AU2011344038A1

AU2011344038A1 - Hybrid cloud broker

Info

Publication number: AU2011344038A1
Application number: AU2011344038A
Authority: AU
Inventors: Nandish Kopri; Jayesh Paliwal; Nandakumar Selvaraj
Original assignee: Unisys Corp
Current assignee: Unisys Corp
Priority date: 2010-12-13
Filing date: 2011-12-13
Publication date: 2013-07-04
Also published as: EP2652695A2; CA2821270A1; WO2012082726A3; WO2012082726A2; EP2652695A4

Abstract

A system and method for managing information technology (IT) infrastructure by automatically adapting hardware and software resources to the dynamic real-time business requirements is disclosed. A web-enabled software application offers users a number of services in the form of business transactions. A business rule defines the backend hardware and software IT resources required to generate data responsive to a particular type of transaction. The business rule also defines priority information for the particular transaction among other transactions in a queue. The rule is deployed to the IT resources and a monitoring module monitors the use of the IT resources to ensure that it is within the set rules. When the resources are over-used or under-used an alarm is triggered. In response to the alarm, the business rule is automatically altered with a new business rule defining a different allocation of IT resources for the next similar transaction type.

Description

WO 2012/082726 PCT/US20111/064619 HYBRID CLOUD BROKER TECHNICAL FIELD [0001] The present invention relates generally to a system and method of managing information technology infrastructure or cloud resources by automatically adapting hardware and software components of the cloud resources to the dynamic real-time business transaction requirements. BACKGROUND [0002] Information technology (IT) service providers are companies that maintain sophisticated hardware and software capabilities to manage data for the services they provide to their customers, herein referred to as "business clients." Backend IT services are used by such businesses as online retailers, e-commerce companies, and banks. By way of an example, a banking business client utilizes backend IT services to offer its customers several online banking services. The online banking services are provided via a web enabled software application and involve a number of business transactions from which a bank customer can choose. Some examples of online banking transactions include balance inquiry, bill payments, and money transfers. Another example of an online business is an e commerce company, such as e-Bay@, which sells auction services online. Such businesses utilize business transactions in the form of online billing, payment processing, order tracking, and account maintenance. [0003] Further, online businesses differ from each other by a number of factors including the nature of the business, its customers, and seasonality of the business. For example, an online retail store typically needs to service more customers during the holiday season than a banking business, which might be more consistent in the number of customers over the same period. In another example, a social networking service utilizing multiple java applications tends to stress the application server tier more than the database server tier. In yet another example, a news website attracts different customer types than an e commerce website. When a news aggregator website provides weblinks to a smaller local website, there is a sudden spike of visitors to the local website. This may be considered a "slashdot" effect, where the traffic to the local website spikes as it is being linked by a WO 2012/082726 PCT/US2011/064619 website of higher popularity. Here, the type of visitor is in a broader interest category than, for example, a website selling VOIP (voice over internet protocol) services and phone cards online. [0004] Even as businesses seek to expand online offerings, it is important to be able to tie business results from online service offering to investments in infrastructure required to implement and maintain the online business. Many businesses try to strike a balance between owning or renting backend IT infrastructure to enable the online business. One form of backend IT infrastructure, herein referred to as "cloud resources," comprises many components including physical components (e.g., servers, network equipment, and accessories - power supply, stabilizer), virtual components (e.g., software licenses), and technical manpower. A datacenter is the physical core of a cloud resources system and can comprise server farms, which are a plurality (typically hundreds or thousands) of servers with varying functions and capacities along with backup and supporting equipment like generators, uninterrupted power supplies ("UPS"), routers, switches, etc. The cost of ownership is high and there is an increased need to tie resource utilization to income and investments. Although the capital costs associated with creation of a datacenter are high, the maintenance and support costs associated with the datacenter can quickly exceed the capital costs over a very short time. Thus, the total cost of owning and maintaining a datacenter, or even a presence within a datacenter, can be very high, and businesses are increasingly looking to justify these costs by tying resource utilization, and the revenue generated therefrom, to the costs associated with those resources. [0005] As a result of high ownership costs to maintain and upgrade IT infrastructure along with the need to protect data and ensure systems for redundancy and reliability, many businesses have moved to using a third party cloud resources model. In this model, an IT service provider is third party business that owns and operates the IT infrastructure for several businesses that offer web-based products and services. The service provider enables sharing of cloud resources among multiple business clients, thereby forming a cloud resources system, where the integration of the resources is dependent on different price-to efficiency models. In one model, the business client pays a fee for leasing certain backend IT hardware for certain periods of time. The business client can add resources during peak seasons or remove resources during regular business seasons. In another model, the 2 WO 2012/082726 PCT/US2011/064619 business client is charged only for the utilization of resources (e.g., energy use, service use processing, memory). Further, some IT companies offer cloud computing resources, where the entire physical and virtual infrastructure is located in multiple locations, business clients still own their data and the fees are strictly usage-based. From a service provider's perspective, a single IT hardware and software resources can be re-allocated to multiple business clients or business functions for the same client depending on resource utilization. [0006] The services offered by the service provider to a business client are frequently based on the level of involvement of the service provider in the client's web-enabled businesses. The negotiated agreement between the service provider and the client is called a service level agreement (SLA). The SLA defines the level and quality of service provided to the business client. It also includes performance metrics (e.g., processing (CPU) and memory consumption), reporting procedures, duration of involvement, issue resolution, and security procedures as well as the transaction times, costs, and penalties involved when a business client uses the service provider's resources. More detailed metrics for the quality parameters are typically listed in a service level objectives ("SLO") document. The SLA defines business policies at a very high level, for example, the description of the service to be provided. [0007] As an example of an SLA-based engagement, in an e-commerce implementation, the SLA would describe, among other things, the service to be provided and the various component modules that are required to enable the system to function. The service to be provided in this e-commerce example could be either the sale of goods or services while the components required include hardware and software resources to enable a payment module, customer tracking, coupons, order tracking, e-mailing procedures, security modules, and other related components. The SLO would provide greater details on the payment modules, such as transaction descriptions and transaction times. Following the disclosure in the SLA, business policies are instituted that are generally broad abstract business statements that target the goals and visions of a business, but are supported by the SLA. An exemplary business policy supported by the SLA would be to increase customer retention, which can be supported by the customer tracking and coupon capabilities under the SLA. In