Patent Application
20100280863
The invention relates to methods of generating a model representing at least part of a computer based business process having a number of functional steps, from existing source content specifying the functional steps, and from source content of software entities implementing the functional steps, and relates to corresponding systems and software.
Physical IT (information technology) infrastructures are difficult to manage. Changing the network configuration, adding a new machine or storage device are typically complicated and error prone manual tasks. In most physical IT infrastructure, resource utilization is very low: 15% is not an uncommon utilization for a server, 5% for a desktop. To address this, modern computer infrastructures are becoming increasingly (re)-configurable and more use is made of shared infrastructure in the form of data centres provided by service providers.
Hewlett Packard's UDC (Utility Data Centre) is an example which has been applied commercially and allows automatic reconfiguration of physical infrastructure: processing machines such as servers, storage devices such as disks, and networks coupling the parts. Reconfiguration can involve moving or starting software applications, changing allocations of storage space, or changing allocation of processing time to different processes for example. Another way of contributing more reconfigurability, is by allowing many “virtual” computers to be hosted on a single physical machine. The term “virtual” usually means the opposite of real or physical, and is used where there is a level of indirection, or some mediation between the resource user and the physical resource.
In addition some modern computing fabrics allow the underlying hardware to be reconfigured. In once instance the fabric might be configured to provide a number of four-way computers. In another instance it might be re-configured to provide four times as many single processor computers.
It is extremely complex to model the full reconfigurability of the above. Models of higher level entities need to be recursive in the sense of containing or referring to lower level entities used or required to implement them (for example a virtual machine VM, may operate faster or slower depending on what underlying infrastructure is currently used to implement it (for example hardware partition nPAR or virtual partition vPAR, as will be described in more detail below). This means a model needs to expose the underlying configurability of the next generation computer fabrics—an nPAR consists of a particular hardware partition. This makes the models so complex that it becomes increasingly difficult for automated tools (and humans) to understand and process the models, to enable design and management of: a) the business process, b) the application and application configuration, and c) the infrastructure and infrastructure configuration.
The need to model the full reconfigurability and recursive nature of a system is exemplified in the DMTF's profile for “System Virtualization, Partitioning and Clustering”: http://www.dmtf.org/apps/org/workgroup/redundancy/
Another example of difficulties in modelling is WO2004090684 which relates to modeling systems in order to perform processing functions. It says “The potentially large number of components may render the approach impractical. For example, an IT system with all of its hardware components, hosts, switches, routers, desktops, operating systems, applications, business processes, etc. may include millions of objects. It may be difficult to employ any manual or automated method to create a monolithic model of such a large number of components and their relationships. This problem is compounded by the typical dynamic nature of IT systems having frequent adds/moves/changes. Secondly, there is no abstraction or hiding of details, to allow a processing function to focus on the details of a particular set of relevant components while hiding less relevant component details. Thirdly, it may be impractical to perform any processing on the overall system because of the number of components involved.”
There have been attempts to automatically and rapidly provide computing infrastructures: HP's Utility Data Center, HP Lab's SoftUDC, HP's Caveo and Amazon's Elastic Compute Cloud (which can be seen at http://www.amazon.com/gp/browse.html?node=201590011). All of these provide computing infrastructures of one form or another, and some have been targeted at testers and developers, e.g. HP's Utility Data Center.
Aris from IDS-Scheer is a known business process modelling platform having a model repository containing information on the structure and intended behaviour of the system. In particular, the business processes are modelled in detail. It is intended to tie together all aspects of system implementation and documentation.
Aris UML designer is a component of the Aris platform, which combines conventional business process modelling with software development to develop business applications from process analysis to system design. Users access process model data and UML content via a Web browser, thereby enabling processing and change management within a multi-user environment. It can provide for creation and communication of development documentation, and can link object-oriented design and code generation (CASE tools). It relies on human entry of the models.
An object is to provide improved apparatus or methods. In one aspect the invention provides:
A method of generating a model representing at least part of a computer based business process having a number of functional steps, from existing source content specifying the functional steps, and from source content of software entities implementing the functional steps, the source content having annotations added, to provide information for modelling, the method having the steps of:
collecting the information provided by the annotations, and
using the information collected by the collector, to generate representations of the functional steps and software entities which implement the functional steps, and arranged to incorporate these representations in the model.
