US20120271949A1 - Real-time data analysis for resource provisioning among systems in a networked computing environment - Google Patents
Real-time data analysis for resource provisioning among systems in a networked computing environment Download PDFInfo
- Publication number
- US20120271949A1 US20120271949A1 US13/090,345 US201113090345A US2012271949A1 US 20120271949 A1 US20120271949 A1 US 20120271949A1 US 201113090345 A US201113090345 A US 201113090345A US 2012271949 A1 US2012271949 A1 US 2012271949A1
- Authority
- US
- United States
- Prior art keywords
- service resources
- service
- provisioning
- systems
- pertaining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
- H04L67/61—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources taking into account QoS or priority requirements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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]
- G06F9/5061—Partitioning or combining of resources
Definitions
- the present invention generally relates to service resource provisioning. Specifically, the present invention relates to the intelligent, inter-system provisioning of service resources in a networked computing environment (e.g., a cloud computing environment).
- a networked computing environment e.g., a cloud computing environment
- the cloud computing environment is an enhancement to the predecessor grid environment, whereby multiple grids and other computation resources may be further abstracted by a cloud layer, thus making disparate devices appear to an end-consumer as a single pool of seamless resources.
- These resources may include such things as physical or logical computing engines, servers and devices, device memory, storage devices.
- Embodiments of the present invention provide an approach for intelligent service resource provisioning among distinct systems in a networked computing environment (e.g., a cloud computing environment).
- a networked computing environment e.g., a cloud computing environment.
- the embodiments of the present invention provide an intelligent provisioning engine (hereinafter engine) that accesses a service intelligence repository that comprises configuration information pertaining to a set of service resources available on a set of systems.
- the engine may also receive/identify a set of rules pertaining to any constraints on the set of service resources as well as a set of policies pertaining to provisioning the set of service resources.
- the engine can collect real-time data pertaining to operational characteristics of the set of service resources. Based on the information/data collected, the engine may determine a plan for provisioning the set of service resources and integrate the plan with ancillary systems/engines (e.g., scaling, provisioning, monitoring, etc.) for implementation of the plan.
- ancillary systems/engines e.g., scaling
- a first aspect of the present invention provides a method for provisioning service resources based on real-time data in a networked computing environment, comprising: accessing a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems; identifying a set of rules pertaining to any constraints on the set of service resources; identifying a set of policies pertaining to provisioning the set of service resources; collecting real-time data pertaining to operational characteristics of the set of service resources; and determining a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
- a second aspect of the present invention provides a system for provisioning service resources based on real-time data in a networked computing environment, comprising: a bus; a processor coupled to the bus; and a memory medium coupled to the bus, the memory medium comprising instructions to: access a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems; identify a set of rules pertaining to any constraints on the set of service resources; identify a set of policies pertaining to provisioning the set of service resources; collect real-time data pertaining to operational characteristics of the set of service resources; and determine a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
- a third aspect of the present invention provides a computer program product for provisioning service resources based on real-time data in a networked computing environment, the computer program product comprising a computer readable storage media, and program instructions stored on the computer readable storage media, to: access a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems; identify a set of rules pertaining to any constraints on the set of service resources; identify a set of policies pertaining to provisioning the set of service resources; collect real-time data pertaining to operational characteristics of the set of service resources; and determine a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
- a fourth aspect of the present invention provides a method for deploying a system for provisioning service resources based on real-time data in a networked computing environment, comprising: providing a computer infrastructure being operable to: access a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems; identify a set of rules pertaining to any constraints on the set of service resources; identify a set of policies pertaining to provisioning the set of service resources; collect real-time data pertaining to operational characteristics of the set of service resources; and determine a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
- FIG. 1 depicts a cloud computing node according to an embodiment of the present invention.
- FIG. 2 depicts a cloud computing environment according to an embodiment of the present invention.
- FIG. 3 depicts abstraction model layers according to an embodiment of the present invention.
- FIG. 4 depicts a system diagram according to an embodiment of the present invention.
- FIG. 5 depicts a method flow diagram according to an embodiment of the present invention.
- embodiments of the present invention provide an approach for intelligent service resource provisioning among distinct systems in a networked computing environment (e.g., a cloud computing environment).
- a networked computing environment e.g., a cloud computing environment.
- the embodiments of the present invention provide an intelligent provisioning engine (hereinafter engine) that accesses a service intelligence repository that comprises configuration information pertaining to a set of service resources available on a set of systems.
- the engine may also receive/identify a set of rules pertaining to any constraints on the set of service resources as well as a set of policies pertaining to provisioning the set of service resources.
- the engine can collect real-time data pertaining to operational characteristics of the set of service resources. Based on the information/data collected, the engine may determine a plan for provisioning the set of service resources and integrate the plan with ancillary systems/engines (e.g., scaling, provisioning, monitoring, etc.) for implementation of the plan.
- ancillary systems/engines e.g., scaling, provision
- Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service.
- This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.
- On-demand self-service a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed, automatically without requiring human interaction with the service's provider.
- Resource pooling the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter).
- Rapid elasticity capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.
- Measured service cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active consumer accounts). Resource usage can be monitored, controlled, and reported providing transparency for both the provider and consumer of the utilized service.
- level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active consumer accounts).
- SaaS Software as a Service: the capability provided to the consumer is to use the provider's applications running on a cloud infrastructure.
- the applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based email).
- a web browser e.g., web-based email.
- the consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited consumer-specific application configuration settings.
- PaaS Platform as a Service
- the consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application-hosting environment configurations.
- IaaS Infrastructure as a Service
- the consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).
- Private cloud the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises.
- Public cloud the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.
- Hybrid cloud the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).
- a cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability.
- An infrastructure comprising a network of interconnected nodes.
- Cloud computing node 10 is only one example of a suitable cloud computing node and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the invention described herein. Regardless, cloud computing node 10 is capable of being implemented and/or performing any of the functionality set forth hereinabove.
- cloud computing node 10 there is a computer system/server 12 , which is operational with numerous other general purpose or special purpose computing system environments or configurations.
- Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with computer system/server 12 include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices, and the like.
- Computer system/server 12 may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system.
- program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types.
- Computer system/server 12 may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network.
- program modules may be located in both local and remote computer system storage media including memory storage devices.
- computer system/server 12 in cloud computing node 10 is shown in the form of a general-purpose computing device.
- the components of computer system/server 12 may include, but are not limited to, one or more processors or processing units 16 , a system memory 28 , and a bus 18 that couples various system components including system memory 28 to processor 16 .
- Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures.
- bus architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnects (PCI) bus.
- Computer system/server 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server 12 , and it includes both volatile and non-volatile media, removable and non-removable media.
- System memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and/or cache memory 32 .
- Computer system/server 12 may further include other removable/non-removable, volatile/non-volatile computer system storage media.
- storage system 34 can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a “hard drive”).
- a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”).
- an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM, or other optical media can be provided.
- memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
- the embodiments of the invention may be implemented as a computer readable signal medium, which may include a propagated data signal with computer readable program code embodied therein (e.g., in baseband or as part of a carrier wave). Such a propagated signal may take any of a variety of forms including, but not limited to, electro-magnetic, optical, or any suitable combination thereof.
- a computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
- Program code embodied on a computer readable medium may be transmitted using any appropriate medium including, but not limited to, wireless, wireline, optical fiber cable, radio-frequency (RF), etc., or any suitable combination of the foregoing.
- any appropriate medium including, but not limited to, wireless, wireline, optical fiber cable, radio-frequency (RF), etc., or any suitable combination of the foregoing.
- Program/utility 40 having a set (at least one) of program modules 42 , may be stored in memory 28 by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment.
- Program modules 42 generally carry out the functions and/or methodologies of embodiments of the invention as described herein.
- Computer system/server 12 may also communicate with one or more external devices 14 such as a keyboard, a pointing device, a display 24 , etc.; one or more devices that enable a consumer to interact with computer system/server 12 ; and/or any devices (e.g., network card, modem, etc.) that enable computer system/server 12 to communicate with one or more other computing devices. Such communication can occur via I/O interfaces 22 . Still yet, computer system/server 12 can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet) via network adapter 20 . As depicted, network adapter 20 communicates with the other components of computer system/server 12 via bus 18 .
- LAN local area network
- WAN wide area network
- public network e.g., the Internet
- cloud computing environment 50 comprises one or more cloud computing nodes 10 with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone 54 A, desktop computer 54 B, laptop computer 54 C, and/or automobile computer system 54 N may communicate.
- Nodes 10 may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as private, community, public, or hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment 50 to offer infrastructure, platforms, and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device.
- computing devices 54 A-N shown in FIG. 2 are intended to be illustrative only and that computing nodes 10 and cloud computing environment 50 can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser).
- FIG. 3 a set of functional abstraction layers provided by cloud computing environment 50 ( FIG. 2 ) is shown. It should be understood in advance that the components, layers, and functions shown in FIG. 3 are intended to be illustrative only and embodiments of the invention are not limited thereto. As depicted, the following layers and corresponding functions are provided:
- Hardware and software layer 60 includes hardware and software components.
- hardware components include mainframes.
- software components include network application server software.
