investment, banking, or other applications where an application failure is to be generally avoided. In this example, server manager 315 may identify and manage redundancy capabilities of one or more servers. In one embodiment, server manager 315 may run in one or more physical locations. Server manager 315 may also move between physical locations for example by operating on different servers.
In another example, server manager 315 may be implemented on dedicated hardware located in data center controller 210 or in data center 100. Further, server manager 315 may instruct that an application be provided to a particular server for execution in response to input from a technician, or at a particular time, for example. In one embodiment, server manager 315 can instruct that all or part of an application be moved from a first server to a second server. In this illustrative embodiment, first and second servers may be located in the same or different data centers 100. For example, server manager 315 may instruct that an application be distributed across a plurality of virtual servers located in more than one data center 100.
Data center controller 210 may also include at least one hardware manager 320. Hardware manager 320 generally optimizes data center 100 performance by monitoring equipment parameters, energy efficiency, total cost of ownership, maintenance, and disaster events to allocate resources in and between data centers 100. In one embodiment, hardware manager 320 unites the functionality of change and capacity manager 305 and server manager 315. For example, hardware manager 320 may evaluate information from change and capacity manager 305 and server manager 315 to provide instructions on where to locate a server. Factors considered by hardware manager 320 in identifying server locations in one or more data centers 100 include power grid outages, maintenance, environmental changes, local time, availability of on-site staff, increasing or decreasing utilization of data center 100. Other factors may be provided by change and capacity manager 305, equipment capacity and status manager 310, or server manager 315, for example.
In one embodiment, a technician may provide instructions to execute an application, or data center 100 operating requirements. For example, a technician may input parameters to hardware manager 320 instructing that no new physical servers are to be added to one or more data centers 100. In this example, hardware manager 320 may identify a virtual server location to execute an application. In another example, a technician may provide a maximum power draw for data center 100 due to an unreliable local power grid that supplies power to data center 100. In this example, hardware manager 320 may time shift or distribute applications to other data centers 100 to keep a power draw of data center 100 below a specified maximum power draw.
In one embodiment, hardware manager 320 provides instructions to move a server from a first location in a first data center 100 to a second location in the first or in a second data center 100. For example, hardware manager 320 may automatically move a server such as a virtual server from a first location in a first data center 100 to a second location in the first or a second data center 100. In one embodiment, based at least in part on data center 100 information, hardware manager 320 may move or provide instructions to move a server to a location in data center 100. Data center 100 information may include status and parameter information of data center components, total cost of ownership factors such as labor and energy costs, security, availability demands, and dynamic requirements such as power, cooling, extended runtime, and redundancy requirements. Hardware manager 320 may also identify reliability or other requirements of servers, network equipment, or other devices in data centers 100. Examples of these requirements include redundancy, runtime, power usage, processing speed or capacity, heat generation, security, power supply, power demand, and network zones associated with data center devices or applications. In one embodiment, hardware manager 320 can evaluate the nature of an application to be executed when identifying a location to execute the application within one or more of data centers 100.
In one embodiment, hardware manager 320 includes an application on a client platform in communication with one or more of change and capacity manager 305, equipment capacity and status manager 310, and server and network manager 315. For example, a hardware manager application may interact with one or more of managers 305 and 310 to identify data center 100 status and configuration information of servers located in data center 100. A hardware manager application may also identify network equipment forming part of network 205, total cost of ownership factors, and data center 100 power generation, storage, or cooling information.
In one embodiment, data center controller 210 includes at least one shared data center network manager 325. Shared data center network manager 325 may monitor demands and operations of one or more networks 205. For example, network 205 infrastructure or equipment may have operational limitations or functional requirements. Network infrastructure limitations, such as capacity, reliability or bandwidth, can be determined by network manager 325 and provided to hardware manager 320 or other data center controller 210 components as a factor that may be considered when identifying a location to execute an application.
It should be appreciated that data center controller 210 need not include separate elements of change manager 305, equipment capacity and status manager 310, server manager 315, hardware manager 320, and shared data center network manager 325. Data center controller 210 may include other elements, such as one or more processors or circuits that can monitor parameters, requirements, and usage of data centers 100 and their components, including servers. In one embodiment, responsive to information received from data centers, data center controller 210 identifies at least one data center 100 as a location to execute an application. The application can be executed on existing equipment, or new equipment such as a virtual server can be added to data center 100 to execute the application.
In one embodiment, data center controller 210, including any combination of its subsystems and managers 305-325, can identify and track the physical location of servers. For example, data center controller 210 may be provided with information indicating that a particular server is located in a particular data center 100. Data center controller 210 may optimize the location of servers within data centers by evaluating server, data center 100, and network 205 information such as parameters, requirements, and operational status information. In one embodiment, data center controller 210 requests virtual, dedicated, or physical server movement, placement, addition, or relocation. This may be, for example, in response to application requirements, data center 100 operating conditions such as planned or unplanned service or maintenance, or network 205 operating conditions such as power grid outages. Requests for server movement may be responsive to power, cooling, or capacity operating conditions of data center 100. Server moves requested by data center controller 210 can increase data center 100 efficiency, reliability, and performance, and can reduce operational cost.
In one embodiment, with respect to FIGS. 1 to 3, data center controller 210 may identify a particular data center 100, or a particular rack 108 where a server is to be inserted. For example, data center controller 210 may identify an existing physical server in data center 100 and instruct that the existing physical server be modified to include a virtual or dedicated server. In one embodiment, data center controller 210 evaluates information from a plurality of data centers 100 and identifies a minimum number of virtual severs that can be used to execute one or more application or to perform one or more operation. This may include a cluster of virtual servers. In this illustrative embodiment, remaining data center 100 physical hardware can be shut down or put in a lower power standby mode. This conserves energy and reduces data center 100 cooling requirements.
In one embodiment, data center controller 210 provides an indication of power grid outages, data center 100 failures, or other disruptions. For example, data center controller 210 may identify a battery shutdown, warning, or other problem with data centers 100 or networks 205. Data center controller 120 may provide to a technician an indication of a data center 100 maintenance request.
In one example, with reference to FIGS. 1-3, data center 100 may be arranged in such a manner that cooling unit 104 is ineffective or inefficient. In this example, based on information received from data center 100 such as temperature data or cooling information, data center controller 210 may identify one or more servers (or other devices) that generate an undue amount of heat. Continuing with this example, data center controller 210 may identify a server for relocation nearer to cooling unit 104. Data center controller 210 may also identify a physical server as generating an inordinate amount of heat, and in response may transfer one or more virtual servers associated with that physical server to a different location in the same or a different data center 100.
It should be appreciated that data center components may be evaluated to increase data center performance or operation. For example, data center controller 210 may identify an inefficiently operating server. In this example, data center controller 210 may identify a hardware or software upgrade. Data center controller 210 may then proceed to install or request an upgrade of the server.