Using annotations for discovering the information about the business process and the software entities implementing the functional steps can enable modelling to be carried out more efficiently and flexibly, as the annotations need not be restricted to codes or symbols or structures of the language of the source content. Hence the annotations can use concepts closer to those in the model being generated. Compared to generating the model manually, less input from scarce skilled humans is needed, and the risk of errors can be reduced, leading to better predictions of performance from the model. This in turn can lead to a better or best configuration of the software or the computing infrastructure, which can lead to more efficient usage of available resources for live deployments, and hence lower costs. This is particularly useful for the common situation where many business processes share the available resources.
Embodiments of the invention can have any additional features, without departing from the scope of the claims, and some such additional features are set out in dependent claims and in embodiments described below.
Another aspect provides software on a machine readable medium which when executed carries out the above method.
Another aspect provides a system for generating a model representing at least part of a computer based business process having a number of functional steps, from existing source content specifying the functional steps, and from source content of software entities implementing the functional steps, the source content having annotations added, to provide information for modelling, the system having: a collector arranged to collect the information provided by the annotations, and a modeller arranged to use the information collected by the collector, to generate representations of the functional steps and software entities which implement the functional steps, and arranged to incorporate these representations in the model.
Other aspects can encompass corresponding steps by human operators using the system, to enable direct infringement or inducing of direct infringement in cases where the infringers system is partly or largely located remotely and outside the jurisdiction covered by the patent, as is feasible with many such systems, yet the human operator is using the system and gaining the benefit, from within the jurisdiction. Other advantages will be apparent to those skilled in the art, particularly over other prior art. Any of the additional features can be combined together, and combined with any of the aspects, as would be apparent to those skilled in the art. The embodiments are examples only, the scope is not limited by these examples, and many other examples can be conceived within the scope of the claims.
Specific embodiments of the invention will now be described, by way of example, with reference to the accompanying Figures, in which:
“Annotation” is intended encompass any extra information added to the source content of any software entity used directly or indirectly by a business process in order to describe the entity in terms of a set of concepts used by a software model of the business process and its associated software components. Annotations may be used by a compiler or other processor of the source content to modify the process of generating executable logic from the source content in order to change the behaviour of that executable logic to allow extraction of the information contained in the annotations.
“non-functional requirements” can encompass how well the functional steps are achieved, in terms such as performance, security properties, cost, availability and others. It is explained in Wikipedia (http://en.wikipedia.org/wiki/Non-functional_requirements) for non-functional requirements as follows—“In systems engineering and requirements engineering, non-functional requirements are requirements which specify criteria that can be used to judge the operation of a system, rather than specific behaviors. This should be contrasted with functional requirements that specify specific behavior or functions. Typical non-functional requirements are reliability, scalability, and cost. Non-functional requirements are often called the ilities of a system. Other terms for non-functional requirements are “constraints”, “quality attributes” and “quality of service requirements”.”
Functional steps can encompass any type of function of the business process, for any purpose, such as interacting with an operator receiving inputs, retrieving stored data, processing data, passing data or commands to other entities, and so on, typically but not necessarily, expressed in human readable form . . . .
“Deployed” is intended to encompass a modelled business process for which the computing infrastructure has been allocated and configured, and the software application components have been installed and configured ready to become operational. According to the context it can also encompass a business process which has started running.
“suitable for automated deployment” can encompass models which provide machine readable information to enable the infrastructure design to be deployed, and to enable the software application components to be installed and configured by a deployment service, either autonomously or with some human input guided by the deployment service.
“business process” is intended to encompass any process involving computer implemented steps and optionally other steps such as human input or input from a sensor or monitor for example, for any type of business purpose such as service oriented applications, for sales and distribution, inventory control, control or scheduling of manufacturing processes, for example. It can also encompass any other process involving computer implemented steps for non business applications such as educational tools, entertainment applications, scientific applications, any type of information processing including batch processing, grid computing, and so on. One or more business process steps can be combined in sequences, loops, recursions and branches to form a complete Business Process. Business process can also encompass business administration processes such as CRM, sales support, inventory management, budgeting, production scheduling and so on, and any other process for commercial or scientific purposes such as modelling climate, modelling structures, or modelling nuclear reactions.