- IBM WebSphere® application server software and database software In one example, IBM DB2® database software. (IBM, zSeries, pSeries, xSeries, BladeCenter, WebSphere, and DB2 are trademarks of International Business Machines Corporation registered in many jurisdictions worldwide.)
- Virtualization layer 62 provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers; virtual storage; virtual networks, including virtual private networks; virtual applications and operating systems; and virtual clients.
- management layer 64 may provide the functions described below.
- Resource provisioning provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment.
- Metering and pricing provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may comprise application software licenses.
- Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources.
- Consumer portal provides access to the cloud computing environment for consumers and system administrators.
- Service level management provides cloud computing resource allocation and management such that required service levels are met.
- Service Level Agreement (SLA) planning and fulfillment provides pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA.
- SLA Service Level Agreement
- Workloads layer 66 provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation; software development and lifecycle management; virtual classroom education delivery; data analytics processing; transaction processing; and intelligent provisioning. As mentioned above, all of the foregoing examples described with respect to FIG. 3 are illustrative only, and the invention is not limited to these examples.
- the embodiments of the present invention comprise one or more of the following steps:
- service and/or service resource configuration including configuration Items (hardware and software) dedicated for a service/resource, or shared by the service/resource (with other services/resource). This can include the physical location of hardware and/or software resources. This step can further include the identification and/or mapping of any provisioning systems that can automatically provision and allocate physical and/or virtual services/resources (e.g., SAAS, IAAS, PAAS, etc.).
- provisioning systems e.g., SAAS, IAAS, PAAS, etc.
- an intelligent provisioning engine (engine 70 ) (e.g., also represented by one or more modules 42 of program/utility 40 of FIG. 1 ) is provided. As indicated above, engine 70 will access various types of information to intelligently provision service resources 84 (shown in provisioned resource pool 82 ) that may be available among a set of systems 80 (e.g., separate and distinct data centers shown in provisioning tools 78 ).
- provisioned resource pool 82 shown in provisioned resource pool 82
- systems 80 e.g., separate and distinct data centers shown in provisioning tools 78 .
- the embodiments described herein provide an approach for inter-system (e.g., inter-cloud) service resource provisioning.
- engine 70 will access various types and/or sources of information.
- One such source is service intelligence repository 86 from which engine 70 can obtain configuration information pertaining to the set of service resources 84 available on set of systems 80 .
- engine 70 will further receive input in the form of:
- Client specific factors 72 e.g., intelligent risk engine data, intelligent scaling engine data, demand data, historical usage data, and rules for service provisioning;
- Service factors 74 e.g., service continuous integration (CI), service capacity utilization and performance data; service related events; service resource related rules and/or policies, and/or mapping data; and/or
- Resource factors 76 e.g., resource scaling capabilities, resource provisioning capabilities, resource capacity utilization and performance data (e.g., operational characteristics); resource events; and internal bottleneck data.
- multiple types of information/data received by engine 70 are a set of rules pertaining to any constraints on the set of service resources, a set of policies pertaining to provisioning the set of service resources, and real-time data (e.g., streaming analytics) pertaining to operational characteristics of the set of service resources.
- the set of rules can further pertain to at least one of the following: available resource pools, locations from where the set of service resources can be provisioned, a capability for the set of services resources to be automatically provisioned, or a granularity of the set of service resources.
- the set of policies can further pertain to at least one of the following: co-location of the set of service resources, or a set of risk factors.
- the real-time data can further pertain to at least one of the following: service traffic through the set of service resources, monitoring and management systems associated with the set of service resources, or load balancing systems associated with the set of service resources. Shown below are examples of a policies and rules:
- Example 1 for a policy Allocation of resources should align resource tiers (and associated resource pool) to service tier (service level tier).
- Example 2 for a policy A bank customer's account information, particularly customer personal data such as social security number, address, contact information, name, family information, etc. should only be stored in the storage clouds located within the geographic region “A”.
- Example 1 for a rule High end or premium storage pools (e.g., using higher cost, high performance, and/or highly resilient storage resources) should only be used for allocating storage resources to Tier “X” services (e.g., that have very stringent SLAs and severe penalties for breaching SLAs).
- Tier “X” services e.g., that have very stringent SLAs and severe penalties for breaching SLAs.
- Example 2 for a rule Provisioning of any database or file system (physical or virtual) which contains or may contain customer sensitive private information including social security number should only be stored in enterprise storage private cloud A, B and C (e.g., all of which are located within geographic region “A”).
- engine 70 will perform an analysis (e.g., statistical) to develop/determine/generate a plan to intelligently provision the set of service resources 84 between set of systems 80 .
- engine 70 will make various decisions/determinations (e.g., the number of units to provision, the timing and frequency thereof, etc.).
- engine 70 can integrate the plan with at least one scaling engine and/or at least one resource provisioning tool for implementation.
- the plan can be generated so that the rules, policies, and any applicable service level agreement (SLA) terms are followed appropriately, while providing the most efficient and effective use of service resources.
- engine 70 can include a rules engine or the like that can apply rules, policies and real-time data. As such, one or more of the following items can result from the rules engine:
- a plan e.g., a document, and XML file, etc.
- a plan e.g., a document, and XML file, etc.
- CI Virtual Server or Virtual Machine (VM).
- Provisioning Tool Version Version 1.2.
- Provisioning Server Name Acme_VMWare_Prov_HostA and HostB. (backup to A)
- Resource-Image File Source (Host Name and Source Directory): Image Management System A: IMSA:/image/production_images/.
- Provisioning and Allocation Script for VMware VM located in the administrative home directory of the Provisioning Server.
- Post Provisioning Procedure Script to allocate and assign new instance of VM to the current service (ecommerce presentation services in this case) located in the administrative home directory of the provisioning server.
- Provisioning Engine Production-Provisioning-EngineA.
- Source of xml file Production-Provisioning-EngineA.
- Target of xml file Acme_VMWare_Prov_HostA and HostB.
- Time to Provision Scheduled via Cron (daily provisioning job which runs during provisioning window—off peak hours).
- Notification time one hour and one minute before and after provisioning and allocation.
- a service intelligence repository is accessed.
- the service intelligence repository comprises configuration information pertaining to a set of service resources available on a set of systems.
- a set of rules pertaining to any constraints on the set of service resources is identified.
- a set of policies pertaining to provisioning the set of service resources is identified.
- real-time data pertaining to operational characteristics of the set of service resources is collected.
- a plan for provisioning the set of service resources between the set of systems is determined. As indicated above, the plan is typically generated based upon the set of rules, the set of policies, and the real-time data. Moreover, the plan will be integrated with at least one scaling engine and/or at least one resource provisioning tool for implementation.
- the invention provides a computer-readable/useable medium that includes computer program code to enable a computer infrastructure to provide intelligent provisioning functionality as discussed herein.
- the computer-readable/useable medium includes program code that implements each of the various processes of the invention. It is understood that the terms computer-readable medium or computer-useable medium comprise one or more of any type of physical embodiment of the program code.
- the computer-readable/useable medium can comprise program code embodied on one or more portable storage articles of manufacture (e.g., a compact disc, a magnetic disk, a tape, etc.), on one or more data storage portions of a computing device, such as memory 28 ( FIG. 1 ) and/or storage system 34 (FIG. 1 ) (e.g., a fixed disk, a read-only memory, a random access memory, a cache memory, etc.).
- portable storage articles of manufacture e.g., a compact disc, a magnetic disk, a tape, etc.
- data storage portions of a computing device such as memory 28 ( FIG. 1 ) and/or storage system 34 (FIG. 1 ) (e.g., a fixed disk, a read-only memory, a random access memory, a cache memory, etc.).
- the invention provides a method that performs the process of the invention on a subscription, advertising, and/or fee basis. That is, a service provider, such as a Solution Integrator, could offer to provide intelligent provisioning functionality.
- the service provider can create, maintain, support, etc., a computer infrastructure, such as computer system 12 ( FIG. 1 ) that performs the processes of the invention for one or more consumers.
- the service provider can receive payment from the consumer(s) under a subscription and/or fee agreement and/or the service provider can receive payment from the sale of advertising content to one or more third parties.
- the invention provides a computer-implemented method for intelligent provisioning.
- a computer infrastructure such as computer system 12 ( FIG. 1 )
- one or more systems for performing the processes of the invention can be obtained (e.g., created, purchased, used, modified, etc.) and deployed to the computer infrastructure.
- the deployment of a system can comprise one or more of: (1) installing program code on a computing device, such as computer system 12 ( FIG. 1 ), from a computer-readable medium; (2) adding one or more computing devices to the computer infrastructure; and (3) incorporating and/or modifying one or more existing systems of the computer infrastructure to enable the computer infrastructure to perform the processes of the invention.
- program code and “computer program code” are synonymous and mean any expression, in any language, code, or notation, of a set of instructions intended to cause a computing device having an information processing capability to perform a particular function either directly or after either or both of the following: (a) conversion to another language, code, or notation; and/or (b) reproduction in a different material form.
- program code can be embodied as one or more of: an application/software program, component software/a library of functions, an operating system, a basic device system/driver for a particular computing device, and the like.
- a data processing system suitable for storing and/or executing program code can be provided hereunder and can include at least one processor communicatively coupled, directly or indirectly, to memory elements through a system bus.
- the memory elements can include, but are not limited to, local memory employed during actual execution of the program code, bulk storage, and cache memories that provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during execution.