In one embodiment, data center controller 210 may evaluate data center information to identify or determine available data center capacity. For example, data center controller 210 may identify available capacity of data center 100 as a whole, or of individual data center components such as servers. In this example, data center controller 210 may indicate that available data center capacity is available for lease, rent, or sale. In one embodiment, leasing of spare data center capacity takes place via a centralized data center capacity leasing system that can identify and indicate the availability of capacity in one or more data centers 100. In one embodiment, spare data center capacity may be distributed to one or more data centers 100 to increase data center 100 performance or to decrease cost. Data center controller 210 may also indicate a need for additional capacity to run an application, and may import or export data center capacity from one or more data centers 100. It should be appreciated that this additional capacity may function as a commodity. For example, like electricity and other energy resources, data center capacity can be sold, leased, or reserved.
Data center 100 may use a three phase power supply where uninterruptable power supply subsystem 230 includes a three phase uninterruptable power supply (UPS). In this example, the three phase UPS can distribute three phase power to power distribution units (PDUs) or circuit breaker panels of data center 100. From the PDUs, the power can be delivered to racks 108 via one or more single phase or three phase branch circuits. In this example, power utilization by data center devices, (e.g., subsystems, servers, or equipment) may be either single phase or three phase, and a server or other equipment may be unaware of the phase it is using. In one embodiment, data center controller 210 may monitor server reported power consumption values from a server of data center 100. In another embodiment, data center controller 210 monitors phase loading within a three phase power system of data center 100. In this embodiment with a three phase power system, data center controller 210 may be provided with phase specific information (e.g., the phase a server is connected to) in addition to any server reported power consumption information that indicates power consumption without specifying a phase.
In one embodiment, available unused UPS capacity of rack 108 may be determined. In another embodiment, where for example available unused capacity of a three phase UPS does not provide a sufficiently accurate indication of data center 100 power characteristics, the load of the individual phases at the UPS, at the PDU inputs, and at branch circuits may be determined. For example, in a three phase power distribution system, the power capacity measurement that most efficiently determines data center available capacity may be the branch circuit power capacity, (e.g., the point at which IT devices or other data center equipment connect to power). In this example, data center equipment may be single phase and connected to one of the three phases of a three phase UPS power system.
In one embodiment, in addition to the available power capacity at the branch circuit, data center controller 210 may also determine or be provided with available power capacity data of the corresponding phase at the UPS associated with the branch circuit, and with available power capacity data of the corresponding phase of the PDU associated with the branch circuit. In one embodiment, capacity at a branch circuit is available when capacity is available at the branch circuit itself, and its corresponding phase at both the PDU and the UPS associated with that branch circuit.
It should be appreciated that capacity may become stranded between PDUs, UPSs, and branch circuits. In other words, some data center 100 devices may have available capacity, but this available capacity may be inaccessible for use by other data center devices. For example, a cabinet such as one of equipment racks 108 may have no IT loads and may have a single phase branch circuit supplied by phase A of a three phase UPS, where the UPS is loaded to 33% with all of this load on phase A. In this example, there is no remaining UPS power for phase A and therefore there would be no available capacity for that rack 108. In this example, rack 108 could be rewired to supply the associated branch circuit from a different phase.
In another example, a rack 108 with no IT loads may have a single phase branch circuit supplied by phase A, where the associated PDU is loaded to 33% with all the load on phase A. In this example, there is no remaining PDU power for phase A and therefore no available capacity for rack 108. In this example, rack 108 could be rewired to supply the associated branch circuit from a different phase.
In another example, a rack 108 with three phase power distribution to the rack 108 rated at 15 kW may be loaded with equipment to a 9 kW capacity distributed equally across all three phases. In this example, each phase would have 2 kW of available capacity, as the power distribution is balanced across the three phases. In this example that, although it may appear that 6 kW of capacity is available, (i.e., 15 kW-9 kW,) due to the balanced distribution each phase has 2 kW of capacity, and in this example a device greater than 2 kW could not be installed in rack 108.
It should be appreciated that on many power grids worldwide, data center equipment is connected to 230V branch circuits, and that in North America three phase power distribution can connect loads such as data center equipment with either 120V or 208V. In one embodiment, 120V and 208V loads can be mixed on a branch circuit of data center 100. Both 120V and 230V loads can be associated with a particular phase, and 208V loads can be connected across two phases and can consume current capacity on both phases. Thus, in one embodiment where data center 100 draws power from a North American power grid, capacity at a branch circuit can be determined based on the availability of capacity at the branch circuit, and its associated UPS and PDU on both of the associated phases connected to the load.
In various embodiments, data center 100 control includes information related to both data center 100 power supply and data center 100 power demand. For example, data center controller 210 may manage information regarding the structure of data center 100 such as its power distribution system, its connection with IT loads such as data center equipment, and the associated phase of the connections.
In one embodiment, data center equipment, such as servers, may include instruments that allow for the reporting of server current and server power consumption information. Further, the physical location of data center equipment may be stored in a database associated with the equipment, or another database such as database 215.
In one embodiment power consumption of a rack 108 may be determined based on reported equipment and power consumption information of the equipment that a database indicates is located in the rack 108. For example, data center controller 210 may use this reported power consumption from server instrumentation of servers known to be located in a rack 108 of data center 100 to determine cooling capacity for all or part of data center 100.
Server instruments that are built into some servers may provide insufficient information to indicate to data center controller 210 which branch circuit or phase it is connected to. In this example, without this information data center controller 210 may not be able to identify server or rack 108 available power capacity due, for example, to the stranded power capacity situations discussed herein. In this example, instruments may be introduced to data center 100 to provide information to data center controller 210.
In one embodiment, power consumption of a rack 108 or other data center equipment may be determined based at least in part on equipment manufacturer data. For example, when phase connections of equipment are known, branch circuit, UPS, and PDU capacities may be determined based at least in part on manufacturer supplied equipment parameters. To simplify these determinations, in one embodiment, branch circuits may be dedicated to a single data center device or piece of equipment, and branch circuit current loads may also be measured. It should be appreciated that such manufacturer data based power capacity determinations may be insufficient for some higher density data centers due, for example, to a high number of phase connections and branch circuit configurations where a branch circuit may be dedicated to a single device.
In one embodiment, instruments may be implemented throughout a power distribution system. For example instruments may be introduced into data center 100 with new devices, or existing data center equipment may be retrofitted. In one embodiment, current can be measured at one or more branch circuits, PDU inputs, and UPS outputs of a power distribution system of data center 100 and this information can be provided to data center controller 210, which can quantify power demand of data center 100 based at least in part on this information. When, for example, data center controller 210 includes a logical representation of interconnections between racks 108, PDUs, and UPSs of data center 100, available power capacity that takes into account the phase loading effects can be determined for all branch circuits of data center 100.
As discussed, data center controller 210 may assist in the deployment of new data center equipment, devices, or IT equipment. In one embodiment, data center controller 210 may identify a location in data center 100 for placement of a device in a way that balances loads between the phases of a three phase power supply. When data center equipment is added to a data center, or moved within a data center, data center controller 210 may indicate that the equipment is to be coupled to underutilized phases of the power system serving data center 100. For example, equipment loads that operate at a power density above an average data center design density could be directed by data center controller 210 to be coupled to phases that are underutilized. Analogously, equipment loads that operate at a power density below an average data center design density could be directed by controller 210 to be coupled to phases that are over utilized. In one embodiment, repeating this phase-utilization based approach for devices added to or moved within data center 100 can optimize phase balance and rack 108 space utilization.