“application components” is intended to encompass any type of software element such as modules, subroutines, code of any amount usable individually or in combinations to implement the computer implemented steps of the business process. It can be data or code that can be manipulated to deliver a business process step (BPStep) such as a transaction or a database table. The Sales and Distribution (SD) product produced by SAP is made up of a number of transactions each having a number of application components for example.
“unbound model” is intended to encompass software specifying in any way, directly or indirectly, at least the application components to be used for each of the computer implemented steps of the business process, without a complete design of the computing infrastructure, and may optionally be used to calculate infrastructure resource demands of the business process, and may optionally be spread across or consist of two or more sub-models. The unbound model can also specify the types or versions of corresponding execution components such as application servers and database servers, needed by each application component, without specifying how many of these are needed for example.
“grounded model” is intended to encompass software specifying in any way, directly or indirectly, at least a complete design of the computing infrastructure suitable for automatic deployment of the business process. It can be a complete specification of a computing infrastructure and the application components to be deployed on the infrastructure.
“bound model” encompasses any model having a binding of the Grounded Model to physical resources. The binding can be in the form of associations between ComputerSystems, Disks, StorageSystems, Networks, NICS that are in the Grounded Model to real physical parts that are available in the actual computing infrastructure. “infrastructure design template” is intended to encompass software of any type which determines design choices by indicating in any way at least some parts of the computing infrastructure, and indicating predetermined relationships between the parts. This will leave a limited number of options to be completed, to create a grounded model. These templates can indicate an allowable range of choices or an allowable range of changes for example. They can determine design choices by having instructions for how to create the grounded model, or how to change an existing grounded model.
“computing infrastructure” is intended to encompass any type of resource such as hardware and software for processing, for storage such as disks or chip memory, and for communications such as networking, and including for example servers, operating systems, virtual entities, and management infrastructure such as monitors, for monitoring hardware, software and applications. All of these can be “designed” in the sense of configuring and/or allocating resources such as processing time or processor hardware configuration or operating system configuration or disk space, and instantiating software or links between the various resources for example. The resources may or may not be shared between multiple business processes. The configuring or allocating of resources can also encompass changing existing configurations or allocations of resources. Computing infrastructure can encompass all physical entities or all virtualized entities, or a mixture of virtualized entities, physical entities for hosting the virtualized entities and physical entities for running the software application components without a virtualized layer.
“parts of the computing infrastructure” is intended to encompass parts such as servers, disks, networking hardware and software for example.
“server” can mean a hardware processor for running application software such as services available to external clients, or a software element forming a virtual server able to be hosted by a hosting entity such as another server, and ultimately hosted by a hardware processor.
“AIService” is an information service that users consume. It implements a business process.
“Application Constraints Model” can mean arbitrary constraints on components in the Customized Process, Application Packaging and Component Performance Models. These constraints can be used by tools to generate additional models as the MIF progresses from left to right.
“ApplicationExecutionComponent” is for example a (worker) process, thread or servlet that executes an Application component. An example would be a Dialog Work Process, as provided by SAP.
“ApplicationExecutionService” means a service which can manage the execution of ApplicationExecutionComponents such as Work Processes, servlets or data-base processes. An example would be an Application Server as provided by SAP. Such an application server includes the collection of dialog work processes and other processes such as update and enqueue processes as shown in the diagram of the master application server. (
“Application Packaging Model” is any model which describes the internal structure of the software: what products are needed and what modules are required from the product, and is typically contained by an unbound model.
“Application Performance Model” means any model which has the purpose of defining the resource demands, direct and indirect, for each Business process (BP) step. It can be contained in the unbound model.
“Component Performance Model” can mean any model containing the generic performance characteristics for an Application Component. This can be used to derive the Application Performance Model (which can be contained in the unbound model), by using the specific Business process steps and data characteristics specified in the Custom Model together with constraints specified in the Application Constraints Model.
“Custom Model” means a customized general model of a business process to reflect specific business requirements.
“Deployed Model” means a bound model with the binding information for the management services running in the system.
“Candidate Grounded Model” can be an intermediate model that may be generated by a tool as it transforms the Unbound Model into the Grounded Model.
“Grounded Component” can contain the installation and configuration information for both Grounded Execution Components and Grounded Execution Services, as well as information about policies and start/stop dependencies.
“Grounded Execution Component” can be a representation in the Grounded Model of a (worker) process, thread or servlet that executes an Application Component.