- Input/output and/or other external devices can be coupled to the system either directly or through intervening device controllers.
- Network adapters also may be coupled to the system to enable the data processing system to become coupled to other data processing systems, remote printers, storage devices, and/or the like, through any combination of intervening private or public networks.
- Illustrative network adapters include, but are not limited to, modems, cable modems, and Ethernet cards.
Abstract
Embodiments of the present invention provide an approach for intelligent service resource provisioning among distinct systems in a networked computing environment (e.g., a cloud computing environment). Specifically, the embodiments of the present invention provide an intelligent provisioning engine (hereinafter engine) that accesses a service intelligence repository that comprises configuration information pertaining to a set of service resources available on a set of systems. The engine may also receive/identify a set of rules pertaining to any constraints on the set of service resources as well as a set of policies pertaining to provisioning the set of service resources. Still yet, the engine can collect real-time data pertaining to operational characteristics of the set of service resources. Based on the information/data collected, the engine may determine a plan for provisioning the set of service resources and integrate the plan with ancillary systems/engines (e.g., scaling, provisioning, monitoring, etc.) for implementation of the plan.
Description
- The present invention generally relates to service resource provisioning. Specifically, the present invention relates to the intelligent, inter-system provisioning of service resources in a networked computing environment (e.g., a cloud computing environment).
- The cloud computing environment is an enhancement to the predecessor grid environment, whereby multiple grids and other computation resources may be further abstracted by a cloud layer, thus making disparate devices appear to an end-consumer as a single pool of seamless resources. These resources may include such things as physical or logical computing engines, servers and devices, device memory, storage devices.
- As enterprises develop their information technology (IT) strategy, and as technologies evolve to enable location of services in a multi-data center configuration, there is a need for inter-data center and inter-cloud provisioning capabilities. However, challenges exist with respect to making inter-system data and policy-driven decisions to take provisioning actions.
- Embodiments of the present invention provide an approach for intelligent service resource provisioning among distinct systems in a networked computing environment (e.g., a cloud computing environment). Specifically, the embodiments of the present invention provide an intelligent provisioning engine (hereinafter engine) that accesses a service intelligence repository that comprises configuration information pertaining to a set of service resources available on a set of systems. The engine may also receive/identify a set of rules pertaining to any constraints on the set of service resources as well as a set of policies pertaining to provisioning the set of service resources. Still yet, the engine can collect real-time data pertaining to operational characteristics of the set of service resources. Based on the information/data collected, the engine may determine a plan for provisioning the set of service resources and integrate the plan with ancillary systems/engines (e.g., scaling, provisioning, monitoring, etc.) for implementation of the plan.
- A first aspect of the present invention provides a method for provisioning service resources based on real-time data in a networked computing environment, comprising: accessing a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems; identifying a set of rules pertaining to any constraints on the set of service resources; identifying a set of policies pertaining to provisioning the set of service resources; collecting real-time data pertaining to operational characteristics of the set of service resources; and determining a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
- A second aspect of the present invention provides a system for provisioning service resources based on real-time data in a networked computing environment, comprising: a bus; a processor coupled to the bus; and a memory medium coupled to the bus, the memory medium comprising instructions to: access a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems; identify a set of rules pertaining to any constraints on the set of service resources; identify a set of policies pertaining to provisioning the set of service resources; collect real-time data pertaining to operational characteristics of the set of service resources; and determine a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
- A third aspect of the present invention provides a computer program product for provisioning service resources based on real-time data in a networked computing environment, the computer program product comprising a computer readable storage media, and program instructions stored on the computer readable storage media, to: access a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems; identify a set of rules pertaining to any constraints on the set of service resources; identify a set of policies pertaining to provisioning the set of service resources; collect real-time data pertaining to operational characteristics of the set of service resources; and determine a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
- A fourth aspect of the present invention provides a method for deploying a system for provisioning service resources based on real-time data in a networked computing environment, comprising: providing a computer infrastructure being operable to: access a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems; identify a set of rules pertaining to any constraints on the set of service resources; identify a set of policies pertaining to provisioning the set of service resources; collect real-time data pertaining to operational characteristics of the set of service resources; and determine a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
- These and other features of this invention will be more readily understood from the following detailed description of the various aspects of the invention taken in conjunction with the accompanying drawings in which:
-
FIG. 1 depicts a cloud computing node according to an embodiment of the present invention. -
FIG. 2 depicts a cloud computing environment according to an embodiment of the present invention. -
FIG. 3 depicts abstraction model layers according to an embodiment of the present invention. -
FIG. 4 depicts a system diagram according to an embodiment of the present invention. -
FIG. 5 depicts a method flow diagram according to an embodiment of the present invention. - The drawings are not necessarily to scale. The drawings are merely schematic representations, not intended to portray specific parameters of the invention. The drawings are intended to depict only typical embodiments of the invention, and therefore should not be considered as limiting the scope of the invention. In the drawings, like numbering represents like elements.
- Illustrative embodiments now will be described more fully herein with reference to the accompanying drawings, in which exemplary embodiments are shown. This disclosure may, however, be embodied in many different forms and should not be construed as limited to the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete and will fully convey the scope of this disclosure to those skilled in the art. In the description, details of well-known features and techniques may be omitted to avoid unnecessarily obscuring the presented embodiments. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of this disclosure. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, the use of the terms “a”, “an”, etc., do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced items. It will be further understood that the terms “comprises” and/or “comprising”, or “includes” and/or “including”, when used in this specification, specify the presence of stated features, regions, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, regions, integers, steps, operations, elements, components, and/or groups thereof.
- As indicated above, embodiments of the present invention provide an approach for intelligent service resource provisioning among distinct systems in a networked computing environment (e.g., a cloud computing environment). Specifically, the embodiments of the present invention provide an intelligent provisioning engine (hereinafter engine) that accesses a service intelligence repository that comprises configuration information pertaining to a set of service resources available on a set of systems. The engine may also receive/identify a set of rules pertaining to any constraints on the set of service resources as well as a set of policies pertaining to provisioning the set of service resources. Still yet, the engine can collect real-time data pertaining to operational characteristics of the set of service resources. Based on the information/data collected, the engine may determine a plan for provisioning the set of service resources and integrate the plan with ancillary systems/engines (e.g., scaling, provisioning, monitoring, etc.) for implementation of the plan.
- It is understood in advance that although this disclosure includes a detailed description of cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present invention are capable of being implemented in conjunction with any other type of computing environment now known or later developed.
- Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models.
- Characteristics are as follows:
- On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed, automatically without requiring human interaction with the service's provider.
- Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs).
- Resource pooling: the provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter).
- Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time.
- Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active consumer accounts). Resource usage can be monitored, controlled, and reported providing transparency for both the provider and consumer of the utilized service.
- Service Models are as follows:
- Software as a Service (SaaS): the capability provided to the consumer is to use the provider's applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based email). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited consumer-specific application configuration settings.
- Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application-hosting environment configurations.
- Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls).
- Deployment Models are as follows:
- Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises.
- Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises.
- Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.
- Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).
- A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure comprising a network of interconnected nodes.
- Referring now to
FIG. 1 , a schematic of an example of a cloud computing node is shown.Cloud computing node 10 is only one example of a suitable cloud computing node and is not intended to suggest any limitation as to the scope of use or functionality of embodiments of the invention described herein. Regardless,cloud computing node 10 is capable of being implemented and/or performing any of the functionality set forth hereinabove. - In
cloud computing node 10, there is a computer system/server 12, which is operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations that may be suitable for use with computer system/server 12 include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices, and the like. - Computer system/
server 12 may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Computer system/server 12 may be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media including memory storage devices. - As shown in
FIG. 1 , computer system/server 12 incloud computing node 10 is shown in the form of a general-purpose computing device. The components of computer system/server 12 may include, but are not limited to, one or more processors orprocessing units 16, asystem memory 28, and abus 18 that couples various system components includingsystem memory 28 toprocessor 16. -
Bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnects (PCI) bus. - Computer system/
server 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server 12, and it includes both volatile and non-volatile media, removable and non-removable media. -
System memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and/orcache memory 32. Computer system/server 12 may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only,storage system 34 can be provided for reading from and writing to a non-removable, non-volatile magnetic media (not shown and typically called a “hard drive”). Although not shown, a magnetic disk drive for reading from and writing to a removable, non-volatile magnetic disk (e.g., a “floppy disk”), and an optical disk drive for reading from or writing to a removable, non-volatile optical disk such as a CD-ROM, DVD-ROM, or other optical media can be provided. In such instances, each can be connected tobus 18 by one or more data media interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention. - The embodiments of the invention may be implemented as a computer readable signal medium, which may include a propagated data signal with computer readable program code embodied therein (e.g., in baseband or as part of a carrier wave). Such a propagated signal may take any of a variety of forms including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
- Program code embodied on a computer readable medium may be transmitted using any appropriate medium including, but not limited to, wireless, wireline, optical fiber cable, radio-frequency (RF), etc., or any suitable combination of the foregoing.