It should be appreciated that a failure to deploy data center equipment in a balanced manner can lead to stranded power capacity that appears to be present in some data center equipment, such as a PDU, branch circuit, or UPS, but that cannot be utilized due to the configuration of the data center equipment or power system, thus reducing data center 100 efficiency and the amount of equipment that can be deployed.
Balancing the phase utilization of a three phase power supply can effect rack 108 power distribution and data center 100 power density. In one embodiment, data center controller 210 can identify zones of equipment enclosures within data centers 100. For example, with respect to FIG. 1, row 102 may be a zone of data center 100. In this example, data center controller 210 may determine or specify the average rack power or peak to average rack ratio for each zone. Continuing with this example, the peak to average ratio may impact the amount of stranded power capacity that can exist. In one embodiment, data center controller 210 may increase the peak to average ratio to a value 20% larger than the value expected from typical rack 108 variations. This can reduce the amount of stranded power capacity due to imbalances between branch circuits.
In one embodiment, three phase power distribution to a rack 108 enables data center controller 210 to assign equipment to different phases of that rack 108, resulting in a balanced application of power phases. In an embodiment with single phase power distribution to a rack 108, data center controller 210 may direct relocation of branch circuits between racks 108.
Turning to FIG. 4, there is illustrated an example server configuration in data center 100. Each server depicted in the example of FIG. 4 may include at least one physical, dedicated, or virtual server, and the servers as depicted in FIG. 4 may be physically located in one or more than one data center 100. In one embodiment, data center servers may include an FTP server 405, file and backup server 410, web server 415, order server 420, database server 425, email server 430, and streaming server 435. It is appreciated that this server configuration is an example and is not limiting. Other server functions, applications, and configurations are possible. Although depicted in FIG. 4 as being located within one data center 100, the server configuration of FIG. 4 and other server configurations may be located in more than one data center 100.
In one embodiment, different applications to be executed on one or more of servers 405 to 435 illustrated in FIG. 4 can have different reliability parameters. Further, the insertion of a server into a server configuration can require different reliability parameters, and can change existing reliability parameters. As depicted in FIG. 4, FTP server 405 and file and backup server 410 may have a low level of reliability, email server 430 and streaming server 435 may have a medium level of reliability, and web server 415, order server 420, and database server 425 may have a high level of reliability. It should be appreciated that other configurations and reliability parameters are possible.
In one embodiment, information technology (IT) or network infrastructure equipment connecting servers in one or more data centers 100 can include connections sufficient to support a requisite level of reliability. For example, FTP server 405 may have a low reliability parameter. Therefore, it may be sufficient for FTP server 405 to be associated with file and backup server 410 that also has, in this example, low reliability demands. In one embodiment, streaming server 435, with, for example, a medium reliability parameter, can be added to the server configuration of FIG. 4. In this example, added streaming server 435 may include a server that can execute a streaming application. However, an inserted streaming server 435 would depend on file and backup server 410, which in this example has a low reliability parameter insufficient to execute the medium reliability streaming application in this example.
With reference to FIGS. 3 and 4, a component of data center controller 210 such as server and network manager 315 can identify network or IT connections between servers. In this example, server and network manager 315 may indicate that file and backup server 410, or a connection between added streaming server 435 and file and backup server 410, would have an insufficient reliability rating to execute a streaming application. Responsive to this determination, server and network manager 315 may instruct that the reliability of file and backup server 410 increase to a level sufficient to allow insertion of streaming server 435 for execution of a streaming application. In one embodiment, dependencies between servers or other elements of data centers 100 or networks 205 can be identified by data center controller 210 or associated components to identify a location to execute an application, and to identify modifications that may be made to data centers 100 to efficiently execute applications at a low cost.
In FIG. 5 there is shown an example of server configuration in data center 100. In one embodiment, FIG. 5 includes first server 505 and second server 510, which, with reference to FIG. 1, may be located in one or more racks 108. First server 505 and second server 510 may each include one or more virtual, physical, or dedicated servers. In one embodiment, first server 505 and second server 510 can be physical infrastructure components that form part of network 205.
As illustrated in FIG. 5, second server 510 including server and network manager 315 implemented as dedicated hardware within second server 510. In one embodiment not shown explicitly in FIG. 5, server and network manager 315 can be implemented in an application run on a virtual or physical server included within first server 505, second server 510, or both. Data centers 100 may include more than one server and network manager 315 to provide sufficient levels of redundancy and reliability. For example, as illustrated in FIG. 5, first server 505 is located in uninterruptable power supply (UPS) zone 1, and second server 510 is located in UPS zone 2. In one embodiment, both first and second servers 505 and 510 include server manager 315 in the form of a virtual or physical server application. In the event of, for example, a power failure in one of the first and second zones, one of first and second servers 505 and 510, with server manager 315, can remain in operation. Thus, server manager 315 may track and optimize physical locations of servers to identify or request server moves in the event of power outages, service, or maintenance disruptions.
Server and network manager 315 may be provided with parameters, requirements, or operational information of second server 510, as well as those of first server 505 or other servers. In one embodiment, server and network manager 315 may instruct one or more of first and second servers 505 and 510 to execute an application based at least in part on server or data center parameters.
FIG. 6 is a flow chart illustrating an example computer implemented method 600 for data center control. In one embodiment, method 600 includes an act of identifying parameters of data centers (ACT 605) where each data center includes at least one device. For example, identifying data center parameters (ACT 605) may include identifying data center power draw, energy use, cooling capacity, processing capability, operational capacity, tolerances, requirements, or operational ranges.
Identifying data center parameters (ACT 605) may include identifying parameters of data centers as a whole as well as identifying parameters of data center components such as servers or cooling units. Identifying data center parameters (ACT 605) may include identifying parameters of one or more networks associated with a data center. For example, a plurality of data centers may be interconnected by one or more networks and controlled by a controller. Identifying data center parameters (ACT 605) may include identifying parameters of networks, where network parameters may limit data center operation.
In one embodiment, identifying data center parameters (ACT 605) includes identifying parameters or characteristics of select data center devices. Examples of data center devices include cooling subsystems, power subsystems, power generation subsystems, security subsystems, uninterruptable power supplies, servers, processors, and computers. It should be appreciated that this list is not exhaustive and that data center devices include other components and logic devices, for example. Identifying data center parameters (ACT 605) may include identifying or determining individual status, requirement, dependency, and operation information for data centers, their subsystems, and individual components. In one embodiment, identifying data center parameters (ACT 605) includes identifying power grid parameters of a power grid from which a data center draws power. Other such external parameters may also be identified. For example, identifying data center parameters (ACT 605) may include identifying labor conditions, political or economic turmoil, or other external factors that can effect data center operation. Further examples of data center parameters include any of data center environmental data, temperature inside a data center, temperature outside a data center, power cost, cooling cost, data center facility lease, rent, or ownership cost, service cost, maintenance cost, and labor cost. It should be appreciated that these lists are examples and are not exhaustive. In various embodiments, the data center parameters may include current or historical data. In one embodiment, identifying data center parameters (ACT 605) may occur in real time or periodic intervals.