view of the business policy, IT business analysts generate business rules to link the abstract business policy to measurable business parameters. Using the same e-commerce 3 WO 2012/082726 PCT/US2011/064619 business example, a business rule to achieve the customer retention policy is to offer discounts to repeat customers. Another business rule example to increase customer retention is to offer coupons to new customers to draw them back for second purchases. [0008] The processes described above require significant manual intervention and are further complicated by variables in the IT architecture including, without limitation, scalability, reliability, repeatability, and security. With the advent of cloud computing methods, there is an increased demand for highly secure, scalable, and reliable automated data management systems with deeper integration between IT and dynamic business requirements. There is also a demand for IT service provider companies to be able to offer agility in infrastructure management services to match changing business methods. Further, IT service providers are attempting to devise better metrics to analyze resource consumption and enable better sharing of resources with minimal human intervention. Conventionally, data management is primarily a mix of manual and automated methods. In some cases, the cloud resources are fixed to be responsive to certain business services offered by the client. Transaction requirements for a business activity are fed into a system management software and alarms are triggered to indicate if the infrastructure requirements are exceeded or under used. The resources are then altered manually to support additional transaction loads. SUMMARY [0009] The systems and methods described herein attempt to overcome the drawbacks discussed above by automatically adapting hardware and software components of the cloud resources to the dynamic real-time business transaction requirements. [0010] In one embodiment, a computer-implemented method for automatically adapting a service provider's cloud resources to the requirements of business transactions comprises providing, by a computer, a first computer-coded business rule, wherein the first computer-coded business rule comprises limiting parameters related to at least one business transaction; providing, by the computer, at least one computer-coded resource policy, wherein the computer-coded resource policy comprises managing parameters to manage the distribution of cloud resources within the limiting parameters in the first computer-coded business rule; monitoring, by the computer, the utilization parameters of the cloud resources for the business transaction, wherein an alarm is generated when the utilization parameters 4 WO 2012/082726 PCT/US2011/064619 exceed the limiting parameters defined in the first computer-coded business rule; updating, by the computer, the limiting parameters of the first computer-coded business rule with new limiting parameters in response to the alarm, thereby generating a second computer-coded business rule; and rendering, by the computer, the second computer-coded business rule, wherein the managing parameters of the computer-coded resource policy manage the distribution of cloud resources within the limiting parameters in the second computer-coded business rule. [0011] In another embodiment a computer-implemented system for automatically adapting a service provider's cloud resources to the requirements of business transactions comprises providing, by a computer, a first computer-coded business rule, wherein the first computer-coded business rule comprises limiting parameters related to at least one business transaction; providing, by the computer, at least one computer-coded resource policy, wherein the computer-coded resource policy comprises managing parameters to manage the distribution of cloud resources within the limiting parameters in the first computer-coded business rule; monitoring, by the computer, the utilization parameters of the cloud resources for the business transaction, wherein an alarm is generated when the utilization parameters exceed the limiting parameters defined in the first computer-coded business rule; updating, by the computer, the limiting parameters of the first computer-coded business rule with new limiting parameters in response to the alarm, thereby generating a second computer-coded business rule; and rendering, by the computer, the second computer-coded business rule, wherein the managing parameters of the computer-coded resource policy manage the distribution of cloud resources within the limiting parameters in the second computer-coded business rule BRIEF DESCRIPTION OF THE DRAWINGS [0012] The accompanying drawings constitute a part of this specification and illustrate an embodiment of the invention, and together with the specification, explain the invention. [0013] FIG. 1 illustrates a system architecture according to an exemplary embodiment. [0014] FIG. 2 illustrates a method of managing multiple cloud site resources using multiple autonomous infrastructure management software modules controlled by a single governing software module according to an exemplary embodiment. 5 WO 2012/082726 PCT/US2011/064619 [0015] FIG. 3 illustrates a method of managing information technology infrastructure by automatically adapting hardware and software resources to business requirements according to an exemplary embodiment. [0016] FIG. 4 illustrates a method of managing information technology infrastructure by automatically adapting hardware and software resources to business requirements during a business transaction according to an exemplary embodiment. [0017] FIG. 5a illustrates the content of the business policy or business rule application logic used to allocate the cloud site resources according to an exemplary embodiment. [0018] FIG. 5b illustrates the content of the computer coded resource policy used to control the cloud site resources according to an exemplary embodiment. DETAILED DESCRIPTION [0019] Reference will now be made in detail to the preferred embodiments, examples of which are illustrated in the accompanying drawings. [0020] Dynamic real-time requirements of business transactions are managed by automatically adapting the information technology (IT) hardware and software resources (or cloud resources) after negotiating between the business policy requirements and the cloud resources. A business client's web-enabled business application offers the customer several business transactions as a business service. By way of an example, an account balance inquiry business service may consist of a savings account balance inquiry transaction, a checking account balance inquiry transaction, and a credit account balance inquiry transaction An SLO is then defined for the business service, and can contain more information on each transaction, including, for example, transaction descriptions and transaction times. Each transaction functions within an application and is initiated as a user request by the user using the application. The transaction interacts with a backend web server and application server to secure the information from backend database servers. A service level agreement (SLA) between the business client and a service provider determines how each transaction should be managed - including the intended transaction times and the required backend servers to process the transaction. The SLA can also include additional performance metrics like traffic capacity, energy consumed, redundancy, and data security to each transaction depending on the transaction type. 6 WO 2012/082726 PCT/US2011/064619 [0021] One exemplary embodiment allows for closer integration between business and IT where, when business transactions are deployed with requirements defined in the SLA, those transactions are dynamically supported within minutes or seconds by the cloud resources. Business rules derived from the business policy are supported by the metrics defined in the terms of the SLA. Business transactions are then determined based on the business rules and are offered as paid or free additional services to the business client's customers. These business rules are then scripted in a computer program, herein referred to as computer-coded, with metrics that determine the type of server tiers that are required to generate the responsive data as well as transaction times that the transaction can afford among other related metrics. Additional metrics include the time and date rules and associated priority information. By way of example, without limitation, some transactions can be configured as having higher priority at certain times the transaction request is made. These computer-coded business rules are related to the business transactions and are initiated when the user requests certain transactions from several