“Grounded Execution Service” is a representation in the Grounded Model of the entity that manages the execution of execution components such as Work Processes, servlets or database processes.
“Infrastructure Capability Model” can be a catalogue of resources that can be configured by the utility such as different computer types and devices such as firewalls and load balancers.
MIF (Model Information Flow) is a collection of models used to manage a business process through its entire lifecycle.
The present invention can be applied to many areas, the embodiments described in detail can only cover some of those areas. It can encompass modeling dynamic or static systems, such as enterprise management systems, networked information technology systems, utility computing systems, systems for managing complex systems such as telecommunications networks, cellular networks, electric power grids, biological systems, medical systems, weather forecasting systems, financial analysis systems, search engines, and so on. The details modelled will generally depend on the use or purpose of the model. So a model of a computer system may represent components such as servers, processors, memory, network links, disks, each of which has associated attributes such as processor speed, storage capacity, disk response time and so on. Relationships between components, such as containment, connectivity, and so on can also be represented.
An object-oriented paradigm can be used, in which the system components are modeled using objects, and relationships between components of the system are modeled either as attributes of an object, or objects themselves. Other paradigms can be used, in which the model focuses on what the system does rather than how it operates, or describes how the system operates. A database paradigm may specify entities and relationships. Formal languages for system modelling include text based DMTF Common InformationModel (CIM), Varilog, NS, C++, C, SQL, or graphically expressed based schemes.
Some examples of additional features for dependent claims are as follows:
The modeller can be arranged to generate for the model a representation of demands on computing infrastructure by the software entities. This is useful to enable a richer model which can be used in reconfiguring the computing infrastructure to meet the demands more efficiently, or to predict alterations in such demands when reconfiguring the business process or the software entities for example.
At least some of the annotations can be descriptive annotations having statically determinable information identifying the functional steps and software entities for implementing the functional steps, and the collector can be arranged to read the source content to collect the information. This can enable the modeller to model some of the structure of software entities, other than behavioural information such as demands on computing infrastructure which depend on state or usage patterns for example.
The descriptive annotations can use types of entities and types of relationships where the types correspond to types used in the model. This means the descriptions by the descriptive annotations are oriented from the perspective of the model. This can help enable the modeller to generate parts of the model more efficiently. This approach can provide consistency which is particularly useful where the source content is in more than one format.
At least some of the annotations can be monitoring annotations arranged to specify instrumentation points that modify the run-time behaviour of the business process to generate information relating to run-time behaviour, and the collector can be arranged such that at least some of the information collected by the collector is the information relating to run-time behaviour. This can enable richer models to be generated. Not all relationships between business processes and software entities may be known statically and so some can be discovered at run time. For example the set of functional steps (business process steps) in a business process, and their sequence or probability may depend on user behaviour or the state of the system. The use of monitoring annotations for discovering the behaviour can enable the richer modelling to be carried out more efficiently and flexibly, as the annotations need not be restricted to codes or symbols or structures of the language of the source content.
The modeller can be arranged to use the collected run-time behaviour information, to generate a representation of demands on the computing infrastructure by the software entities. This is particularly useful information to enable more complete models which can help make more efficient usage of available computing infrastructure.
The modeller can be arranged to correlate the collected information on run-time behaviour with corresponding representations of software entities and functional steps in the model. This can enable the model to be more complete in modelling behaviour, which can be useful to predict demands on computing infrastructure for example. The information generated by the monitoring events can be arranged to contain modelling data contained in the annotations, to help make the correlation easier.
A level of detail of the monitoring of run-time behaviour can be configurable. This can enable the monitoring to be focussed on areas of interest, which is particularly useful for more complex systems which could otherwise generate too much information.