Identifying data center parameters (ACT 605) may also include identifying factory provided or built-in device tolerance data. Identifying data center parameters (ACT 605) may include monitoring or sampling data centers or their equipment to determine the parameters. In one embodiment, identifying data center parameters
(ACT 605) includes receiving information identifying the parameters. In one embodiment data center parameters that are identified (ACT 605) can be stored for subsequent retrieval in one or more databases or memory storage devices. In one embodiment, identifying data center parameters (ACT 605) includes identifying which data centers or data center components may be available to execute additional applications. For example, a list of available data centers may be provided and ranked in order of available capacity or in order of operating expense. Such a list may be stored in a database and updated in real time or periodically as data center parameters change.
In one embodiment, identifying data center parameters (ACT 605) includes determining the impact that any added components such as subsystems, hardware, or virtual servers have on a data center. For example, identifying data center parameters (ACT 605) may include determining an impact any added data center components have on data center cooling capacity, power draw, or performance.
In one embodiment, method 600 includes an act of indicating excess data center capacity (ACT 610) of one or more data centers. For example, indicating excess data center capacity (ACT 610) may include providing an indication of excess data center capacity to a technician, or to a logic device associated with a different data center that may have less or no excess capacity. In one embodiment, indicating excess data center capacity (ACT 610) includes a graphical display of data center operating capacity or excess capacity in real time. For example, indicating excess data center capacity (ACT 610) may include providing information indicating that a data center is operating at, for example, 80% capacity and thus has 20% excess data capacity. By redistributing data center applications or shutting down data center devices, excess data capacity can be provided to other data centers, reduced, or eliminated.
Method 600 may also include an act of detecting an application failure (ACT 615). In one embodiment, detecting application failure (ACT 615) includes detecting application failure due to a lack of an available data center, data center operational problems, maintenance, network problems, or power supply problems. In one embodiment, an indication of an application failure at a data center may be detected (ACT 615) at a location internal to or remote from the data center where the application failure occurred.
In one embodiment, detecting an application failure (ACT 615) includes locating data center or network equipment associated with or effected by the failure. For example, an application may fail to execute as intended when run on a server. In this example, the server may be identified and identifying information may be provided to a technician, controller, or logic associated with the same or different data centers. In one embodiment, where an application fails to properly execute on a physical server, one or more virtual servers running on top of the virtual server may also be identified. The virtual servers may then be transferred to a different location within the same data center, or to a different data center. In one embodiment, responsive to detecting application failure (ACT 615), a temporary location may be found for application transfer. This temporary location may not be the most suitable location for long term application execution. For example, running the application at the temporary location may increase the burden on a data center component to an unsustainable level. In this example, an application may run at a temporary location until a more suitable location can be identified.
In one embodiment, detecting an application failure (ACT 615) includes providing information related to the failure to technicians. This information may identify failed data center or network equipment, transferred virtual servers, new hardware, maintenance operations, and shut down signals, for example.
Method 600 may include an act of generating a request to add hardware to a data center (ACT 620). In one embodiment, responsive to detecting an application failure (ACT 615), method 600 includes an act of generating a request to add hardware (ACT 620). For example, an application may fail due to a lack of server processing capacity in a data center. Responsive to detection (ACT 615) of this failure, method 600 may generate a request (ACT 620) to add hardware to the data center where the application failed. An attempt may then be made to execute the failed application using new hardware added to the data center responsive to the request (ACT 620). Generating a request to add hardware to a data center (ACT 620) may also include providing the request to a data center technician. In one embodiment, a generated (ACT 620) request may be displayed on a graphical interface. Generating a request (ACT 620) may include generating a request to add a virtual server to a data center.
Method 600 may include an act of disabling one or more data center devices (ACT 625). In one embodiment a data center device such as a server or other component may not be in use, or may be used at a fraction of its capacity. Disabling a data center device (ACT 625) can increase data center efficiency, reduce power draw, and reduce heat generation, all of which can lower the cost of data center operation. Disabling a data center device (ACT 625) may include shutting down a device, removing a device such as a physical or virtual server from a data center, or putting a device in a sleep mode that reduces power draw of that device. In one embodiment, disabling a data center device (ACT 625) includes transferring applications running on that data center device to a different device that may be located in the same or a different data center prior to disabling the device.
In one embodiment, method 600 includes an act of monitoring network equipment parameters (ACT 630). For example, network limitations can limit data center operation. This may include limitations of the network infrastructure equipment that form at least part of the network. Monitoring network equipment (ACT 630) may include any of receiving an indication of network equipment requirements, dependencies, capacity, speed, functionality, or bandwidth. This list of examples is not exhaustive. Monitoring network parameters (ACT 630) may include detecting a network failure or disruption, and may include detecting a power grid disruption of a power grid that may provide power to a data center. In one embodiment, monitoring network equipment (ACT 630) includes monitoring the status of individual network elements, devices, or components such as servers, switches, or routers.
Method 600 may include an act of receiving a warning message (ACT 635). For example, receiving a warning message (ACT 635) may include receiving a message of planned or unplanned data center maintenance, or a power disruption in a location that includes a data center. In one embodiment, receiving a warning message (ACT 635) may include identifying a problem with a data center. For example, receiving a warning message (ACT 635) may include receiving a message that data center components or subsystems are operating at or near capacity.
In one embodiment, receiving a warning message (ACT 635) may include receiving information indicating that a data center, its subsystems (e.g., cooling units) or components (e.g., servers) are being underutilized. For example, a warning message may be received (ACT 635) that a data center or component (e.g., device) thereof is currently using 5% of its available processing capacity. Responsive to this warning message, the data center may be shut down at least temporarily. Any applications running at that data center may be stopped, and a technician may be alerted. Such action may increase overall efficiency and lower cost when a plurality of data centers operate in concert.
In one embodiment, method 600 includes an act of receiving a command to execute an application (ACT 645). Receiving a command to execute an application (ACT 645) may include receiving a request to execute an application. The request or command may be received (ACT 645) from a data center, a network associated with a data center, or a technician, for example. In one embodiment, receiving a command to execute an application (ACT 645) includes receiving a request to transfer an application between data centers or between data center components of one or more data centers. In one embodiment, receiving a request to execute an application (ACT 645) can be responsive to an act of detecting an application failure (ACT 615) at one or more data centers. In one embodiment, receiving a request to execute an application (ACT 645) includes a controller generating the request. In one embodiment, receiving a command to execute an application (ACT 645) includes receiving a command to execute an application at a data center, where the application was provided by a different data center.
In one embodiment, method 600 includes an act of identifying requirements of an application (ACT 650). For example, identifying requirements of an application (ACT 650) may include identifying system resources used by an application during its execution. System resources may include memory or processor capacity used, as well as heat generated, cooling capacity required to control generated heat, or power draw of equipment used to run, store, or execute the application, for example. In one embodiment requirements of an application are identified (ACT 650) responsive to or together with the received (ACT 645) command to execute the application. Identifying requirements of an application (ACT 650) may include identifying a time period in which an application is to be executed. In one embodiment, identifying requirements of an application (ACT 650) includes identifying redundancy, accuracy, reliability, or fault tolerant requirements of an application.