transaction options on the business clients' web-enabled software application. Using the previously discussed e commerce business example, a conventional business rule to achieve a customer retention policy is to offer discounts to repeat customers. Another business rule example to increase customer retention is to offer coupons to new customers to draw them back for second purchases. An embodiment converts the business rule to a computer-coded business rule comprising limiting parameters to define the priority metrics, cloud resources usage metrics, user information, and the discount or coupon information for the business rule. As a result, a returning user of a business client, on recognition (e.g., using the same login name or internet protocol address), will have their new transaction requests subject to a faster interaction process with more discounts or coupons in the options. The final result is an enhanced user experience for a returning customer. [0022] In another exemplary embodiment, the resource usage for a type of business transaction is monitored and statistics are collected concerning the energy used, processor, and memory utilization, and software utilization, among other utilization parameters. An analysis module obtains the usage data from a monitoring module and analyzes this data for each business rule that accompanies a transaction. The analyses module determines if the resources are being improperly used including over-used, under-used or not matching to one 7 WO 2012/082726 PCT/US2011/064619 of the metrics defined in the computer-coded business rules. The allocation of resources for each business transaction is a result of the business rules, which means that if a business deploys a new business transaction and defines the applicable business rules for the transaction, the resources are available, instantly (typically within minutes or seconds), to enable full functionality for the new service. Alternatively, an existing business rule can be applied to the newly deployed transaction, thereby ensuring a quick deployment time and effective use of resources to support the new transaction. The existing business rule can be applied automatically after the system determines, by intelligent analysis, the historical business rules and resource utilization for previous business transaction that could be similar to the new transaction. [0023] In further embodiments, the business rules are defined so as to convert abstract human-readable logic that are the business policies into application logic for computer implementation via an automated service governor software module comprising a business rules engine module and a business rules manager module. The service governor software module works with an autonomic infrastructure management (AIM) software module which comprises smaller modules for resource discovery, monitoring, and management. Discovery is a process wherein the types of hardware, software and personas are identified along with their status (e.g., available, unavailable, or shared). The service governor module further comprises a business rules engine module and a business rules manager module. The computer-coded business rules are defined in the business rules engine module while autonomous programming script resource policies, herein referred to as computer-code resource policies, are defined in the business rules manager. The output of the business rules manager module is essentially limited by the output from the business rules engine module which contains historic rules responsive to previous transactions and new custom defined business rules if the system administrator intervenes on an alarm. The alarm is generated when the thresholds set by the computer-coded business rules and the computer coded resource policies are breached. For example, the threshold for an acceptable business transaction is less than 80% or more than 30% of resource usage, where 'less than 80%' or 'more than 30%' serves as the threshold, if more resources are required or less resources are being utilized by the transactions, then the alarm is triggered. 8 WO 2012/082726 PCT/US2011/064619 [0024] In one embodiment, the automated computer-coded business rules can be generated in an intelligent server module using a server-size algorithm, where the algorithm calculates the server size (or server instances) and threshold based on a delta workload as disclosed in equations (1) and (2). The delta workload is defined as the inverse ratio of the previous rule threshold and the product of the absolute threshold and the difference of the current rule threshold and previous rule threshold. The suggested number of server instances will then be the product of the delta workload calculated from the above method and the number of server instances from the current rule. In another exemplary embodiment, the automated computer-coded business rules can be generated in the intelligent server module using an approximation algorithm. The approximation algorithm can be used to generate computer-coded business rules by changing either the server size or both the service size and the service thresholds. When the maximum threshold is affected by the current business transactions, the approximation algorithm is implemented by calculating the current delta workload for the current and maximum thresholds. The server size is then calculated as the product of the delta workload and the maximum number of servers as shown in equation (1); the server size is then added to the maximum number of server instances as disclosed in equation (3). In another embodiment, if the minimum threshold is affected then, as disclosed in equation (4) the minimum number of servers are further reduced by the server size calculated from the current delta workload and the minimum number of servers for the transaction using the method described above. Server size = Delta Workload * Number of current server instances (1) Absolute threshold * Delta workload = Currrent rule threshold - Previous rule threshold} (2) Previous rule threshold ) New server size = Server size from equation (1) +current maximum number of server instances (3) New server size = Current mimimum number of server instances - Server size from equation (4) [0025] In a yet another exemplary embodiment for generating automated computer coded business rules, if the number of server instances and the threshold are affected by the 9 WO 2012/082726 PCT/US2011/064619 current business transaction volume, the following exemplary calculation can be used. For the minimum and maximum threshold violations, the delta workload is calculated using the forecasted minimum and maximum thresholds, the server size is then calculated using the delta workload (equation (2)) and the maximum or minimum number of servers as described in the previous embodiment. Accordingly, the maximum or the minimum number of servers will be increased or decreased, respectively, by the calculated server size. The corresponding thresholds, if affected, can be updated using the new maximum or minimum thresholds based on the newly calculated server size. A combination for the minimum and maximum forecasted thresholds can be implemented if both thresholds are simultaneously breached. The automated computer-coded business rules generated from these calculations contain new limiting parameters, which are then used to update the old parameters in the previous computer-coded business rules as a result threshold and/or server size breach alarms. [0026] In an exemplary embodiment, if a business transaction requires the use of an Apache application server from the cloud resources, the business rules manager deploys resource specific policies that define the available metrics for the Apache server. The metrics in these policies are resource specific and include the maximum and minimum number of server instances, the server threshold information, and scale-in and scale-out actions. When these policies are deployed to the AIM module, they instruct the module to use resources in the manner designated by the rule for the incoming business transaction. The policies within the business rules manager, herein referred to as computer-code resource policies, are limited by the computer-code business rules which essentially add resource utilization limiting metrics like priority and time period application of the computer-code resource policies beyond which an alarm is triggered for out-of-limitation resource uses. [0027] In another embodiment, the discovery module recognizes the status of the cloud resources and lets the administrator know about the availability of resources for new transactions. The monitoring module monitors resource utilization and informs the AIM module so that the policies can be updated where required. The service governor module also ensures that the computer-code business rules