The system can have a documentation generator, arranged to generate human readable documentation relating to the functional steps and the software entities for implementing the functional steps, from the information collected. This can help enable this important task to be carried out more efficiently. Such documentation can be both on the information that can be discovered statically and also information discovered at runtime. For example, it could encompass a report on what functional steps were actually executed and their demands
The model can comprise an unbound model, and a grounded model, the modeller being arranged to generate the unbound model, and the system further having a design service to generate a mapping of logical components of the unbound model on to computing infrastructure, to provide a grounded model of the business process, suitable for automated deployment on the computing infrastructure. This can help exploit some of the advantages of modelling, by providing a way to find a better or best configuration of the software or the mapping to the computing infrastructure, to lead to more efficient usage of available resources for live deployments. The mapping could have for example a mapping of a logical infrastructure component used to host a software component, to a specific type of physical infrastructure. It could be in the form of a template, or alternatively the annotations could contain such information. This could be seen as a refinement of the template, or as an additional set of constraints. It is conceivable to have a complete template included in the annotations. The unbound model or the grounded model can be used to develop and test alternatives to the existing business process in terms of changes to functional steps, software or computing infrastructure, rather than risking untested changes to the existing business process.
The annotations can be in the source content that specifies the business process and the source content of the software entities that implement that business process. Both can be important if the relationship between the two is relevant, such as where some operators are only interested in the sequence of business process steps, and others are interested in the underlying software entities and lower layers.
The service provider could offer to deploy on dedicated hardware local to the enterprise, and yet provide ongoing management by a service provider. Reference is made to above referenced copending application number 200702144 for more details of examples of this. This can increase complexity for the service provider, in which case, the advantages of using annotations as described can become all the more valuable.
Where a 3-D visual interface is provided with a game server to enable multiple developers to work on the same model and see each others changes, developers can navigate complex models more quickly. Reference is made to above referenced copending application number 200702356 for more details of examples of this. As the complexity increases, again the advantages of using annotations as described can become all the more valuable.
Where an enterprise interface is provided to enable the enterprise to customise the non functional requirements independently of each other, then the service provider may be faced with more complex development effort to meet the customised requirements. Reference is made to above referenced copending application number 200702363 for more details of examples of this. Combining this with the use of annotations as described can assist developers in documentation and model generation and help deal with the more complex development effort.
Where the operation of the business process can be simulated or where multiple test deployments can be made in parallel, development can be accelerated. Reference is made to above referenced copending application number 200702377 for more details of examples of this. Combining this with the use of annotations as described can assist developers and enable the advantages of both to be enhanced.
Setting up of a development environment can be facilitated by providing a predetermined mapping of which tools are appropriate for a given development purpose and given part of the model, or by including models of tools to be deployed with the model. Reference is made to above referenced copending application numbers 200702145, and 200702601 for more details of examples of this. Combining this with the use of annotations as described can assist developers further and so enable the advantages of both to be enhanced.
In the embodiments described, annotations are used in various model based approaches. A general aim of these model based approaches is to enable development and management of the business process to provide matched changes to three main layers: the functional steps of the process, the applications used to implement the functional steps of the process, and configuration of the computing infrastructure used by the applications. Such changes are to be carried out automatically by use of appropriate software tools interacting with models modelling the above mentioned parts. Until now there has not been any attempt to link together tools that integrate business process, application and infrastructure management through the entire system lifecycle.
A model-based approach for management of such complex computer based processes will be described. Such models can have structured data models in CIM/UML to model the following three layers:
A model is an organized collection of elements modelled in UML for example. A goal of some embodiments is to use these data models for the automated on-demand provision of enterprise applications following a Software as a service (SaaS) paradigm.
The design of the hardware infrastructure and software landscape for large business processes such as enterprise applications is an extremely complex task, requiring human experts to design the software and hardware landscape. Once the enterprise application has been deployed, there is an ongoing requirement to modify the hardware and software landscape in response to changing workloads and requirements. This manual design task is costly, time-consuming, error-prone, and unresponsive to fast-changing workloads, functional requirements, and non-functional requirements. The embodiments describe mechanisms to automatically create an optimised design for an enterprise application, monitor the running deployed system, and dynamically modify the design to best meet the non-functional requirements. There are two basic inputs to the design process:
The design process involves the creation of a specification of the hardware and software landscape of the enterprise application that will meet the functional and non-functional requirements described above. This can consist of:
Using Model-Based technologies to automatically design and manage Enterprise applications can offer powerful predictive power, and the capability to automatically design, deploy, modify, monitor, and manage a running system to implement a business process, while minimizing the requirement for human involvement.
The Enterprise application can be modelled at 4 interconnected layers:
This model is called the Enterprise application Model. At each layer, it consists of two sets of models—the Automation Models and the Document Models.