In one embodiment, method 600 includes an act of identifying a data center as a location to run the application (ACT 655). This may include identifying a data center (ACT 655) from a plurality of data centers based at least in part on an evaluation of parameters of the plurality of data centers. These parameters may include, for example power, current, energy, cooling, and device characteristics of data centers as a whole, data center equipment, and network equipment of networks connecting a controller to one or more data centers. Identifying a data center (ACT 655) may include identifying a data center or individual components or subsystems thereof, such as a server. In one embodiment, identifying a data center (ACT 655) includes identifying a data center based at least in part on requirements of an application that may be executed within a data center.
In one example, a plurality of data centers may be connected to each other via at least one network and also connected to at least one controller. These data centers may be geographically disparate. A first data center may be operating, for example, at 35% of its processing capacity but may be using 98% of its cooling capacity and therefore may be drawing a high amount of power. A second data center may be operating, for example, at 90% of its capacity, but may be using only 60% of its cooling capacity and may, in this example, draw less power than the first data center. Continuing with this example, a controller may evaluate the capacity and power draw data of these two data centers and identify (ACT 655) second data center as a location to execute an application. In this example, the application may be a new application, or may be transferred from the first data center to the second data center. It should be appreciated that identifying a data center (ACT 655) can include an evaluation of more than data center processing, cooling, and power capacities. For example, network equipment and individual data center subsystems and devices may be evaluated when identifying one or more data centers to execute an application (ACT 655).
The above example is not limiting, and other factors, parameters, and requirements may be considered in identifying a data center (ACT 655). For example, two or more data centers may be drawing equal power, but one of the data centers may be located in a nation or region having less expensive power. In this example, identifying a data center (ACT 655) may include identifying the data center that draws power from a less expensive source, as this decreases the total cost of data center operation. In another example, power generated from an environmentally safer source, (e.g., solar, wind, hydroelectric, or nuclear) may influence an act of identifying a data center (ACT 655). Geographic, and political concerns, as well as labor costs are further examples of factors that may be considered when identifying a data center (ACT 655).
In one embodiment, identifying a data center (ACT 655) may include an evaluation of the climate or local weather conditions in an area that includes a data center. For example, in a cold climate a data center may be designed in a way that minimizes the amount of cooling equipment necessary to cool a data center. In another example, the potential for extreme weather conditions, such as hurricanes or blizzards, could lead to power grid disruptions, and may be considered when identifying a data center (ACT 655).
In one embodiment, identifying a data center (ACT 655) may include identifying a particular data center subsystem or device as a location to execute at least part of an application. For example, identifying a data center (ACT 655) may include identifying a first data center or component thereof to run part of an application, and identifying a different component of the first data center to run another part of an application. Further, another part of the application may be run at a second data center or component thereof. In one embodiment, identifying a data center (ACT 655) includes identifying a time to execute an application at one or more data centers. For example, it may be most cost effective to execute an application at a particular data center in the middle of the night due, for example, to data center use conditions or the resources required to run the application.
In one embodiment, identifying a data center as a location to execute an application (ACT 655) includes identifying the effect that an application would have on a data center, should data center components execute the application. For example, a data center may be operating at 77% of its capacity. Identifying a data center as a location to execute an application (ACT 655) may include a determination that executing an application at the identified data center would cause that data center to operate at a different percentage of its capacity. In another example, identifying a data center (ACT 655) may include determining that executing an application on a data center would cause a 0.5% increase in data center power draw if the application is executed during business hours. It should be appreciated that these percentages, and other example percentages used herein, are arbitrary. Other percentages or values indicative of data center or network functionality can be used.
In one embodiment, an indication of the effect an application may have on a data center can be displayed or provided to a technician. In this example, identifying a data center (ACT 655) may occur responsive to an indication from a technician indicating that the effect of an application on a data center is acceptable. In another example, identifying a data center (ACT 655) may occur responsive to an indication from a controller or data center components of any data center indicating that the effect of an application on a data center is acceptable.
In one embodiment, identifying a data center (ACT 655) includes identifying a plurality of data centers having sufficient capacities to execute an application. For example, identified data center parameters may be evaluated to produce a list of suitable locations to execute an application within one or more data centers. In this example, the list may be ordered so that at least one location is identified as a primary location. Continuing with this example, a plurality of servers within one or more data centers may be identified from those having the lowest operating expenses to those having the highest operating expenses. Either the data centers themselves or their individual components or subsystems may be identified (ACT 655). In one embodiment, a cluster of virtual servers in one or more data centers can be identified (ACT 655).
Identifying a data center (ACT 655) may include identifying a location of a virtual server of a data center, where the virtual server has sufficient capacities to execute an application. In one embodiment, identifying a data center (ACT 655) includes identifying a virtual server in a data center, and identifying a suitable alternate location for that virtual server. Such alternate location may be within a data center having lower operating expenses or a lower total cost of ownership than another data center. For example, a virtual server capable of executing an application may be in a data center that has an unreliable power grid, or the virtual server may be reliant on other data center components that are insufficient or unreliable. In this example, identifying a data center (ACT 655) may include identifying an alternate location for the virtual server. The alternate location may be in the same or a different data center. A virtual server or cluster of virtual servers may then be transferred to the alternate location to execute an application.
In one embodiment, identifying a data center (ACT 655) includes identifying a data center as being in need of maintenance. In this illustrative embodiment, a technician may approve a request to upgrade or perform maintenance on a data center, its components, or its associated networks or controllers. For example, virtual server performance may increase if hardware of an underlying physical server is upgraded. In this example, identifying a data center (ACT 655) may include, or be responsive to, a request to upgrade server hardware. In one embodiment, the cost of hardware, maintenance, or installation activity when upgrading equipment or adding hardware can be taken into account when identifying a data center (ACT 655). This may occur, for example, in response to a request to add hardware (ACT 620) to a data center.
A specific application need not be provided for execution prior to the act of identifying a data center (ACT 655). For example, identifying a data center (ACT 655) may include identifying a plurality of data centers having, for example, available server processing capacity. A list of these data centers may be ranked by, for example, amount of processing capacity, cost of operation, location, or other factors. This list may be updated periodically or in real time. This list may be retrieved from a memory storage unit or database where it is stored.
In one embodiment, method 600 may include an act of transferring data center applications (ACT 658). Data center applications may be transferred (ACT 658) between devices within a one data server, or from a first data center to a second data center. In one embodiment, transferring data center applications can be responsive to an act of receiving a warning message from a data center (ACT 635). In one embodiment, components such as virtual, physical, or dedicated servers may be added to a data center for the purpose of receiving a transferred (ACT 658) application. Transferring an application (ACT 658) may include transferring an application to two or more physical or virtual locations, or to a cluster of virtual servers. In one embodiment, transferring an application (ACT 658) includes transferring a portion of an application while another portion of an application remains at an existing physical or virtual location.
In one embodiment, transferring a data center application (ACT 658) includes identifying a data center as being capable of executing an application currently allocated or assigned to a device of a different data center. For example, a plurality of data centers may be operating simultaneously. One of the plurality of data centers may be operating in a location where energy costs are lower than energy costs at the location of other data centers. In this example, transferring a data center application (ACT 658) may include identifying a data center having lower energy costs as a location to execute an application currently executed by a different data center that has higher energy costs. In this example, the application may be transferred (ACT 658) from the data center with higher energy costs to the data center with lower energy costs. This reduces overall operating costs of the plurality of data centers. It should be appreciated that the example of energy costs is not limiting. Other factors, such as labor costs, maintenance, processing capacity, reliability, or power grid durability may be evaluated when transferring a data center to a location to execute an application (ACT 658).