generated at the business rules engine are within the policies of resource usage established through the SLA. The availability and usage of resources should be aligned with the SLA requirements regarding resource 10 WO 2012/082726 PCT/US2011/064619 consumption, transaction time, and energy usage, while the resource usage per transaction should be within the bounds of the computer-coded business rules. If there is an improper use of resources as a result of the usage being out of policy, alarms can be triggered in the system. [0028] In another exemplary application, the service governor module is a web-enabled application accessible via a browser and comprises event handler function modules which receive and respond to all alerts from the system. The event handler function module determines the actions to be applied in response to the alarms. In an example, the event handler function modules and logs are implemented using a .NET framework and a common runtime language. Further, a publisher-subscriber pattern is implemented in a C# .NET environment. There are multiple event handlers that are used to track information, for example, an ICustomerEventHandler function can be used to define the policy or rule to be implemented on an event alarm, an INotifier handler function that defines the method of applying the rule, and an ISubscriber function that defines the rule. [0029] A SQL database can be used to manage and store status information of the alarms generated, action response information, resource usage, and related information. The web-enabled application comprising the service governor module further comprise options to manually or automatically define metrics in the computer-coded business rules, wherein the rules are within the business policy. The automated definition computer-coded business rules are based on an intelligent learning module that uses historical metrics used in previous computer-coded business rules responsive to new business transactions. An example of an intelligent learning module is a neural networks module that associates metrics in the computer-coded business rules to the certain historical transaction types and identifies similarity of transaction types using the metrics. One method of using an intelligent learning module compares the type of business transaction and the date of the transaction to historical transactions and then offers the administrator a choice of computer-coded business rules or automatically applies the best choice to the business rules manager module. [0030] In yet another embodiment, the intelligent learning module is configured to negotiate with the business rules engine to add or remove resources and to learn from the updates to the computer-coded business rules to derive intelligent new computer-coded business rules for certain transactions. The web-enabled software application coupled to the 11 WO 2012/082726 PCT/US2011/064619 service governor also comprises a reports module to generate real-time reports of the status, alarms, resource usage and resolutions based on user requests. Additional web-enabled software applications also provide the system administrator with a user interface to the AIM module that implements the rules so that the emergency changes in resource management can be implemented while bypassing the business rules manager. The output of the AIM module provides physical as well as virtual provisioning of the cloud resources using an orchestrating and a resource adapting module. The service governor is also capable of interacting with multiple applications that analyze, monitor, discover, and orchestrate between the business transactions and the service provider's resources. [0031] In additional embodiments, the service governor software is designed to accept business rules across a multi-tier IT architecture for the business backend. For the quality of service (QoS) benchmark in the SLA, it can be advantageous if the architecture described is extensible with support for .NET clients. The graphical user interface (GUI) used to provide business rules to the governor is developed on a .NET WPF framework and contains a Rule editor with capabilities to define, create, update, and delete rules. The rules can be stored in event handler function modules for future references, to train the system for intelligent responses, and to record error parameter for manual intervention. The result of any deployment of business rules and the utilization information is also recorded for reporting and billing purposes. In other embodiments, a Drools .NET engine can be used to generate and manage workflow rules in a .NET environment. [0032] In yet another embodiment, resources are made available in the form of multi tier network architectures using web servers like Apache servers, IBM HTTP Servers, and Sun Web Servers which can be used in the web tier of the backend architecture. Also, IBM's Websphere, BEA's Weblogic, Tomcat, SAP's NetWeaver, and Caucho Resin are exemplary application server types that can be implemented herewith. In the Database tier, the Oracle Database, Sybase, and SQL Servers can be configured into the architecture. Further, existing third party modules can also be used with the service governor software. Modules to monitor and distribute resources, like Optier core first, BMC, and TM-ART, as well as statistical analysis modules can be implemented herewith. The AIM monitors the use of resources through an orchestration module which adapts physical tier pools to work based on the requirements of the business rules. 12 WO 2012/082726 PCT/US2011/064619 [0033] The AIM module can also monitor the use of the virtual machine (VM) resources in the cloud, thereby enabling virtual provisioning of personas and software. Personas are software components containing metadata relating the component to a certain hardware platform which is required for the persona to operate. A few examples of virtual machines used herein include VMware Virtual center 2.x, VMWare, ESX V13 Solaris Zones, XEN, and Microsoft virtual center. The AIM module also comprises internal modules to monitor the computer-coded business rules and the cloud resources while working as an interface to the orchestrating module. A few examples of virtual machines used herein include VMware Virtual center 2.x, VMWare, ESX V13 Solaris Zones, XEN, and Microsoft virtual center. Web-enabled user interface applications can also be made available to the business client and the administrator so that each may access the cloud resources, modules and functions of each of the modules including the AIM service, the orchestrating module, the service governor module, the alarm module, the SQL database and the analysis module. [0034] FIG. 1 illustrates the architecture of an exemplary embodiment using a cloud computing architecture 100 where a business client front end or client computing device 105 communicates through a network 120, e.g., the internet, with a cloud services gateway 110 and cloud resources 115. The frontend computing device 105 can be any network-enabled computing device, e.g., a personal computer, laptop, palm top computer, tablet computer, smart phone, personal data assistant, mobile or cellular phone, or any other device with at least one processor, networking capability and one storage unit. The front end computing device 105 allows the user to communicate with the IT service provider on new business transactions, changes to the SLA, business policies, rules, and the like. The gateway computing device 110 is a secure server computing device with at least one processor, networking capability and one storage unit configured to execute a web-enabled user interface application. The user interface application comprising modules 135 allows a system administrator to interact with several application modules 135 that perform functions including discovery, monitoring, and managing of backend IT resources, analyzing business rules and resource consumption, and storing and reporting analytical information. The computing device 110 is capable of handling large volume requests, data analysis and multi tasking applications. 