The Automation Models consist of those models described in the MIF (Business Process Model, Custom Model, Unbound Model, Grounded Model, Bound Model, and Deployed Model), that enable the automation of the Enterprise application through its entire lifecycle from design to deployment.
In general, an Automation Model is composed of two categories of sub-models—the Static Model and Operational Model. The Static Model describes the static structure of the system—the selection and configuration options of candidate designs of the Enterprise application. The Operational Model describes the internal structure, run-time operation, and performance demands (such as CPU, memory, disk, or network I/O) of the infrastructure and software. It is these Operational Models that allow simulation and evaluation of how well a candidate design will meet the non-functional requirements of the System.
The output from Monitoring and Reporting Services could also be classified as a special case of the Document Model, describing the run-time behaviour and performance of the system in human-readable form. Enterprise applications are very complex, and the Models underlying the modelling techniques are correspondingly complex and difficult to create. The Models may change over time as systems are modified, patched and redesigned. Additionally, the models may depend on the actual data and configuration contained within a specific System and the observed behaviour of a running system.
In general, much of the detailed structure and parameters of the required models are too complex and dynamic for human beings to generate by hand in a timely fashion. The problem addressed by this invention is how to automatically generate, at least parts of, the Automation and Document Models. The information in the models must be consistent and correlated—activity in one part of the system must be traceable and correlated with related activities. For example, an activity A may result in a cascade of other activities B, C and D; it is desirable that these relationships can be represented at run-time and captured in the models.
Model-Based technologies to automatically design and manage Enterprise applications—see “Adaptive Infrastructure meets Adaptive Applications”, by Brand et al, published as an external HP Labs Tech Report: http://www.hpl.hp.com/techreports/2007/HPL-2007-138.html and incorporated herein by reference, can provide the capability to automatically design, deploy, modify, monitor, and manage a running System to implement a business process, while minimizing the requirement for human involvement.
The embodiments are concerned with providing a mechanism to automatically generate key aspects of the required Automation Models of an Enterprise application, together with additional Document Models to be used by humans to understand and analyse the system. The embodiments describe adding consistent and correlated annotations, Model Mark-up, to the various forms of Source Content for the software of an Enterprise Application. The annotations can describe the structure of the system from the perspective of the models that are to be generated. The models and annotations can share the same concepts, such as Business Process, Business Process Steps, Business Object, and Software Component. Instances of those concept types are described in the annotations, together with the relationships between them. Information is automatically captured from the annotations to create or supplement the required models, using a combination of both static analysis and run-time discovery.
The software of an Enterprise Application can be described by various kinds of Source Content. Typically the Source Content is owned by the Enterprise Application Vendor, who would also be responsible for adding the Model-Markup annotations. There may be several forms of Source Content such as:
Program Code or Program Models may be generated via tools, such as graphical editors, or directly by humans. The syntax and language used to describe Source Content may vary widely. However the Model Mark-up added as annotations to the Source Content, should have consistent semantics, concepts, and identifiers so the various parts of the system can be correlated and analysed. Despite the single conceptual model, the syntactic mechanisms used to add the Model Mark-up would necessarily vary, to be compatible with each of the forms of Source Content.
This figure shows source content A B and C, and corresponding annotations in the form of model mark up A, B and C. In the static analysis, a set of tools shown as model transformation tools, can extract and transform the Model Mark-up in the Source Content into elements of the Automation and Document Models. For example, this can capture the set of Business Processes and Business Steps in a system, and any statically known invocation relationships between them.
Annotation would be used to add information to various parts of the models in the MIF during static analysis. In particular, the annotation describes information that forms parts of the Unbound Model. Some examples of the use of annotation during static analysis are now given, but should not be considered exhaustive and simply illustrative of the principles.
Annotation in the source content of business processes would describe the business processes and business process steps in the terms of the concepts used by the Business and Custom Models—the set of business processes, how they are composed into business process steps, the invocation relationships between these steps and how the business process steps are implemented as application software components. The relationships between Business Processes and Business Process steps can be described statically where they are known by the designer of the business process or business process step. For example that a business process will always make use of a business process step, or that the execution of one business process step always immediately follows the execution of another business process step. There may be situations where these relationships cannot be described and discovered by static analysis, and must be discovered at run-time via the Run-time Model Reporting functionality. For example a business process step may be generic and able to be used in many business processes, where the execution of the business process step is conditional on the run-time state of the system or human actions.