In one embodiment, method 600 includes an act of providing an application to a data center (ACT 660). For example, providing an application to a data center (ACT 660) may include transmitting an application via a network to a data center or component thereof such as a server having sufficient capacity to execute the application. An application may be provided (ACT 660) to a data center via a network, another data center, a technician, or a controller. In one embodiment, providing an application to a data center (ACT 660) includes providing an application to hardware added to a data center responsive to the act of generating a request (ACT 620) to add the hardware. It should be appreciated that providing an application to a data center (ACT 660) may change data center operating characteristics and other parameters.
In one embodiment, method 600 includes an act of instructing a server or other data center component to execute an application (ACT 665). For example, an application may be provided to a data center (ACT 660) for immediate execution by a server or other data center component. Instructing a server to execute an application (ACT 665) may also include instructions as to how an application is to be executed. For example, instructions may include reliability or fault tolerance specifications. In various embodiments, instructing a data center to execute an application (ACT 665) can be responsive to, for example, transferring an application (ACT 658), providing an application to a data center (ACT 660), providing an application to a second data center (ACT 680) or identifying a data center (ACT 655).
In one embodiment, method 600 includes an act of time shifting execution of an application (ACT 670). Time shifting execution of an application (ACT 670) may include delaying execution of an application. For example, when identifying requirements of an application (ACT 650), it may be determined that execution of an application is not time sensitive. Further, a data center may have additional capacity on certain days such as holidays or weekends, or at certain times of day, such as after a stock market is closed or after working hours. In situations such as these, an application may be time shifted (ACT 670) to use a data center during a period of reduced data center activity. In one embodiment, instructions to execute an application (ACT 665) include instructions to time shift execution of the application (ACT 670). In one embodiment, time shifting execution of an application (ACT 670) can be responsive to identification of data center parameters (ACT 605). Further, time shifting execution of an application (ACT 670) may be responsive to receipt of a warning message (ACT 635). The warning message may indicate, for example, that a data center or components thereof are at or near capacity, that data center maintenance is scheduled, that a power grid associated with a data center is disrupted, that there are labor or security concerns, or other factors.
Method 600 may include an act of determining a first data center capacity (ACT 675). For example, determining first data center capacity (ACT 675) may include determining an amount of data center capacity being used, or an amount of data center capacity that is available. The data center capacity that is determined (ACT 675) may include processing capacity, power capacity, or cooling capacity of a data center as a whole or of individual subsystems or elements therein. For example, identifying first data center capacity (ACT 675) may include identifying a server in a data center as having sufficient capacity to execute an application. First data center capacity may be determined (ACT 675) based on information provided by the first data center or its equipment, or by extrapolation based on known equipment tolerances and information related to a number of applications first data center may be executing.
Determining a first data center capacity (ACT 675) may include identifying a data center as having excess or available capacity. Determining a first data center capacity (ACT 675) may also include determining that a data center is operating at capacity. For example, a data center may be drawing 100% of its available power, or data center cooling units may be operating at capacity. Further, servers or other components may be operating at their maximum processing capacity, or memory devices may be full. In one embodiment, identifying data center parameters (ACT 605) includes an act of determining a first data center capacity (ACT 675).
In one embodiment, determining a first data center capacity (ACT 675) may be accomplished by referencing a data center model. For example, a data center controller external to a data center may simulate data center operation. In this example, determining a first data center capacity (ACT 675) may include determining data center capacity based on simulated—as opposed to measured—data center data.
In one embodiment, method 600 includes an act of providing an application to a second data center (ACT 680). Providing an application to a second data center (ACT 680) may occur responsive to at least one of determining first data center capacity (ACT 675), receiving a warning message (ACT 635), detecting an application failure (ACT 615), monitoring network equipment parameters (ACT 630), indicating excess data center capacity (ACT 610), and identifying data center parameters (ACT 605), for example. In one embodiment, providing an application to a second data center (ACT 680) includes providing an application to second data center components such as a server for execution. In one embodiment, providing an application to a second data center (ACT 680) includes providing a portion of the application to a second data center.
Various aspects and embodiments described herein may be implemented on one or more computer systems as discussed above. For example, system 200 may be implemented in a single computer system or in multiple computer systems. These computer systems may be, for example, general-purpose computers such as those based on Intel PENTIUM-type processor, Motorola PowerPC, Sun UltraSPARC, Hewlett-Packard PA-RISC processors, or any other type of processor.
For example, various aspects may be implemented as specialized software executing in a general-purpose computer system 700 such as that shown in FIG. 7. The computer system 700 may include a processor 705 connected to one or more memory devices 710, such as a disk drive, memory, or other device for storing data. Memory 710 is typically used for storing programs and data during operation of the computer system 700. The computer system 700 may also include a storage system 715 that provides additional storage capacity. Components of computer system 700 may be coupled by an interconnection mechanism 720, which may include one or more busses (e.g., between components that are integrated within a same machine) and/or a network (e.g., between components that reside on separate discrete machines). The interconnection mechanism 720 enables communications (e.g., data, instructions) to be exchanged between system components of system 700.
Computer system 700 also includes one or more input devices 725, for example, a keyboard, mouse, trackball, microphone, touch screen, and one or more output devices 730, for example, a printing device, display screen, speaker. In addition, computer system 700 may contain one or more interfaces (not shown) that connect computer system 700 to a communication network (in addition or as an alternative to the interconnection mechanism 720).
The storage system 715, shown in greater detail in FIG. 8, typically includes a computer readable and writeable nonvolatile recording medium 805 in which signals are stored that define a program to be executed by the processor or information stored on or in the medium 805 to be processed by the program to perform one or more functions associated with embodiments described herein. The medium may, for example, be a disk or flash memory. Typically, in operation, the processor causes data to be read from the nonvolatile recording medium 805 into another memory 810 that allows for faster access to the information by the processor than does the medium 805. This memory 810 is typically a volatile, random access memory such as a dynamic random access memory (DRAM) or static memory (SRAM). It may be located in storage system 715, as shown, or in memory system 710. The processor 705 generally manipulates the data within the integrated circuit memory 710, 810 and then copies the data to the medium 805 after processing is completed. A variety of mechanisms may manage data movement between the medium 805 and the integrated circuit memory element 710, 810, and the examples provided herein, including example memory system 710 and storage system 715 are not limiting.
Computer systems implemented herein may include specially-programmed, special-purpose hardware, for example, an application-specific integrated circuit (ASIC). Various aspects described herein may be implemented in software, hardware or firmware, or any combination thereof. Further, such methods, acts, systems, system elements and components thereof may be implemented as part of the computer system described above or as an independent component.
Although computer system 700 is shown by way of example as one type of computer system upon which various aspects described herein may be practiced, it should be appreciated that aspects and embodiments are not limited to being implemented on the computer system as shown in FIG. 7. Various aspects may be practiced on one or more computers having a different architecture or components shown in FIG. 7. Further, where functions or processes of embodiments that are described herein (or in the claims) as being performed on a processor or controller, such description is intended to include systems that use more than one processor or controller to perform the functions.