- Program/
utility 40, having a set (at least one) ofprogram modules 42, may be stored inmemory 28 by way of example, and not limitation, as well as an operating system, one or more application programs, other program modules, and program data. Each of the operating system, one or more application programs, other program modules, and program data or some combination thereof, may include an implementation of a networking environment.Program modules 42 generally carry out the functions and/or methodologies of embodiments of the invention as described herein. - Computer system/
server 12 may also communicate with one or moreexternal devices 14 such as a keyboard, a pointing device, adisplay 24, etc.; one or more devices that enable a consumer to interact with computer system/server 12; and/or any devices (e.g., network card, modem, etc.) that enable computer system/server 12 to communicate with one or more other computing devices. Such communication can occur via I/O interfaces 22. Still yet, computer system/server 12 can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and/or a public network (e.g., the Internet) vianetwork adapter 20. As depicted,network adapter 20 communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardware and/or software components could be used in conjunction with computer system/server 12. Examples include, but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc. - Referring now to
FIG. 2 , illustrativecloud computing environment 50 is depicted. As shown,cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone 54A,desktop computer 54B,laptop computer 54C, and/orautomobile computer system 54N may communicate.Nodes 10 may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as private, community, public, or hybrid clouds as described hereinabove, or a combination thereof. This allowscloud computing environment 50 to offer infrastructure, platforms, and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices 54A-N shown inFIG. 2 are intended to be illustrative only and thatcomputing nodes 10 andcloud computing environment 50 can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser). - Referring now to
FIG. 3 , a set of functional abstraction layers provided by cloud computing environment 50 (FIG. 2 ) is shown. It should be understood in advance that the components, layers, and functions shown inFIG. 3 are intended to be illustrative only and embodiments of the invention are not limited thereto. As depicted, the following layers and corresponding functions are provided: - Hardware and
software layer 60 includes hardware and software components. Examples of hardware components include mainframes. In one example, IBM® zSeries® systems and RISC (Reduced Instruction Set Computer) architecture based servers. In one example, IBM pSeries® systems, IBM xSeries® systems, IBM BladeCenter® systems, storage devices, networks, and networking components. Examples of software components include network application server software. In one example, IBM WebSphere® application server software and database software. In one example, IBM DB2® database software. (IBM, zSeries, pSeries, xSeries, BladeCenter, WebSphere, and DB2 are trademarks of International Business Machines Corporation registered in many jurisdictions worldwide.) -
Virtualization layer 62 provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers; virtual storage; virtual networks, including virtual private networks; virtual applications and operating systems; and virtual clients. - In one example,
management layer 64 may provide the functions described below. Resource provisioning provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and pricing provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may comprise application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. Consumer portal provides access to the cloud computing environment for consumers and system administrators. Service level management provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment provides pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA. -
Workloads layer 66 provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation; software development and lifecycle management; virtual classroom education delivery; data analytics processing; transaction processing; and intelligent provisioning. As mentioned above, all of the foregoing examples described with respect toFIG. 3 are illustrative only, and the invention is not limited to these examples. - It is understood all that functions of the present invention as described herein typically may be performed by the intelligent provisioning functionality, which can be tangibly embodied as modules of
program code 42 of program/utility 40 (FIG. 1 ). However, this need not be the case. Rather, the functionality recited herein could be carried out/implemented and/or enabled by any of the layers 60-66 shown inFIG. 3 . - It is reiterated that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, the embodiments of the present invention are intended to be implemented with any type of networked computing environment now known or later developed.
- In general, the embodiments of the present invention comprise one or more of the following steps:
- 1. Development of and/or access to a service intelligence repository that has data pertaining to: service and/or service resource configuration including configuration Items (hardware and software) dedicated for a service/resource, or shared by the service/resource (with other services/resource). This can include the physical location of hardware and/or software resources. This step can further include the identification and/or mapping of any provisioning systems that can automatically provision and allocate physical and/or virtual services/resources (e.g., SAAS, IAAS, PAAS, etc.).
- 2. Identify and develop rules pertaining to constraints associated with services, service components, and service resource provisioning such as:
-
- Service and service component related constraints such as compatibility constraints (e.g., only certain vendor resources and resource version levels are compatible with the service and other service components);
- Resource pools that can be used;
- Locations from where service components and service resources can be provisioned;
- Manual versus automated provisioning;
- Thin versus thick provisioning (granularity of resource units); and/or
- Allocation related constraints.
- 3. Identify and develop rules pertaining to policies associated with resource provisioning such as:
-
- Rules associated with co-location of service resources (e.g., whether storage systems containing database (DB) tables and associated DB servers need to be physically co-located);
- Rules determining whether web server and web-caching systems need to be located close to where the end users are located; and/or
- Rules associated with provisioning due to risk factors (e.g., capital resource availability, disaster recovery (DR) considerations, etc.).
- 4. Collect real-time data about operational characteristics (e.g., service traffic) and other service resource provisioning related information from:
-
- End-to-end service monitoring and management systems (including capacity/utilization and performance monitoring tools, availability monitoring tools, etc.);
- Load balancing systems (such as Internet protocol (IP) load balancers); and/or
- Intelligent risk engine(s) (e.g., about risk data associated with potential DR scenarios).
- 5. Develop/determine a plan for provisioning the set of service resources between the set of systems based on the collected information.
- 6. Integrate the plan with intelligent scaling engine(s) to check if the resource can be scaled up or down if necessary (e.g., vertical scaling of service component or service resources before provisioning and allocating additional resources).
- 7. Integrate the plan with individual (e.g., resource specific) provisioning tools (e.g., service and service resource provisioning tools).
- 8. Make determinations based on the plan and its input such as:
-
- Real time service demand and utilization data;
- Service demand and utilization data patterns and trends;
- End user location(s);
- Service component and service resource locations;
- Service and resource provisioning constraints; and/or
- Service and resource provisioning policies (e.g., policies can come from a capacity management system such as an IT process with provisioning and allocation operations such as sub-processes or related IT process domains).
- 9. Implement/take specific action(s) on these determinations (e.g., the plan) via remote commands to individual provisioning tools located at each data center or directly interfacing with the resource/resource pools at different data centers.
- Referring now to
FIG. 4 , a system diagram according to an embodiment of the present invention is shown. As depicted, an intelligent provisioning engine (engine 70) (e.g., also represented by one ormore modules 42 of program/utility 40 ofFIG. 1 ) is provided. As indicated above,engine 70 will access various types of information to intelligently provision service resources 84 (shown in provisioned resource pool 82) that may be available among a set of systems 80 (e.g., separate and distinct data centers shown in provisioning tools 78). Thus, the embodiments described herein provide an approach for inter-system (e.g., inter-cloud) service resource provisioning. - As shown,
engine 70 will access various types and/or sources of information. One such source isservice intelligence repository 86 from whichengine 70 can obtain configuration information pertaining to the set of service resources 84 available on set ofsystems 80. As further shown,engine 70 will further receive input in the form of: - Client specific factors 72 (e.g., intelligent risk engine data, intelligent scaling engine data, demand data, historical usage data, and rules for service provisioning;
- Service factors 74 (e.g., service continuous integration (CI), service capacity utilization and performance data; service related events; service resource related rules and/or policies, and/or mapping data); and/or
- Resource factors 76 (e.g., resource scaling capabilities, resource provisioning capabilities, resource capacity utilization and performance data (e.g., operational characteristics); resource events; and internal bottleneck data.
- As indicated, multiple types of information/data received by
engine 70 are a set of rules pertaining to any constraints on the set of service resources, a set of policies pertaining to provisioning the set of service resources, and real-time data (e.g., streaming analytics) pertaining to operational characteristics of the set of service resources. Under embodiments of the present invention, the set of rules can further pertain to at least one of the following: available resource pools, locations from where the set of service resources can be provisioned, a capability for the set of services resources to be automatically provisioned, or a granularity of the set of service resources. Moreover, the set of policies can further pertain to at least one of the following: co-location of the set of service resources, or a set of risk factors. Still yet, the real-time data can further pertain to at least one of the following: service traffic through the set of service resources, monitoring and management systems associated with the set of service resources, or load balancing systems associated with the set of service resources. Shown below are examples of a policies and rules: - Example 1 for a policy: Allocation of resources should align resource tiers (and associated resource pool) to service tier (service level tier).
- Example 2 for a policy: A bank customer's account information, particularly customer personal data such as social security number, address, contact information, name, family information, etc. should only be stored in the storage clouds located within the geographic region “A”.
- Example 1 for a rule: High end or premium storage pools (e.g., using higher cost, high performance, and/or highly resilient storage resources) should only be used for allocating storage resources to Tier “X” services (e.g., that have very stringent SLAs and severe penalties for breaching SLAs).
- Example 2 for a rule: Provisioning of any database or file system (physical or virtual) which contains or may contain customer sensitive private information including social security number should only be stored in enterprise storage private cloud A, B and C (e.g., all of which are located within geographic region “A”).
- Based on the information collected,
engine 70 will perform an analysis (e.g., statistical) to develop/determine/generate a plan to intelligently provision the set of service resources 84 between set ofsystems 80. In developing the plan,engine 70 will make various decisions/determinations (e.g., the number of units to provision, the timing and frequency thereof, etc.). Moreover,engine 70 can integrate the plan with at least one scaling engine and/or at least one resource provisioning tool for implementation. In general, the plan can be generated so that the rules, policies, and any applicable service level agreement (SLA) terms are followed appropriately, while providing the most efficient and effective use of service resources. Along these lines,engine 70 can include a rules engine or the like that can apply rules, policies and real-time data. As such, one or more of the following items can result from the rules engine: - (A) A plan (e.g., a document, and XML file, etc.) that can be reviewed, approved and implemented manually;
- (B) A plan that can be approved and implemented automatically (i.e., pre-approved—similar to pre-approved changes via interfacing with provisioning tools); and/or
- (C) A combination of manual and automated actions (e.g., manual review and approval with automated implementation).