Similarly, annotation in program code or program models would describe the software structure in terms understood by the Application Packaging Model—the other application components an application component depends on, the software module an application component is part of, the software modules an application component depends on, how software modules are packaged into products, and the software service that executes an application component.
A further feature of some embodiments of the invention is to use the same Model Mark-up for run-time discovery and analysis of the system. This is shown in
Another feature is to use the annotations to relate the modelled concepts with measured performance demands placed on the infrastructure by the Software components, so that the resulting models can ultimately relate the Business Processes to infrastructure requirements.
A number of complementary implementation mechanisms are possible for the Run-time Model Reporting functionality, including:
For both mechanisms described above for the Run-time Model Reporting functionality, the Model-Markup explicitly triggers modification of the Source Content or byte code at a specific point in the Source Code. Additionally, the transformation tools may analyse the Source Content directly, for example to put wrappers or traps around significant collections of method calls, such as a specific source file; in this case, the Model-Markup may simply modify this process, for example by specifying the level-of-detail, or naming specific parameters for special reporting treatment.
A feature of some embodiments of the invention is that the level-of-detail or sub-set of information gathered and reported from the generated Run-time Model Reporting is configurable, either statically at generation time or dynamically at run-time. For example level-of-detail for reporting could be for:
The information gathered could be targeted or presented according to views/properties of the architecture or person interested in the information. For example:
Another feature of some embodiments of the invention is to also use the annotations to relate the modelled concepts with measured performance demands placed on the infrastructure by the Software components, so that the resulting models can ultimately relate the Business Processes to infrastructure requirements. This is achieved by supplementing the execution context captured from information in the Markup with information derived from run-time monitoring of the system. For example, the Model-Markup would denote the start and end of a Business Process Step. It would be possible to associate the measured demands on the part of the system that is executing that step with the step itself (e.g. CPU, memory, network I/O) and with the details of the virtual/physical infrastructure, and incorporate this into the generated models to make future performance predictions.
Annotation would be used to provide input to various parts of the models in the MW during runtime discovery analysis. In particular, the annotation describes information that will form parts of the Unbound Model.
Annotation for Run-time Model Reporting in the source content of business processes allow relationships between business processes and business process steps to be discovered at run-time, where these relationships are not known to the designer of the business processes. For example a business process step may be generic and able to be used in many business processes or the execution of the business process step is conditional on run-time state of the system or human actions, and therefore may be used in business processes that were not predicted by the designer of the business process step. The information about these discovered relationships extend and supplement the Business and Custom Models. Examples are now given of how the Business and Custom Models could be extended and supplemented. These examples should not be considered to be exhaustive, but simply illustrative of the principle. The set of business processes actually used by an organisation, the actual set of business process steps used within that business process, and the invocation ordering between these steps can be discovered at run-time from actual use within the organisation. The detailed invocation relationships between business processes that form part of the Custom Model can be measured, leading to more accurate prediction of the future load on the system based on real user behaviour. For example the actual branching probabilities between business process steps, as users make decisions as they progress through the business process, can be substituted into the Custom Model. Similarly, annotation for Run-time Model Reporting in program code or program models would allow discovery of information and relationships used to extend and supplement the representation of the software structure and performance in terms understood by the Custom Model, Application Packaging Model and Application Performance Model, as shown in
This shows steps carried out by a system according to an embodiment. At step 917, the preliminary step of adding annotation to source content of business process functional steps and software entities to identify entities and relationships is shown. This is typically done manually, though it is conceivable to have software to guide the operator and limit the types of annotations to ensure they are consistent and match the layered structure of the model. The same applies to step 923, the preliminary step of adding monitoring annotation to source content to monitor behaviour. This alters the run time behaviour to generate monitoring events. Examples of this are discussed above. The system can then do the static analysis of deriving a structure of entities and relationships from descriptive annotations, by analysing the source content at step 927. This can be done before or possibly after the run time analysis, as shown at steps 930 to 941. The business process or relevant parts of it, are carried out at step 930. The information on behaviour is collected at step 933, and processed at step 937 to correlate the behaviour to modelled entities. Further processing to deduce invocation relationships and demands by given entities on computing infrastructure is carried out at step 941. Step 943 shows incorporating the discovered relationships and demands into an unbound model of the business process.