Computer system 700 may be a general-purpose computer system that is programmable using a high-level computer programming language. Computer system 700 may be also implemented using specially programmed, special purpose hardware. In computer system 700, processor 705 may be a commercially available processor such as the well-known Pentium class processor available from the Intel Corporation. Other processors are available, such as those that can execute an operating system which may be, for example, the Windows 95, Windows 98, Windows NT, Windows 2000 (Windows ME), Windows XP, or Windows Vista operating systems available from the Microsoft Corporation, MAC OS System X operating system available from Apple Computer, the Solaris operating system available from Sun Microsystems, or UNIX operating systems available from various sources. Many other operating systems may be used.
The processor and operating system together define a computer platform for which application programs in high-level programming languages are written. It should be understood that embodiments of the systems and methods described herein are not limited to a particular computer system platform, processor, operating system, or network. Also, it should be appreciated that these systems and methods are not limited to a specific programming language or computer system. Other appropriate programming languages and other appropriate computer systems can be used.
One or more portions of the computer system may be distributed across one or more computer systems coupled to a communications network. For example, as discussed above, network manager 315 may be located remotely from change and capacity manager 305. These computer systems also may be general-purpose computer systems. For example, system 200 elements can be distributed among one or more computer systems configured to provide a service (e.g., servers) to one or more client computers, or to perform an overall task as part of a distributed system. For example, operations may be performed on a client-server or multi-tier system that includes components distributed among one or more server systems that perform various functions according to various embodiments described herein. These components may be executable, intermediate (e.g., IL) or interpreted (e.g., Java) code which communicate over a communication network (e.g., the Internet) using a communication protocol (e.g., TCP/IP). For example, one or more database servers may be used to store device data that is used in designing layouts, and one or more servers may be used to efficiently perform cooling calculations associated with embodiments described herein.
It should be appreciated that aspects and embodiments described herein are not limited to executing on any particular system or group of systems. Also, it should be appreciated that the aspects and embodiments described herein are not limited to any particular distributed architecture, network, or communication protocol.
Various aspects and embodiments may be programmed using an object-oriented programming language, such as SmallTalk, Java, C++, Ada, or C# (C-Sharp). Other object-oriented programming languages may also be used. Alternatively, functional, scripting, and/or logical programming languages may be used. Various aspects and embodiments may be implemented in a non-programmed environment (e.g., documents created in HTML, XML or other format that, when viewed in a window of a browser program, render aspects of a graphical-user interface (GUI) or perform other functions). Various aspects and embodiments may be implemented as programmed or non-programmed elements, or any combination thereof.
Systems and methods are described herein that provide indications of remaining cooling capacity for equipment enclosures. The indication of remaining cooling capacity may be a direct indication of remaining cooling in terms of, for example, kilowatts or BTU per hour, or the indication may be indirect such as providing the total capacity of cooling available to an enclosure along with an indication of how much cooling is being used, for example, in terms of percentage. Further, calculated values, including the capture index and the recirculation index may be used to determine the sufficiency of a particular design and to determine additional cooling capacity before a warning or error condition will result.
In aspects and embodiments discussed herein, results of analyses are described as being provided in real-time. It should be appreciated that the use of the term real-time may, but need not suggest that the results are available immediately. For example, results may become outdated quickly, giving a designer the ability to try a number of different designs over a short period of time, such as a matter of minutes.
Note that in FIGS. 1 through 8, the enumerated items are shown as individual elements. In actual implementations of the systems and methods described herein, however, they may be inseparable components of other electronic devices such as a digital computer. Thus, actions described above may be implemented at least in part in software that may be embodied in an article of manufacture that includes a program storage medium. The program storage medium includes data signals embodied in one or more of a carrier wave, a computer disk (magnetic, or optical (e.g., CD or DVD, or both), non-volatile memory, tape, a system memory, and a computer hard drive.
From the foregoing, it will be appreciated that the aspects and embodiments described herein afford effective data center control. These aspects and embodiments are able to identify a plurality of characteristics from geographically disparate data centers and their associated devices and networks. By evaluating these characteristics, aspects and embodiments can identify data center locations to execute new or existing applications. This redistribution and placement of applications for execution increases data center efficiency and compatibility, saves energy, and lowers operating cost.
Embodiments and aspects described herein are suitable for use in relatively large data centers having numerous equipment racks, as well as smaller or informal data centers and with facilities other than data centers. Estimations of branch circuit capacities and phase balance can become complex in high density data centers. Internal server power instrumentation may provide information to a data center controller to identify cooling susbsystem capacity. In various embodiments, such as those utilizing three phase power supplies or where server instrumentation is lacking, power distribution system instrumentation can provide information used to determine load consumption, available capacities, and phase balance. This information can be used by a data center controller to allocate or reallocate data center devices, subsystems, or equipment to or within one or more data centers. This improves data center operation and efficiency, and lowers operating cost.
Any references to front and back, left and right, top and bottom, and upper and lower are intended for convenience of description, not to limit the present systems and methods or their components to any one positional or spatial orientation.
Any references to embodiments or elements or acts of the systems and methods herein referred to in the singular may also embrace embodiments including a plurality of these elements, and any references in plural to any embodiment or element or act herein may also embrace embodiments including only a single element. References in the singular or plural form are not intended to limit the presently disclosed systems or methods, their components, acts, or elements.
Any embodiment disclosed herein may be combined with any other embodiment, and references to "an embodiment", "some embodiments", "an alternate embodiment", "various embodiments", "one embodiment" or the like are not necessarily mutually exclusive and are intended to indicate that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment. Such terms as used herein are not necessarily all referring to the same embodiment. Any embodiment may be combined with any other embodiment in any manner consistent with the objects disclosed herein. References to "or" may be construed as inclusive so that any terms described using "or" may indicate any of a single, more than one, and all of the described terms.
Where technical features in the drawings, detailed description or any claim are followed by references signs, the reference signs have been included for the sole purpose of increasing the intelligibility of the drawings, detailed description, and claims. Accordingly, neither the reference signs nor their absence have any limiting effect on the scope of any claim elements.
One skilled in the art will realize the systems and methods described herein may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. For example, physically separate data centers in geographically disparate areas may be considered to be one distributed data center. In another example, resources may be allocated or adjusted between one or more devices or subsystems of a single data center. The foregoing embodiments are therefore to be considered in all respects illustrative rather than limiting of the described systems and methods. Scope of the systems and methods described herein is thus indicated by the appended claims, rather than the foregoing description, and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
What is claimed is:
1. A computer implemented method for data center control, comprising:
identifying parameters of a plurality of data centers, each data center including a plurality of devices;
identifying requirements of a device to run an application, including cooling capacity required to control heat generated during execution of the application, simulated redundancy and simulated reliability;
responsive to detecting a failure to execute the application at one of the plurality of data centers, identifying a selected data center from the plurality of data centers as a location to run the application based at least in part on an evaluation of the parameters and the requirements;
transfer the application to the selected data center responsive to identifying the selected data center;
evaluating the parameters and requirements for an underutilization condition of a device of one of the plurality of data centers, including simulated cooling characteristics and simulated power characteristics for each data center of the plurality of data centers, to identify an underutilization condition of a device of one of the plurality of data centers; and
disabling the device of the one of the plurality of data centers based on the underutilization condition.