- Shown below is an illustrating template for a provisioning and allocation plan according to an embodiment of the present invention:
- Resource (Configuration Item) Class: Server.
- Resource (CI) Type: Virtual Server or Virtual Machine (VM).
- Resource (CI) Vendor: VMware (example).
- Resource Pool Name: Ecommerce Production Pool E (example).
- Resource Provisioning Tool Vendor: Acme.
- Resource Provisioning Tool: Acme Data Center.
- Provisioning Tool Version: Version 1.2.
- Provisioning Server Name: Acme_VMWare_Prov_HostA and HostB. (backup to A)
- Service to which Resource being allocated to: Ecommerce Presentation Service.
- Reason for provisioning and allocation: Performance (one of many choices).
- Resource Configuration Data Source: Production Instance A.
- Resource Configuration File Location: Directory and File name in CMDB.
- Resource-Image File Name: EComm-Production-PoolE.vmdk (Example of vmdk file).
- Resource-Image File Source (Host Name and Source Directory): Image Management System A: IMSA:/image/production_images/.
- Method to Use Image and Configuration File: Provisioning and Allocation Script for VMware VM located in the administrative home directory of the Provisioning Server.
- Post Provisioning Procedure: Script to allocate and assign new instance of VM to the current service (ecommerce presentation services in this case) located in the administrative home directory of the provisioning server.
- Provisioning Engine: Production-Provisioning-EngineA.
- XML file from Provisioning Engine (with this data): VMware_Prov.xml.
- Source of xml file: Production-Provisioning-EngineA.
- Target of xml file: Acme_VMWare_Prov_HostA and HostB.
- Time to Provision: Scheduled via Cron (daily provisioning job which runs during provisioning window—off peak hours).
- Exception for Window: Yes or No (Rule for immediate provisioning i.e., do not wait for the next window).
- Notification to: VMware_admin (alias).
- Notification time: one hour and one minute before and after provisioning and allocation.
- Referring now to
FIG. 5 , a method flow diagram according to embodiments of the present invention is shown. In step S1, a service intelligence repository is accessed. In general, the service intelligence repository comprises configuration information pertaining to a set of service resources available on a set of systems. In step S2, a set of rules pertaining to any constraints on the set of service resources is identified. In step S3, a set of policies pertaining to provisioning the set of service resources is identified. In step S4, real-time data pertaining to operational characteristics of the set of service resources is collected. In step S5, a plan for provisioning the set of service resources between the set of systems is determined. As indicated above, the plan is typically generated based upon the set of rules, the set of policies, and the real-time data. Moreover, the plan will be integrated with at least one scaling engine and/or at least one resource provisioning tool for implementation. - While shown and described herein as an intelligent provisioning solution, it is understood that the invention further provides various alternative embodiments. For example, in one embodiment, the invention provides a computer-readable/useable medium that includes computer program code to enable a computer infrastructure to provide intelligent provisioning functionality as discussed herein. To this extent, the computer-readable/useable medium includes program code that implements each of the various processes of the invention. It is understood that the terms computer-readable medium or computer-useable medium comprise one or more of any type of physical embodiment of the program code. In particular, the computer-readable/useable medium can comprise program code embodied on one or more portable storage articles of manufacture (e.g., a compact disc, a magnetic disk, a tape, etc.), on one or more data storage portions of a computing device, such as memory 28 (
FIG. 1 ) and/or storage system 34 (FIG. 1) (e.g., a fixed disk, a read-only memory, a random access memory, a cache memory, etc.). - In another embodiment, the invention provides a method that performs the process of the invention on a subscription, advertising, and/or fee basis. That is, a service provider, such as a Solution Integrator, could offer to provide intelligent provisioning functionality. In this case, the service provider can create, maintain, support, etc., a computer infrastructure, such as computer system 12 (
FIG. 1 ) that performs the processes of the invention for one or more consumers. In return, the service provider can receive payment from the consumer(s) under a subscription and/or fee agreement and/or the service provider can receive payment from the sale of advertising content to one or more third parties. - In still another embodiment, the invention provides a computer-implemented method for intelligent provisioning. In this case, a computer infrastructure, such as computer system 12 (
FIG. 1 ), can be provided and one or more systems for performing the processes of the invention can be obtained (e.g., created, purchased, used, modified, etc.) and deployed to the computer infrastructure. To this extent, the deployment of a system can comprise one or more of: (1) installing program code on a computing device, such as computer system 12 (FIG. 1 ), from a computer-readable medium; (2) adding one or more computing devices to the computer infrastructure; and (3) incorporating and/or modifying one or more existing systems of the computer infrastructure to enable the computer infrastructure to perform the processes of the invention. - As used herein, it is understood that the terms “program code” and “computer program code” are synonymous and mean any expression, in any language, code, or notation, of a set of instructions intended to cause a computing device having an information processing capability to perform a particular function either directly or after either or both of the following: (a) conversion to another language, code, or notation; and/or (b) reproduction in a different material form. To this extent, program code can be embodied as one or more of: an application/software program, component software/a library of functions, an operating system, a basic device system/driver for a particular computing device, and the like.
- A data processing system suitable for storing and/or executing program code can be provided hereunder and can include at least one processor communicatively coupled, directly or indirectly, to memory elements through a system bus. The memory elements can include, but are not limited to, local memory employed during actual execution of the program code, bulk storage, and cache memories that provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during execution. Input/output and/or other external devices (including, but not limited to, keyboards, displays, pointing devices, etc.) can be coupled to the system either directly or through intervening device controllers.
- Network adapters also may be coupled to the system to enable the data processing system to become coupled to other data processing systems, remote printers, storage devices, and/or the like, through any combination of intervening private or public networks. Illustrative network adapters include, but are not limited to, modems, cable modems, and Ethernet cards.
- The foregoing description of various aspects of the invention has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed and, obviously, many modifications and variations are possible. Such modifications and variations that may be apparent to a person skilled in the art are intended to be included within the scope of the invention as defined by the accompanying claims.
Claims (25)
1. A method for provisioning service resources based on real-time data in a networked computing environment, comprising:
accessing a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems;
identifying a set of rules pertaining to any constraints on the set of service resources;
identifying a set of policies pertaining to provisioning the set of service resources;
collecting real-time data pertaining to operational characteristics of the set of service resources; and
determining a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
2. The method of claim 1 , the set of systems comprising a plurality of systems, and the plan comprising a plan for provisioning the set of service resources among the plurality of systems.
3. The method of claim 1 , the service intelligence repository further comprising a map of the set of service resources.
4. The method of claim 1 , the set of rules further pertaining to at least one of the following: available resource pools, locations from where the set of service resources can be provisioned, a capability for the set of services resources to be automatically provisioned, or a granularity of the set of service resources.
5. The method of claim 1 , the set of policies further pertaining to at least one of the following: co-location of the set of service resources, or a set of risk factors.
6. The method of claim 1 , the real-time data further pertaining to at least one of the following: service traffic through the set of service resources, monitoring and management systems associated with the set of service resources, or load balancing systems associated with the set of service resources.
7. The method of claim 1 , further comprising:
integrating the plan with at least one scaling engine; and
integrating the plan with at least one resource provisioning tool.
8. The method of claim 7 , further comprising implementing the plan to provision the set of service resources among the set of systems using the at least one scaling engine and the at least one resource provisioning tool.
9. A system for provisioning service resources based on real-time data in a networked computing environment, comprising:
a bus;
a processor coupled to the bus; and
a memory medium coupled to the bus, the memory medium comprising instructions to:
access a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems;
identify a set of rules pertaining to any constraints on the set of service resources;
identify a set of policies pertaining to provisioning the set of service resources;
collect real-time data pertaining to operational characteristics of the set of service resources; and
determine a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
10. The system of claim 9 , the set of systems comprising a plurality of systems, and the plan comprising a plan for provisioning the set of service resources among the plurality of systems.
11. The system of claim 9 , the service intelligence repository further comprising a map of the set of service resources.
12. The system of claim 9 , the set of rules further pertaining to at least one of the following: available resource pools, locations from where the set of service resources can be provisioned, a capability for the set of service resources to be automatically provisioned, or a granularity of the set of service resources.
13. The system of claim 9 , the set of policies further pertaining to at least one of the following: co-location of the set of service resources, or a set of risk factors.
14. The system of claim 9 , the real-time data further pertaining to at least one of the following: service traffic through the set of service resources, monitoring and management systems associated with the set of service resources, or load balancing systems associated with the set of service resources.
15. The system of claim 9 , the memory medium further comprising instructions to:
integrate the plan with at least one scaling engine; and
integrate the plan with at least one resource provisioning tool.
16. The system of claim 15 , the memory medium further comprising instructions to implement the plan to provision the set of service resources among the set of systems using the at least one scaling engine and the at least one resource provisioning tool.