13 WO 2012/082726 PCT/US2011/064619 [0035] The client computing device 105 contains a web-enabled user interface software application comprising input module 130 that interacts with the backend cloud services gateway computing device 110 by providing inputs to application module components 135 on gateway computing device 110. In the illustrated embodiment, the business client defines SLA terms, business policies and business rules on the client computing device 105, and this information functions as an input to the service governor application through the business rules engine on the gateway computing device. In an exemplary embodiment, the business rules broker, or negotiate, with the resource policy to adjust the cloud resources for the changing business transaction needs. This enables seamless business to information technology (IT) integration between the business client and the IT platform. The web enabled user interface software application 130 contains fields or options to provide inputs for metrics that are generated on the cloud services gateway 110. The computer-coded business rules output from the cloud services gateway 110 are used to control the cloud resources 115. [0036] The cloud resources 115 include server pools which could function as a multi tier network cloud architecture. The pools 120, 125, 170 reflect a collection of hardware, software and persona (or virtual machine) resources that form a web-tier, an application tier and a database tier. Depending on the type of business transaction initiated by a customer using the business client's online services, the resource pools are adjusted by moving hardware resources 140, 145 in pool 120 to pool 125. This allows for re-allocation of the resources in the multi-tier cloud architecture. Further, software resources 150, 165 can be shared between hardware components depending on the requirements of the business transaction in effect. The datacenter resources 115 in the form of hardware, software and personas (or virtual machines) are monitored by an orchestrator which receives instructions from the autonomic infrastructure management ("AIM") module. In some embodiments, both modules may be resident on the cloud gateway computing device 135. [0037] The service governor module receives the business rules from the application inputs 130 on the business client computing device 105 and converts the rules to measurable metrics in a computer-coded business rules comprising limiting parameters. By way of example, without limitation, a business rule within a business policy is defined by such features as date and time of utilization, priority level and CPU utilization parameters at the 14 WO 2012/082726 PCT/US2011/064619 time of implementation. This business rule can be converted to a computer-coded business rule which determines the limitations on the resources by the number of instances and the scalability options available with the resource, etc. Such information also allows the AIM module on the gateway 110 to review and allocate the resources that can be tied to a transaction. These resources in Pool 1 120 to Pool 3 170 can then be made unavailable for other transactions during the period. This is advantageous when the backend IT service provider uses the same cloud resources for multiple business clients. The two software resources 150, 165 also represent virtual machines or personas. [0038] While transferring resources across tiers, the software required for the transferred resource may be different from the existing software. One exemplary implementation allows software to be ported or enabled on a different server based on the function of the server. In some embodiments, sharing of software can be implemented using a shared license for multiple systems, where when a first system is activated, the license for the software on that system is allocated to that system for a given time period (e.g., until the first system is deactivated) and can be de-allocated and allocated to a second system at a different time. It is appreciated that the cloud services gateway computing device 110 may be a network enabled device similar to device 105 and could be a personal computer, laptop, palm tops, Smart Phones, personal data assistant, mobile or cellular phones, or any other device with at least one processor, networking capability and one storage unit. [0039] The user interface application is used to define business related limiting parameters and abstract concepts including business policies and their associated business rules. The business rules might include metrics such as discount values and period of discount as well as customer tags to identify the user or the transaction type. These business rules are automatically converted into limiting parameters in the computer-coded business rules using input modules in the user application 130 on the cloud services gateway 135. The cloud services gateway 135 can further be comprised of two independent computing devices - one which can be automated using intelligent processing and learning methods and the other which allows for manual interrupts to the intelligent systems. This allows the user to define the initial responses to the system alarms. In some embodiments, the alarms are primarily resident within the analysis modules on the cloud services gateway 135. These alarms could trigger an internal silent alarm to the intelligent system, or alternatively, the 15 WO 2012/082726 PCT/US2011/064619 alarms could trigger e-mail or similar messages to the system administrator. Further, the business client computing device 105 can be integrated with the cloud services computing device 110, wherein the business client computing device defines business rules and e-mails them to the cloud services administrator or the cloud computing device. The administrator can manually update the service governor or the cloud computing device can be configured to deconstruct the e-mail and automatically update the service governor with the new business rules. [0040] The system 100 can be configured to work with third party software applications designed as modules to fit within an existing IT architecture. Certain monitoring applications like Optier@ core first, BMC and TM-ART@ can be used as modules by altering the input computer-codes of the service governor to accept the monitoring outputs. The outputs have to be analyzed along with the business rules to provide some meaning to monitoring data in view of the resource usage in SLA. The operating systems that work with the frontend 105 and the cloud services gateway 110 computing devices include, without limitation, Microsoft Windows@, Apple Macintosh@ OSx, Solaris®, Linux® and AIX®. In some embodiments, the user interfaces can be managed using web-browser applications like Internet Explorer@ and Mozilla Firefox@ from a web-enabled device. [0041] The information related to utilization of resources, alarms, business policies and rules can be stored in storage database 175 which, in some embodiments, may be a SQL database. The SQL database can be accessed via the software application 135 on the gateway device 110. In some embodiments, the gateway device 110 may be capable of running multi-user applications and managing large traffic volumes. The actual software applications on the cloud services gateway can be controlled using a web interface. [0042] The event handler function modules in the service governor module allow the system to generate appropriate action responses in view of the alarms. Some event handler function modules are also used by user requests to generate reports or custom actions from user interface module 135. The reports function in the user interface module 135 is used to generate usage statistics of the resources, current real-time status of the system for each business transaction or business client, the learning parameters of the intelligent system, and related information. The report can be configured to generate invoices with fee values calculated for the resources used based on a per unit fee established in the SLA. 16 WO 2012/082726 PCT/US2011/064619 [0043] Fig. 2 illustrates an exemplary embodiment of the methods and systems 200 of this disclosure. A business client 202 defines the SLA 208 along with the business policies 210 and the business rules 212. This can be done on a web-enabled software application on the client frontend as illustrated in Fig. 1 or by mutual agreements between the business client and the IT service provider. These definitions are then communicated to the cloud services gateway 204. Manual overrides to the business rules or the AIM can be executed by direct input into the software user interface 214. The service governor 224 software module of the disclosure is resident on the gateway for the datacenter operations as illustrated in Fig. 1. This exemplary service governor software module accepts abstract business rules and policy statements from the business client 202 through the input module 216 and computes the abstract statements to application logic for the AIM modules 226. The abstract business statements may specify exemplary business limitations, such as a transaction priority (e.g., in an e-commerce application, ordering can take priority over payment, or tracking status transactions). An exemplary application logic 500 generated using the input business rules and business policy is illustrated in Fig. 5a. The application logic is then forwarded to an appropriate AIM 226 for a selected cloud site. This logic is stored in the AIM for future implementation. It is appreciated that