2. The computer implemented method of claim 1, wherein the evaluation of the parameters and the requirements for identifying the selected data center includes an evaluation of at least one of simulated first data center cooling characteristics and simulated first data center power characteristics for determining a first data center capacity of a first data center;
providing information indicating the first data center capacity to a device associated with a second data center; and
receiving a request to execute, on a device in the first data center, an application provided by the device associated with the second data center.
3. The computer implemented method of claim 1, comprising:
identifying insufficient data center capacity in the selected data center based al east in part on simulated characteristics of the selected data center; and
enabling at least one of an uninterruptible power supply, a server, network equipment, and a cooling unit of the selected data center.
4. The computer implemented method of claim 1, wherein at least two of the plurality of data centers are connected by a network comprising:
monitoring simulated parameters of network infrastructure equipment that forms at least part of the network.
adding a physical server to a cluster of virtual servers of the selected data center; and
distributing at least a portion of the application to the cluster of virtual servers.
providing the application to a virtual server of the selected data center.
disabling at least one of an uninterruptible power supply, a server, network equipment, and a cooling unit associated with at least one of the parameters of the plurality of data centers.
enabling at least one of an uninterruptible power supply, a server, network equipment, and a cooling unit associated with at least one of the parameters of the plurality of data centers.
identifying system requirements to execute the application ; and
time shifting execution of the application based on the evaluation of the parameters, the requirements of the device, and an evaluation of the system requirements.
10. The computer implemented method of claim 1, comprising:
identifying a server in the selected data center as having capacity sufficient to execute the application;
providing the application to the server; and
instructing the server to execute the application.
distributing at least a portion of the application to two or more data centers.
12. A data center activity control system, comprising:
a data center controller associated with a network and configured to identify parameters of a plurality of data centers associated with the network, each data center including a plurality of devices, and to identify requirements of a device to run an application, including cooling capacity requirements to control heat generated during execution of the application, simulated redundancy, and simulated reliability;
the data center controller configured to evaluate the parameters and the requirements to identify a selected data center from the plurality of data centers as a location to run the application responsive to a failure to execute the application at one of the plurality of data centers;
the data center controller configured to transfer the application to the selected data center responsive to identifying the selected data center;
the data center controller configured to evaluate the parameters and requirements for an underutilization condition of a device of one of the plurality of data centers, including simulated cooling characteristics and simulated power characteristics for each data center of the plurality of data centers, to identify an underutilization condition of a device of one of the plurality of data centers; and
the data center controller configured to disable the device of the one of the plurality of data centers based on the underutilization condition.
13. The system of claim 12, wherein the parameters include at least one of simulated power consumption, simulated cooling capacity, simulated efficiency, and simulated backup runtime of a device located in one of the data centers.
14. The system of claim 12, wherein:
the evaluation of the parameters and the requirements to identify the selected data center includes an evaluation of at least one of simulated first data center cooling characteristics and simulated first data center power characteristics to determine a first data center capacity of a first data center; and wherein
the data center controller provides information indicating the first data center capacity to a device associated with a second data center; and wherein
the data center controller receives a request to execute, on a device in the first data center, an application provided by the device associated with the second data center.
15. The system of claim 12, wherein the data center controller monitors parameters of network infrastructure equipment that form at least part of the network.
16. The system of claim 12, wherein the data center controller is configured to distribute at least a portion of the application to a cluster of virtual servers of the selected data center.
17. The system of claim 12, wherein the data center controller is configured to provide the application to a virtual server located in the selected data center.
the data center controller is configured to receive a warning message from a subsystem of a first data center; and wherein:
the data center controller is configured to transfer, via the network, a first application from a server located in the first data center to a server located in a second data center.
the data center controller is configured to identify system requirements to execute the application; and wherein
the data center controller is configure o time shift execution of the application based on in part on the system requirements.
a server in the selected data center includes capacity sufficient to execute the application; and wherein
the data center controller is configured to provide the application to the server for execution by the server.
21. The system of claim 12, wherein the data center controller is configured to generate a request to add hardware to at least one of the plurality of data centers.
22. The system of claim 12, wherein the data center controller is configured to indicate that the selected data center has excess capacity based at least in part on an evaluation, by the data center controller, of the parameters and the requirements of the device.
23. The system of claim 12, wherein the data center controller is configured to distribute at least a portion of the application to two or more data centers based at least on part on an evaluation, by the data center controller, of the parameters and the requirements of the device.
24. A non-transitory computer readable medium having stored thereon sequences of instructions, the sequences of instructions including instructions, when executed by a processor, that cause the processor to:
identify parameters of a plurality of data centers, each data centincluding a plurality of devices;
identify requirements of a device to run the application, including cooling capacity required to control heat generated during execution of the application, simulated redundancy, and simulated reliability;
detect a failure to execute the aplication of the plurality of data centers;
identify a selected data center from the plurality of data centers as a location to run the application responsive to detecting the failure based at least in part on an evaluation of the parameters and the requirements;
evaluate the parameters and requirements for an underutilization condition of a device of one of the plurality of data centers, including simulated cooling characteristics and simulated power characteristics for each data center of the plurality of data centers, to identify an underutilization condition of a device of one of the plurality of data centers; and
disable the device of one of the plurality of data centers based on the underutilization Condition.
25. The computer readable medium of claim 24, wherein the evaluation of the parameters and the requirements to identify the selected data center includes
an evaluation of at least one of simulated first data center cooling characteristics and simulated first data center power characteristics to determine a first data center capacity of a first data center;
provide information indicating the first data center capacity to a device associated with a second data center; and
receive a request to execute, on a device in the first data center, an application provided by the device associated with the second data center.
26. The computer implemente method of claim 1, comprising:
identifying a reliability level of a first device of the selected data center; and
providing the application to the first device based at least in part on an evaluation of the reliability level.
27. The computer implemented method of claim 26, comprising:
adjusting the reliability level.
receiving an indication that a power failure has occurred in the selected data center; and
reallocating, responsive to the power failure, the application from a first device of the selected data center to a second device of the selected data center.
detecting an application failure that has occurred; and
transferring, responsive to the application failure, the application to a first device at a temporary location of the selected data center.
US12/371,355 2009-02-13 2009-02-13 Data center control Active 2029-04-07 US9519517B2 (en)
US12/371,355 US9519517B2 (en) 2009-02-13 2009-02-13 Data center control
PCT/US2010/022074 WO2010093515A1 (en) 2009-02-13 2010-01-26 Data center control
EP10703552A EP2396726A1 (en) 2009-02-13 2010-01-26 Data center control
AU2010214029A AU2010214029B2 (en) 2009-02-13 2010-01-26 Data center control
CA2752613A CA2752613A1 (en) 2009-02-13 2010-01-26 Data center control
CN201080016515.0A CN102395955B (en) 2009-02-13 2010-01-26 Data center control
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US12/888,053 Continuation-In-Part US8560677B2 (en) 2009-02-13 2010-09-22 Data center control
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