17. A computer program product for provisioning service resources based on real-time data in a networked computing environment, the computer program product comprising a computer readable storage media, and program instructions stored on the computer readable storage media, to:
access a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems;
identify a set of rules pertaining to any constraints on the set of service resources;
identify a set of policies pertaining to provisioning the set of service resources;
collect real-time data pertaining to operational characteristics of the set of service resources; and
determine a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
18. The computer program product of claim 17 , the set of systems comprising a plurality of systems, and the plan comprising a plan for provisioning the set of service resources among the plurality of systems.
19. The computer program product of claim 17 , the service intelligence repository further comprising a map of the set of service resources.
20. The computer program product of claim 17 , the set of rules further pertaining to at least one of the following: available resource pools, locations from where the set of service resources can be provisioned, a capability for the set of services resources to be automatically provisioned, or a granularity of the set of service resources.
21. The computer program product of claim 17 , the set of policies further pertaining to at least one of the following: co-location of the set of service resources, or a set of risk factors.
22. The computer program product of claim 17 , the real-time data further pertaining to at least one of the following: service traffic through the set of service resources, monitoring and management systems associated with the set of service resources, or load balancing systems associated with the set of service resources.
23. The computer program product of claim 17 , further comprising program instructions stored on the computer readable storage media to:
integrate the plan with at least one scaling engine; and
integrate the plan with at least one resource provisioning tool.
24. The computer program product of claim 23 , further comprising program instructions stored on the at least one computer readable storage media to provision the set of service resources among the set of systems using the at least one scaling engine and the at least one resource provisioning tool.
25. A method for deploying a system for provisioning service resources based on real-time data in a networked computing environment, comprising:
providing a computer infrastructure being operable to:
access a service intelligence repository, the service intelligence repository comprising configuration information pertaining to a set of service resources available on a set of systems;
identify a set of rules pertaining to any constraints on the set of service resources;
identify a set of policies pertaining to provisioning the set of service resources;
collect real-time data pertaining to operational characteristics of the set of service resources; and
determine a plan for provisioning the set of service resources between the set of systems, the plan being generated based upon the set of rules, the set of policies, and the real-time data.
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US13/090,345 US20120271949A1 (en) | 2011-04-20 | 2011-04-20 | Real-time data analysis for resource provisioning among systems in a networked computing environment |
US14/215,152 US9503549B2 (en) | 2011-04-20 | 2014-03-17 | Real-time data analysis for resource provisioning among systems in a networked computing environment |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US13/090,345 US20120271949A1 (en) | 2011-04-20 | 2011-04-20 | Real-time data analysis for resource provisioning among systems in a networked computing environment |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US14/215,152 Continuation US9503549B2 (en) | 2011-04-20 | 2014-03-17 | Real-time data analysis for resource provisioning among systems in a networked computing environment |
Publications (1)
Publication Number | Publication Date |
---|---|
US20120271949A1 true US20120271949A1 (en) | 2012-10-25 |
Family
ID=47022135
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/090,345 Abandoned US20120271949A1 (en) | 2011-04-20 | 2011-04-20 | Real-time data analysis for resource provisioning among systems in a networked computing environment |
US14/215,152 Active 2031-12-18 US9503549B2 (en) | 2011-04-20 | 2014-03-17 | Real-time data analysis for resource provisioning among systems in a networked computing environment |
Family Applications After (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US14/215,152 Active 2031-12-18 US9503549B2 (en) | 2011-04-20 | 2014-03-17 | Real-time data analysis for resource provisioning among systems in a networked computing environment |
Country Status (1)
Country | Link |
---|---|
US (2) | US20120271949A1 (en) |
Cited By (41)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140074539A1 (en) * | 2012-09-07 | 2014-03-13 | Oracle International Corporation | Business attribute driven sizing algorithms |
US20140089178A1 (en) * | 2012-09-21 | 2014-03-27 | Gotrust Technology Inc. | Mobile financial transaction system and method |
US20140156518A1 (en) * | 2012-12-04 | 2014-06-05 | Xerox Corporation | Method and systems for sub-allocating computational resources |
WO2014086043A1 (en) * | 2012-12-07 | 2014-06-12 | Hewlett-Packard Development Company, L.P. | Network resource management |
US20150052053A1 (en) * | 2013-08-15 | 2015-02-19 | Mastercard International Incorporated | Internet site authentication with payments authorization data |
US9098617B1 (en) * | 2012-09-27 | 2015-08-04 | Emc Corporation | Data analytics lifecycle automation |
US20150256475A1 (en) * | 2014-03-05 | 2015-09-10 | Wipro Limited | Systems and methods for designing an optimized infrastructure for executing computing processes |
WO2015191119A1 (en) * | 2014-06-11 | 2015-12-17 | Oracle International Corporation | Providing a subscription for a service using an existing subscription |
US9235630B1 (en) | 2013-09-25 | 2016-01-12 | Emc Corporation | Dataset discovery in data analytics |
US9253113B2 (en) | 2012-09-07 | 2016-02-02 | Oracle International Corporation | Customizable model for throttling and prioritizing orders in a cloud environment |
WO2016022908A1 (en) * | 2014-08-08 | 2016-02-11 | Oracle International Corporation | Placement policy-based allocation of computing resources |
US9262493B1 (en) | 2012-12-27 | 2016-02-16 | Emc Corporation | Data analytics lifecycle processes |
US9319269B2 (en) | 2012-09-07 | 2016-04-19 | Oracle International Corporation | Security infrastructure for cloud services |
WO2016102297A1 (en) * | 2014-12-24 | 2016-06-30 | Koninklijke Kpn N.V. | Method for controlling on-demand service provisioning |
US9467355B2 (en) | 2012-09-07 | 2016-10-11 | Oracle International Corporation | Service association model |
US9542400B2 (en) | 2012-09-07 | 2017-01-10 | Oracle International Corporation | Service archive support |
US9621435B2 (en) | 2012-09-07 | 2017-04-11 | Oracle International Corporation | Declarative and extensible model for provisioning of cloud based services |
US9667470B2 (en) | 2012-09-07 | 2017-05-30 | Oracle International Corporation | Failure handling in the execution flow of provisioning operations in a cloud environment |
US9684866B1 (en) | 2013-06-21 | 2017-06-20 | EMC IP Holding Company LLC | Data analytics computing resource provisioning based on computed cost and time parameters for proposed computing resource configurations |
US9749208B2 (en) | 2014-06-30 | 2017-08-29 | Microsoft Technology Licensing, Llc | Integrated global resource allocation and load balancing |
US9800489B1 (en) * | 2014-12-17 | 2017-10-24 | Amazon Technologies, Inc. | Computing system monitor auditing |
EP3143562A4 (en) * | 2014-05-16 | 2017-10-25 | Transvoyant LLC | Computer-implemented systems and methods of analyzing data in an ad-hoc network for predictive decision-making |
CN107563663A (en) * | 2017-09-15 | 2018-01-09 | 重庆智迅云信息技术有限公司 | Enterprise's scene cloud management system based on cloud computing |
US9961017B2 (en) | 2014-08-08 | 2018-05-01 | Oracle International Corporation | Demand policy-based resource management and allocation system |
US9973439B2 (en) * | 2012-03-29 | 2018-05-15 | Infoblox Inc. | Internet protocol address management (IPAM) integration with a plurality of virtualization tiers in the virtual cloud using infrastructure metadata |
US10142174B2 (en) | 2015-08-25 | 2018-11-27 | Oracle International Corporation | Service deployment infrastructure request provisioning |
US10148530B2 (en) | 2012-09-07 | 2018-12-04 | Oracle International Corporation | Rule based subscription cloning |
US10164901B2 (en) | 2014-08-22 | 2018-12-25 | Oracle International Corporation | Intelligent data center selection |
US10235205B2 (en) | 2012-05-24 | 2019-03-19 | Citrix Systems, Inc. | Remote management of distributed datacenters |
US10244403B2 (en) | 2014-05-08 | 2019-03-26 | Nokia Solutions And Networks Oy | Cloud based access network |
US10521746B2 (en) | 2012-09-07 | 2019-12-31 | Oracle International Corporation | Recovery workflow for processing subscription orders in a computing infrastructure system |
US10546040B2 (en) | 2013-06-14 | 2020-01-28 | Microsoft Technology Licensing Llc | System and method for automatic provisioning of companion resources in a web hosting environment |