a failure in the service governor module 224 will not affect the functioning of the backend resources in the datacenter 206, as a result of the storing the application logic in the AIM modules 226. [0044] The exemplary embodiments of the methods described herein enable a single service governor 224 module resident in the cloud services gateway 204 to control multiple AIM modules 226 located in the service gateway. Alternatively, it is appreciated that the AIM modules can be resident in a user interface at the datacenter/cloud resources 206 for each of a number of cloud sites. A cloud site, according to the exemplary embodiments herein, is a geographically disparate location comprising a number of backend computing devices to perform the functional requirements of a datacenter. The backend computing devices may be further divided in a multi-tier architecture as discussed above with reference to Fig. 1. The AIM 226 can be autonomous software enabled control module that can function independent of the service governor module to allocate physical and virtual resources of a each respective cloud resource sites 206. The AIM module converts the application logic from the service governor module into a resource specific computer-coded 17 WO 2012/082726 PCT/US2011/064619 logic 510 as illustrated in Fig. 5b. The exemplary embodiments in Fig. 2, also illustrates an option of implementing business rules/business policies via a user interface, where the user interface interacts with multiple service governor software modules 224 in different cloud gateways 204 or the same cloud gateway. Such an implementation would enable separation of data and resources for different business clients within a private or public cloud. A private cloud is a method of restricting a set of cloud resources to a single business client (e.g., a single client company), versus, a public cloud, which allows multiple business clients to share a single set of cloud resources. [0045] Further, according to an exemplary embodiment, each AIM module 226 communicates with an orchestrating and provisioning tool 232. The orchestrating and provisioning tool 232 is a software module that is responsible for implementing the computer-coded logic from AIM module associated with the cloud site 206. Exemplary cloud sites A, B, to X 206, are used to demonstrate the exemplary architecture of the system of this disclosure. The physical and virtual resources 234 are monitored by a monitoring software sub-module in each AIM module 226. This exemplary architecture allows different business transactions to access different cloud sites at any given time. Further, all the business transaction requirements, as well as the resource requirements pass through the central gateway software module 204 for complete control over remote cloud sites. An analytics software module 228 analyzes the usage pattern information from the monitoring software sub-module and initiates the alarm processes 230, in the event of a resource overuse, under-use, or other related error types. The analytics module keeps track of the service governor 224 requirements set forth by the business rules from the business client to trigger a related alarm based on the error type. The event handler functions module 220 comprises software code in the form of automated software functions to inform the other sub-modules in the service governor 224 of the alarm generated. In response, the service governor set new business rules, generated automatically, or uses manual overrides to correct the respective error type. All events generated by the alarm, the response, and the resource usage is stored in the storage database 218 for future reporting by the reports module 222. [0046] The method and systems illustrated in Fig 2 also enables a business client to control the resources of multiple cloud sites for the client data. The business client 202 can 18 WO 2012/082726 PCT/US2011/064619 choose to implement certain transaction on a different cloud site, depending on the costs associated with the physical resources (e.g., energy costs, data storage costs, etc.). The AIM module 226 maintains computer-coded resource policies for monitoring and adjusting resources 234 of its connected cloud site 206. The resource policies can be updated using the computer-coded business rules from the service governor 224 at any time during the operation of the datacenter. However, once the resource policy is set at the respective AIM modules, and should the service governor fail, the AIM modules will continue to control the backend resources at its respective cloud sites till a new rule is issued. [0047] Fig. 3 illustrates an exemplary embodiment of a method 300 for managing the backend information technology infrastructure by automatically adapting hardware and software resources to the dynamic real-time business requirements. Fig. 3 is an exemplary implementation of the methods and systems disclosed herein for a single AIM module connected to its respective cloud resources 306. It is appreciated that this exemplary embodiment can be extended to include multiple cloud sites, with multiple AIM modules, where each AIM module controls its respective cloud site, via an orchestrating and provisioning tool 346. This extension to multiple sites is illustrated in Fig. 2 as discussed above. A business client 302 defines the SLA 308 along with the business policies 310 and the business rules 312. This can be done on a web-enabled software application on the client frontend as illustrated in Fig. 1 or by mutual agreements between the business client and the IT service provider. These definitions are then communicated to the cloud services gateway 304. Alternatively, the definitions can be made via an e-mail that is then deconstructed and its contents are automatically recognized by the input module 316 of the cloud services gateway 304. Both the cloud services gateway 304 and the business client 302 can be computing devices as described in Fig. 1. If the business rules, business policy and the SLA are identified by an analyst with the service provider, the analyst can provide the information directly to the user interface module 314. [0048] In one embodiment, the business rules 312 are defined so as to convert human readable logic for business policies 310 into application logic for computer implementation via an automated service governor software module 324. The service governor software module 324 works with an AIM software module 326 which comprises smaller modules for resource discovery 330, monitoring 332, and management 328. The service governor 19 WO 2012/082726 PCT/US2011/064619 module further comprises a business rules engine module 320 and a business rules manager module 318 which feeds the application logic form of the business rules (computer-coded business rules and resource policies) to the AIM module 326 for deployment to the backend hardware and software resources in the cloud resources 306. The AIM module deploys the application logic form of rules via orchestrating and provision modules 346. The computer coded business rules are defined in the business rules engine module 320 while the autonomous computer-coded resource policies are defined, with managing parameters, in the business rules manager 318. By default, the automatic actions of module 324 select a response to an alarm from a database of previous computer-coded business rules in the business rules engine 320 via the automatic actions module 322. However, the business rules engine 320 can be forced to accept a custom rule from module 322, where the custom rule is defined by a user on manual intervention as a result of the alarm. [0049] In another exemplary embodiment, the human-readable logic of the business rule can be converted to application-logic with added parameters (managing and limiting) which define the intended backend resources, user type, data, time, and priority of the transaction that the business rule is intended to cover. The conversion occurs at module 324 and the application logic business rule output, also called a computer-coded business rule, is stored in the business rules engine 320. The business rules manager 318 generates cloud resource specific computer-coded resource policies which are limited by the computer coded business rules. The managing parameters in the computer-coded resource policies are tied to the individual resources (e.g., Apache server, Java server) and define the number of available instances, the status of the resources and other related information. The computer coded business rule limits this information with priority, data and time information for allocation of resources tied to a particular business transaction. [0050] The business rules manager 318 interacts with the AIM module 326 to manage, discover, and monitor the datacenter or cloud resources 306. When a new