US10594800B2 (en) * | 2012-04-26 | 2020-03-17 | Hewlett Packard Enterprise Development Lp | Platform runtime abstraction |
US10762230B2 (en) * | 2012-10-12 | 2020-09-01 | Egnyte, Inc. | Systems and methods for facilitating access to private files using a cloud storage system |
US10860965B2 (en) | 2016-07-18 | 2020-12-08 | Transvoyant, Inc. | System and method for tracking assets |
WO2021068763A1 (en) * | 2019-10-09 | 2021-04-15 | 北京金山云网络技术有限公司 | Cloud resource creation method, apparatus, client and server |
US11086667B2 (en) | 2019-06-11 | 2021-08-10 | International Business Machines Corporation | Selective scheduling of cloud maintenance tasks |
US11159446B2 (en) | 2018-10-30 | 2021-10-26 | Red Hat, Inc. | Cloud resource management using externally-sourced data |
US11277727B1 (en) * | 2020-07-17 | 2022-03-15 | Sprint Communications Company L.P. | Internet of Things communication service |
US11316934B2 (en) | 2015-12-28 | 2022-04-26 | Koninklijke Kpn N.V. | Method for providing a service to a user equipment connected to a first operator network via a second operator network |
US11681573B2 (en) | 2017-09-30 | 2023-06-20 | Oracle International Corporation | API registry in a container platform providing property-based API functionality |
Families Citing this family (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
FR3021108B1 (en) * | 2014-05-16 | 2016-05-06 | Thales Sa | METHOD FOR REAL-TIME SERVICE EXECUTION, IN PARTICULAR FLIGHT MANAGEMENT, AND REAL-TIME SYSTEM USING SUCH A METHOD |
US10332018B2 (en) | 2016-03-01 | 2019-06-25 | International Business Machines Corporation | Service level agreement risk analysis with exogenous architecture |
US10270846B2 (en) * | 2016-08-11 | 2019-04-23 | Dell Products L.P. | System and method for monitoring a service-oriented architecture in a load-balanced environment |
US10846070B2 (en) | 2018-07-05 | 2020-11-24 | At&T Intellectual Property I, L.P. | Facilitating cloud native edge computing via behavioral intelligence |
US11080091B2 (en) | 2019-02-05 | 2021-08-03 | Bank Of America Corporation | System for real time provisioning of resources based on condition monitoring |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20090300107A1 (en) * | 2008-05-30 | 2009-12-03 | Kabushiki Kaisha Toshiba | Presence Service Provision System and Server Unit Thereof |
US20100005175A1 (en) * | 1999-11-22 | 2010-01-07 | Akamai Technologies, Inc. | Distributed on-demand computing system |
US20100057833A1 (en) * | 2008-08-29 | 2010-03-04 | Dehaan Michael Paul | Methods and systems for centrally managing multiple provisioning servers |
US20100125664A1 (en) * | 2008-11-14 | 2010-05-20 | Computer Associates Think, Inc. | System, Method, and Software for Integrating Cloud Computing Systems |
US20100262695A1 (en) * | 2009-04-13 | 2010-10-14 | Raytheon Company | System and Method for Allocating Resources in a Distributed Computing System |
US20100293602A1 (en) * | 2009-05-13 | 2010-11-18 | Canon Kabushiki Kaisha | System operating under web environment and method of controlling the same |
US20110066731A1 (en) * | 2008-06-25 | 2011-03-17 | Telefonaktiebolaget L M Ericsson (Publ) | Dynamic Application Server Allocation in an IMS Network |
Family Cites Families (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6880002B2 (en) | 2001-09-05 | 2005-04-12 | Surgient, Inc. | Virtualized logical server cloud providing non-deterministic allocation of logical attributes of logical servers to physical resources |
US7574496B2 (en) | 2001-11-30 | 2009-08-11 | Surgient, Inc. | Virtual server cloud interfacing |
US7072807B2 (en) | 2003-03-06 | 2006-07-04 | Microsoft Corporation | Architecture for distributed computing system and automated design, deployment, and management of distributed applications |
US7516457B2 (en) | 2004-01-30 | 2009-04-07 | International Business Machines Corporation | Componentized automatic provisioning and management of computing environments for computing utilities |
US8429630B2 (en) | 2005-09-15 | 2013-04-23 | Ca, Inc. | Globally distributed utility computing cloud |
US7912955B1 (en) | 2007-04-24 | 2011-03-22 | Hewlett-Packard Development Company, L.P. | Model-based provisioning of resources |
US8238256B2 (en) | 2008-09-08 | 2012-08-07 | Nugent Raymond M | System and method for cloud computing |
US7636764B1 (en) | 2008-09-29 | 2009-12-22 | Gene Fein | Cloud resource usage in data forwarding storage |
US8271974B2 (en) | 2008-10-08 | 2012-09-18 | Kaavo Inc. | Cloud computing lifecycle management for N-tier applications |
US7904540B2 (en) | 2009-03-24 | 2011-03-08 | International Business Machines Corporation | System and method for deploying virtual machines in a computing environment |
US20110047413A1 (en) | 2009-08-20 | 2011-02-24 | Mcgill Robert E | Methods and devices for detecting service failures and maintaining computing services using a resilient intelligent client computer |
-
2011
- 2011-04-20 US US13/090,345 patent/US20120271949A1/en not_active Abandoned
-
2014
- 2014-03-17 US US14/215,152 patent/US9503549B2/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100005175A1 (en) * | 1999-11-22 | 2010-01-07 | Akamai Technologies, Inc. | Distributed on-demand computing system |
US20090300107A1 (en) * | 2008-05-30 | 2009-12-03 | Kabushiki Kaisha Toshiba | Presence Service Provision System and Server Unit Thereof |
US20110066731A1 (en) * | 2008-06-25 | 2011-03-17 | Telefonaktiebolaget L M Ericsson (Publ) | Dynamic Application Server Allocation in an IMS Network |
US20100057833A1 (en) * | 2008-08-29 | 2010-03-04 | Dehaan Michael Paul | Methods and systems for centrally managing multiple provisioning servers |
US20100125664A1 (en) * | 2008-11-14 | 2010-05-20 | Computer Associates Think, Inc. | System, Method, and Software for Integrating Cloud Computing Systems |
US20100262695A1 (en) * | 2009-04-13 | 2010-10-14 | Raytheon Company | System and Method for Allocating Resources in a Distributed Computing System |
US20100293602A1 (en) * | 2009-05-13 | 2010-11-18 | Canon Kabushiki Kaisha | System operating under web environment and method of controlling the same |
Non-Patent Citations (1)
Title |
---|
Doyle, Ronald P., et al. "Model-Based Resource Provisioning in a Web Service Utility." USENIX Symposium on Internet Technologies and Systems. 2003. * |
Cited By (72)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9973439B2 (en) * | 2012-03-29 | 2018-05-15 | Infoblox Inc. | Internet protocol address management (IPAM) integration with a plurality of virtualization tiers in the virtual cloud using infrastructure metadata |
US10594800B2 (en) * | 2012-04-26 | 2020-03-17 | Hewlett Packard Enterprise Development Lp | Platform runtime abstraction |
US10235205B2 (en) | 2012-05-24 | 2019-03-19 | Citrix Systems, Inc. | Remote management of distributed datacenters |
US9619540B2 (en) | 2012-09-07 | 2017-04-11 | Oracle International Corporation | Subscription order generation for cloud services |
US9792338B2 (en) | 2012-09-07 | 2017-10-17 | Oracle International Corporation | Role assignments in a cloud infrastructure |
US10778542B2 (en) | 2012-09-07 | 2020-09-15 | Oracle International Corporation | Rule based subscription cloning |
US9734224B2 (en) | 2012-09-07 | 2017-08-15 | Oracle International Corporation | Data synchronization in a cloud infrastructure |
US10521746B2 (en) | 2012-09-07 | 2019-12-31 | Oracle International Corporation | Recovery workflow for processing subscription orders in a computing infrastructure system |
US9397884B2 (en) | 2012-09-07 | 2016-07-19 | Oracle International Corporation | Workflows for processing cloud services |
US9319269B2 (en) | 2012-09-07 | 2016-04-19 | Oracle International Corporation | Security infrastructure for cloud services |
US9253113B2 (en) | 2012-09-07 | 2016-02-02 | Oracle International Corporation | Customizable model for throttling and prioritizing orders in a cloud environment |
US10212053B2 (en) | 2012-09-07 | 2019-02-19 | Oracle International Corporation | Declarative and extensible model for provisioning of cloud based services |
US10270706B2 (en) | 2012-09-07 | 2019-04-23 | Oracle International Corporation | Customizable model for throttling and prioritizing orders in a cloud environment |
US10009219B2 (en) | 2012-09-07 | 2018-06-26 | Oracle International Corporation | Role-driven notification system including support for collapsing combinations |
US20140074539A1 (en) * | 2012-09-07 | 2014-03-13 | Oracle International Corporation | Business attribute driven sizing algorithms |
US10148530B2 (en) | 2012-09-07 | 2018-12-04 | Oracle International Corporation | Rule based subscription cloning |
US9467355B2 (en) | 2012-09-07 | 2016-10-11 | Oracle International Corporation | Service association model |
US9501541B2 (en) | 2012-09-07 | 2016-11-22 | Oracle International Corporation | Separation of pod provisioning and service provisioning |
US9667470B2 (en) | 2012-09-07 | 2017-05-30 | Oracle International Corporation | Failure handling in the execution flow of provisioning operations in a cloud environment |
US9542400B2 (en) | 2012-09-07 | 2017-01-10 | Oracle International Corporation | Service archive support |
US11075791B2 (en) | 2012-09-07 | 2021-07-27 | Oracle International Corporation | Failure handling in the execution flow of provisioning operations in a cloud environment |
US9621435B2 (en) | 2012-09-07 | 2017-04-11 | Oracle International Corporation | Declarative and extensible model for provisioning of cloud based services |
US9646069B2 (en) | 2012-09-07 | 2017-05-09 | Oracle International Corporation | Role-driven notification system including support for collapsing combinations |
US9838370B2 (en) * | 2012-09-07 | 2017-12-05 | Oracle International Corporation | Business attribute driven sizing algorithms |
US20140089178A1 (en) * | 2012-09-21 | 2014-03-27 | Gotrust Technology Inc. | Mobile financial transaction system and method |
US9098617B1 (en) * | 2012-09-27 | 2015-08-04 | Emc Corporation | Data analytics lifecycle automation |
US10762230B2 (en) * | 2012-10-12 | 2020-09-01 | Egnyte, Inc. | Systems and methods for facilitating access to private files using a cloud storage system |
US11663355B2 (en) * | 2012-10-12 | 2023-05-30 | Egnyte, Inc. | Systems and methods for facilitating access to private files using a cloud storage system |
US11275863B2 (en) * | 2012-10-12 | 2022-03-15 | Egnyte, Inc. | Systems and methods for facilitating access to private files using a cloud storage system |
US9507642B2 (en) * | 2012-12-04 | 2016-11-29 | Xerox Corporation | Method and systems for sub-allocating computational resources |
US20140156518A1 (en) * | 2012-12-04 | 2014-06-05 | Xerox Corporation | Method and systems for sub-allocating computational resources |
WO2014086043A1 (en) * | 2012-12-07 | 2014-06-12 | Hewlett-Packard Development Company, L.P. | Network resource management |
US10057183B2 (en) | 2012-12-07 | 2018-08-21 | Hewlett Packard Enterprise Development Lp | Network resource management |
CN104838690A (en) * | 2012-12-07 | 2015-08-12 | 惠普发展公司,有限责任合伙企业 | Network resource management |
US9262493B1 (en) | 2012-12-27 | 2016-02-16 | Emc Corporation | Data analytics lifecycle processes |
US10546040B2 (en) | 2013-06-14 | 2020-01-28 | Microsoft Technology Licensing Llc | System and method for automatic provisioning of companion resources in a web hosting environment |
US9684866B1 (en) | 2013-06-21 | 2017-06-20 | EMC IP Holding Company LLC | Data analytics computing resource provisioning based on computed cost and time parameters for proposed computing resource configurations |
US9972013B2 (en) * | 2013-08-15 | 2018-05-15 | Mastercard International Incorporated | Internet site authentication with payments authorization data |
US20150052053A1 (en) * | 2013-08-15 | 2015-02-19 | Mastercard International Incorporated | Internet site authentication with payments authorization data |
US9235630B1 (en) | 2013-09-25 | 2016-01-12 | Emc Corporation | Dataset discovery in data analytics |
US10949778B2 (en) | 2013-09-27 | 2021-03-16 | Transvoyant, Inc. | Computer-implemented systems and methods of analyzing data in an ad-hoc network for predictive decision-making |
US10091276B2 (en) | 2013-09-27 | 2018-10-02 | Transvoyant, Inc. | Computer-implemented systems and methods of analyzing data in an ad-hoc network for predictive decision-making |
US20150256475A1 (en) * | 2014-03-05 | 2015-09-10 | Wipro Limited | Systems and methods for designing an optimized infrastructure for executing computing processes |
US10244403B2 (en) | 2014-05-08 | 2019-03-26 | Nokia Solutions And Networks Oy | Cloud based access network |
EP3143562A4 (en) * | 2014-05-16 | 2017-10-25 | Transvoyant LLC | Computer-implemented systems and methods of analyzing data in an ad-hoc network for predictive decision-making |
WO2015191119A1 (en) * | 2014-06-11 | 2015-12-17 | Oracle International Corporation | Providing a subscription for a service using an existing subscription |
US9749208B2 (en) | 2014-06-30 | 2017-08-29 | Microsoft Technology Licensing, Llc | Integrated global resource allocation and load balancing |
US9912609B2 (en) | 2014-08-08 | 2018-03-06 | Oracle International Corporation | Placement policy-based allocation of computing resources |
US10291548B2 (en) | 2014-08-08 | 2019-05-14 | Oracle International Corporation | Contribution policy-based resource management and allocation system |
WO2016022908A1 (en) * | 2014-08-08 | 2016-02-11 | Oracle International Corporation | Placement policy-based allocation of computing resources |
US9961017B2 (en) | 2014-08-08 | 2018-05-01 | Oracle International Corporation | Demand policy-based resource management and allocation system |
CN106664321A (en) * | 2014-08-08 | 2017-05-10 | 甲骨文国际公司 | Placement policy-based allocation of computing resources |
US10164901B2 (en) | 2014-08-22 | 2018-12-25 | Oracle International Corporation | Intelligent data center selection |
US11528207B1 (en) * | 2014-12-17 | 2022-12-13 | Amazon Technologies, Inc. | Computing system monitor auditing |
US9800489B1 (en) * | 2014-12-17 | 2017-10-24 | Amazon Technologies, Inc. | Computing system monitor auditing |
WO2016102297A1 (en) * | 2014-12-24 | 2016-06-30 | Koninklijke Kpn N.V. | Method for controlling on-demand service provisioning |
EP3637259A1 (en) * | 2014-12-24 | 2020-04-15 | Koninklijke KPN N.V. | Method for controlling on-demand service provisioning |
CN107209694A (en) * | 2014-12-24 | 2017-09-26 | 皇家Kpn公司 | Method for controlling on-demand service to supply |
US10581703B2 (en) | 2014-12-24 | 2020-03-03 | Koninklijke Kpn N.V. | Method for controlling on-demand service provisioning |
US10142174B2 (en) | 2015-08-25 | 2018-11-27 | Oracle International Corporation | Service deployment infrastructure request provisioning |
US11316934B2 (en) | 2015-12-28 | 2022-04-26 | Koninklijke Kpn N.V. | Method for providing a service to a user equipment connected to a first operator network via a second operator network |
US10860965B2 (en) | 2016-07-18 | 2020-12-08 | Transvoyant, Inc. | System and method for tracking assets |
US11507911B2 (en) | 2016-07-18 | 2022-11-22 | Transvoyant, Inc. | System and method for tracking assets |
CN107563663A (en) * | 2017-09-15 | 2018-01-09 | 重庆智迅云信息技术有限公司 | Enterprise's scene cloud management system based on cloud computing |
US11681573B2 (en) | 2017-09-30 | 2023-06-20 | Oracle International Corporation | API registry in a container platform providing property-based API functionality |
US11755393B2 (en) | 2017-09-30 | 2023-09-12 | Oracle International Corporation | API registry in a container platform for automatically generating client code libraries |
US11159446B2 (en) | 2018-10-30 | 2021-10-26 | Red Hat, Inc. | Cloud resource management using externally-sourced data |
US11784939B2 (en) | 2018-10-30 | 2023-10-10 | Red Hat, Inc. | Cloud resource management using externally-sourced data |
US11086667B2 (en) | 2019-06-11 | 2021-08-10 | International Business Machines Corporation | Selective scheduling of cloud maintenance tasks |
WO2021068763A1 (en) * | 2019-10-09 | 2021-04-15 | 北京金山云网络技术有限公司 | Cloud resource creation method, apparatus, client and server |
US11277727B1 (en) * | 2020-07-17 | 2022-03-15 | Sprint Communications Company L.P. | Internet of Things communication service |
US11611861B2 (en) | 2020-07-17 | 2023-03-21 | Sprint Communications Company, L.P. | Internet of Things communication service |
Also Published As
Publication number | Publication date |
---|---|
US9503549B2 (en) | 2016-11-22 |
US20140201362A1 (en) | 2014-07-17 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US9503549B2 (en) | Real-time data analysis for resource provisioning among systems in a networked computing environment | |
US10776730B2 (en) | Policy-based scaling of computing resources in a networked computing environment | |
US9569598B2 (en) | Software license management in a networked computing environment | |
US9465644B2 (en) | Selection of virtual machines from pools of pre-provisioned virtual machines in a networked computing environment | |
US9158590B2 (en) | Dynamically acquiring computing resources in a networked computing environment | |
US8793377B2 (en) | Identifying optimal virtual machine images in a networked computing environment | |
US9225604B2 (en) | Mapping requirements to a system topology in a networked computing environment | |
US9009294B2 (en) | Dynamic provisioning of resources within a cloud computing environment | |
US9641392B2 (en) | Policy implementation in a networked computing environment | |
US8806003B2 (en) | Forecasting capacity available for processing workloads in a networked computing environment | |
US8909769B2 (en) | Determining optimal component location in a networked computing environment | |
US9229784B2 (en) | Determining resource instance placement in a networked computing environment | |
US20130311988A1 (en) | Migrating virtual machines between networked computing environments based on resource utilization | |
US9229777B2 (en) | Dynamically relocating workloads in a networked computing environment | |
US8806485B2 (en) | Configuring virtual machine images in a networked computing environment | |
US8825862B2 (en) | Optimization of resource provisioning in a networked computing environment | |
US9225662B2 (en) | Command management in a networked computing environment | |
US20140244311A1 (en) | Protecting against data loss in a networked computing environment |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: INTERNATIONAL BUSINESS MACHINES CORPORATION, NEW Y Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:RADHAKRISHNAN, RAJESH;TAN, YIH-SHIN;SIGNING DATES FROM 20110330 TO 20110406;REEL/FRAME:026155/0704 |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO PAY ISSUE FEE |
|
AS | Assignment |
Owner name: KYNDRYL, INC., NEW YORK Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:INTERNATIONAL BUSINESS MACHINES CORPORATION;REEL/FRAME:058213/0912 Effective date: 20211118 |