business client is introduced into the system, the discover datacenter resources 330 module sends a request to the orchestrating and provisioning module 346 in the cloud resources 306 asking the module to determine the resources available, the time of availability, and capacities. This information, along with the new client business rules 310 and resource policies from module 312 is used to allocate resources from the cloud resources 306 for use by the business client 20 WO 2012/082726 PCT/US2011/064619 during the business transactions. In other embodiments, once a single transaction has been processed, the monitoring module 332 keeps track of the utilization of each of the resources focusing on several features including energy usage, processor (CPU) usage and memory usage among other available features. [0051] In an exemplary embodiment, the AIM is an autonomous software module capable of automatically controlling the resources of its respective cloud site using previously set business rules, even if the service governor fails to provide new rules. The monitoring module 332 stores the computer coded business rules application logic from the service governor 324, and functions autonomously in implementing the business rules. The business rules are combined with resource policies from the service governor to optimize the use of the respective cloud site 306 resources 344, 348, and 350. Should the service governor software module fail to function correctly (e.g., fails to issue new rules), the monitoring module 324 continues to monitor and control the resource usage at the respective cloud site 306. In the event of a resource error, the monitoring module 324 intimates the managing module 328 directly for new rules to re-allocate the datacenter resources 328. This module 328 then uses the stored business rules and resource policy logic to generate a new resource usage rule, thereby correcting the error generated during the monitoring phase. In an exemplary implementation of the service governor, the software modules of the service governor can be software coded using a Java stack in a Windows or Linux operating system machine. [0052] Further, the analytics module 334 analyzes the raw numbers from the monitoring module 332 using the computer-coded business rules from the service governor 324 to determine if the resources are within the rule metrics and generally within the SLA requirements. If the analytics module 334 determines that the resources are under-used, over-used, that the rules do not match historical resolutions, or other such noteworthy occurrences are noted, an alarm 336 is triggered. The alarm could be a message to the system administrator via the user interface module 314, an e-mail sent to a predetermined list, a short message service ("SMS") message to one or more recipients, an instant message ("IM"), or the like. [0053] In further embodiments, the event handler function module 338 monitors the alarms and, after reviewing the available actions, triggers a pre-set response. In one 21 WO 2012/082726 PCT/US2011/064619 embodiment, the module 336 could trigger an alarm to the system administrator through event handler 338, and the system administrator can manually edit the computer-coded business rules from the rules engine 320 or change the custom rules for the business policy via custom rules module 322, thereby setting new rules for the AIM module 326 to facilitate reallocation of the cloud resources for the transaction. In some embodiments, the alarm may be registered at the event handler function module 338 which reviews the alarm and triggers an automated intelligent function in custom rules module 322 within the service governor 324 to select a new computer-coded business rule from the business rules engine 320, which then limits and monitors the computer-coded resource policies to prevent an alarm. This limitation method by the computer-coded business rules can cause an intervention at the AIM module 370 and an adjustment of the resource usage to turn off the alarm. By way of example, without limitation, the resource usage should be above 50% and below 90% for each of the features disclosed above, such as energy usage, processor (CPU) usage and memory usage, for each of these resources. [0054] Further, as illustrated in Fig. 3, the alarm may also add information from the analytics module to the storage database 342. The storage database 342 interacts with the user interface module 314 to present the user with real-time information on rules, resources and analytics. Should the user desire a report of a particular rule implementation, a general policy implementation comprising a number of rules within the policy, or the like, the reports module 340 can be used to combine certain elements from storage database 342 into a human-readable report for the user. Alternatively, if the service provider needs to provide a monthly usage invoice to the business client, the reports module 340 can be used in conjunction with the SLA fee terms from the SLA input 316 to calculate the fee for resource usage during a particular period. [0055] Fig. 4 is an illustration of the use of the system 400 during a business transaction according to one embodiment. Fig. 4 is an exemplary implementation of the methods and systems disclosed herein for a business transaction, and its lifecycle with a single AIM module 444 and a single cloud site 464. It is appreciated that this exemplary embodiment can be extended to include business transactions to multiple cloud sites, with multiple AIM modules, where each AIM module controls its respective cloud site, via an orchestrating and provisioning tool 472. In the illustrated embodiment, the business client 22 WO 2012/082726 PCT/US2011/064619 owns a web-enabled banking business application 404, such as a website operated by an IT service provider, from which the business client offers its customers services in the form of business transaction services 408. As illustrated in the figure, an exemplary banking business application 404 comprises multiple business transaction options, including an account balance inquiry in the transaction services 408. The user chooses this service and enters the specific account for which the balance inquiry is being requested. The cloud services gateway 412 comprises the service governor module 416 that determines the computer-coded business rules that should apply to the transaction depending on the user (e.g., frequent user, premium user, time of transaction, etc.). The business rules engine 424 generates the computer-coded business rule containing the transaction information and the metrics for limiting the computer-coded resource policies from the business rules manager 420. The supplemented computer-coded resource policies are then forwarded to the AIM module 444 which determines the resources to be used according to the business rule for the chosen transaction. [0056] Fig. 4 further illustrates the orchestrating module 472 which performs the required transaction processes using the resources required by the managing parameters in the computer-coded resource policies, thereby incorporating in the database tier server 475 and the application tier server 476 to respond to the business transaction request. During this data-mining operation, the monitoring module 452 monitors the time to response, the processor consumption, and memory usage, among other metrics, for the transaction. As the number of transactions increases because of additional users on different computing devices, and more resources are being consumed, the analytics module 456 combines information from the managing and limiting parameters with the utilization parameters from monitoring module 452 to determine if the system is functioning within the correct utilization metrics defined by the SLA and the business rules for the transaction load. When alarms are triggered, the event handler function module 432 reviews the alarm and responds with an action to module 428 for manual or automated responses. The business rules manager 420 is initiated and the rules are altered by an intelligent learning function or manual function that feeds the business rules engine 424. The newly altered computer-coded business rules add new limitation parameters to the computer-coded resource policies and the computer coded resource policies are applied to the AIM module 444 to rectify the alarm. In the 23 WO 2012/082726 PCT/US2011/064619 absence of an alarm, the monitoring continues normally. The status of the system is also updated in the storage database 440. [0057] The embodiments described above are intended to be exemplary. One skilled in the art should recognize that numerous alternative components and embodiments that may be substituted for the particular examples described herein and still fall within the scope of the invention. 24

Claims

1. A computer-implemented method for automatically adapting a service provider's cloud resources to the requirements of business transactions, the method comprising: providing, by a computer, a first computer-coded business rule, wherein the first computer-coded business rule comprises limiting parameters related to at least one business transaction; providing, by the computer, at least one computer-coded resource policy, wherein the computer-coded resource policy comprises managing parameters to manage the distribution of cloud resources within the limiting parameters in the first computer-coded business rule; monitoring, by the computer, the utilization parameters of the cloud resources for the business transaction, wherein an alarm is generated when the utilization parameters exceed the limiting parameters defined in the first computer-coded business rule; updating, by the computer, the limiting parameters of the first computer coded business rule with new limiting parameters in response to the alarm, thereby generating a second computer-coded business rule; and rendering, by the computer, the second computer-coded business rule, wherein the managing parameters of the computer-coded resource policy manage the distribution of cloud resources within the limiting parameters in the second computer-coded business rule.

2. The method according to claim 1, wherein the second computer-coded business rule is generated by using an intelligent learning software module that reviews the alarm and implements one of plurality of historic computer-coded business rule in response to the alarm. 25 WO 2012/082726 PCT/US2011/064619

3. The method according to claim 2, wherein the intelligent learning software module is based on a neural networks model.

4. The method according to claim 1, wherein the second computer-coded business rule is manually defined after a manual review of the alarm.

5. The method according to claim 1, wherein the improper utilization parameters of the cloud resources includes a measure of consumption of resource features such as the central processor unit (CPU), the main memory, and the energy for each resource.

6. The method according to claim 5, wherein the improper utilization of cloud resources is a measure of consumption that is more than 90% and less than 50% of the maximum availability of each of the features of each of the resources.

7. The method according to claim 1, wherein the cloud resources includes multi-tier cloud resources comprising web-tier servers, an application tier servers and a database tier servers.

8. The method according to claim 1, wherein the limiting parameters and the managing parameters includes minimum and maximum scalable values, threshold values, CPU utilization parameters, implementation data and time, and priority values.

9. The method according to claim 1, wherein the utilization parameters of the cloud resources includes energy consumption, processor (CPU) utilization, memory utilization, time schedules, and heat generated. 26 WO 2012/082726 PCT/US2011/064619

10. The method according to claim 1, wherein the alarm triggered during the analyzing step is in the form of an e-mail, voice message or a message to the system administrator.

11. A computer-implemented system for automatically adapting a service provider's cloud resources to the requirements of business transactions, the system comprising: providing, in a computer, a first computer-coded business rule, wherein the first computer-coded business rule comprises limiting parameters related to at least one business transaction; providing, by the computer, at least one computer-coded resource policy, wherein the computer-coded resource policy comprises managing parameters to manage the distribution of cloud resources within the limiting parameters in the first computer-coded business rule; monitoring, by the computer, the utilization parameters of the cloud resources for the business transaction, wherein an alarm is generated when the utilization parameters exceed the limiting parameters defined in the first computer-coded business rule; updating, by the computer, the limiting parameters of the first computer coded business rule with new limiting parameters in response to the alarm, thereby generating a second computer-coded business rule; and rendering, by the computer, the second computer-coded business rule, wherein the managing parameters of the computer-coded resource policy manage the distribution of cloud resources within the limiting parameters in the second computer-coded business rule.

12. The system according to claim 11, wherein the second computer-coded business rule is generated by using an intelligent learning software module that reviews the alarm and implements one of plurality of historic computer-coded business rule in response to the alarm. 27 WO 2012/082726 PCT/US2011/064619

13. The system according to claim 12, wherein the intelligent learning software module is based on a neural networks model.

14. The system according to claim 11, wherein the second computer-coded business rule is manually defined after a manual review of the alarm.

15. The system according to claim 11, wherein the improper utilization parameters of the cloud resources includes a measure of consumption of resource features such as the central processor unit (CPU), the main memory, and the energy for each resource.

16. The system according to claim 15, wherein the improper utilization of cloud resources is a measure of consumption that is more than 90% and less than 50% of the maximum availability of each of the features of each of the resources.

17. The system according to claim 11, wherein the cloud resources includes multi-tier cloud resources comprising web-tier servers, an application tier servers and a database tier servers.

18. The system according to claim 11, wherein the limiting parameters and the managing parameters includes minimum and maximum scalable values, threshold values, CPU utilization parameters, implementation data and time, and priority values.

19. The system according to claim 11, wherein the utilization parameters of the cloud resources includes energy consumption, processor (CPU) utilization, memory utilization, time schedules, and heat generated. 28 WO 2012/082726 PCT/US20111/064619

20. The system according to claim 11, wherein the alarm triggered during the analyzing step is in the form of an e-mail, voice message or a message to the system administrator. 29