This figure shows steps carried out by a system according to an embodiment, and showing more details of an example of the run time analysis. The source content with annotations is compiled into executable code at step 947 and loaded onto a target machine. At run time, monitoring annotations pass a reference to a shared model context as a parameter at step 951. The Model Context is a shared repository to store and capture information reported by the Run-time Model Reporting during a related sequence of interactions between modelled entities, and identifies a related set of events from the Run-time Model Reporting for a call chain of related interactions of software components. The Model Context could for example be located within the Model Information Collector. The Model Context can store all of the reported model events for a related set of interactions, such as the call graph between application components resulting from the execution of a business process step in a business process. A reference to the Model Context is passed between applications components to maintain the identifier for the related event sequence. This information includes the details of the business process currently executing, the call chain of business process steps, and the invocation relationships between the application components that implement them. As execution passes from one application component to another, information can be added to the generated Run-time Model Reporting events sent to the Model Context about the details of the execution environment of that component—for example, the software execution service executing that component, the host Operating System, and the details of the host hardware. The information in the Model Context can additionally be supplemented with information from other sources that has been correlated with the information discovered from the Run-time Model Reporting. For example information from a monitoring sub-system for resource utilisation measured on the computing infrastructure such as CPU, memory, or disk I/O, could be added to the Model Context for the correlated set of application component interactions. Events are reported to the model context according to specified level of detail, e.g. amount of cpu/memory/bandwith consumed by each stage in call chain at step 953. Behaviour such as events and performance are correlated to modelled entities at step 957. Then the model discovery service can analyse the model context to record the execution of the business process in terms of reported and correlated events and performance metrics, as shown by step 961. At step 963, tools can use the model context to derive parts of the unbound model such as application performance model, component performance model and customised process model. Examples of these parts of the unbound model will be discussed below in more detail with reference to
Examples will now be given of the kind of annotation that could be added. The examples are not meant to be complete or imply there is only one way of implementing the mechanism—they are simply illustrative of the principles. The annotations are shown in a pseudo XML format. The actual syntax used may be different, to better match the specifics of a particular Source Content type.
The principle is to identify, in the Source Code, instances of the various concepts that will appear in the generated Models of the system that the Source Content implements. For example, Business Process, Business Object, method call, etc. For each annotation instance, the details of that concept instance are given as a set of key-value pairs. Some examples of model concepts are given.
The meta-data associated with a Business Process could be located either in a separate Model-Markup file or embedded in a Source Content file that describes the process. Only one instance would exist for each Business Process. An example could be:
The ID field allows other annotation instances to uniquely refer to it. Several mechanisms are possible to associate the Source Content that defines the Business Process with the Business Process annotation. A typical use case might be that a complete Source Content File, describing the process, is tagged with the ID of the process and any resulting code for the process contains the BusinessProcess in its execution context. Alternatively, the tag is associated with only a sub-section of the Source Content file, and only the functionality generated from within that section adds the Business Process to the context passed down the invocation chain.
A Business Process is made up of the invocation of one or more related Business Process Steps. These Business Process Steps are semantically meaningful units of functionality that can be reused in more than one Business Process. The step itself is described in a BusinessProcessStep structure, which like the BusinessProcess, could be embedded in a Source Content file for the step, or be located in a separate mark-up file. Each instance of a Business Process Step annotation would itself have a unique ID.
When the relationship between Business Processes and Business Process Steps is known statically by the designers of the business processes, the relationships can be captured explicitly in the annotation. There are two possible, complementary, mechanisms that would allow tools to easily discover the invocation relationships with a simple static analysis:
The Source Content that results in the implementation of a Business Process Step would contain annotations that describe the behaviour of the step in more detail. These additional annotations within the Source Content describe meaningful operations, or points, within the step, such as start, stop, or external interaction with a third-party system.
The implementation of business functionality, in the form of Business Objects (BO) would be described in similar way. There would be a single annotation instance for each type of BO.
Within the implementation of a Business Object, each externally visible method would also be annotated. The methods would make reference to the type of Business Object.
At run-time a context, the Model Context, would be maintained to collect data from the various annotations to build a picture of the execution of the application. This context would be organised using the structures defined in the Annotation definitions—a set of structured key-value pairs. A reference to the context would be passed as a parameter down the call chain of the generated code, even across machine boundaries. The context itself may be located in a central repository or service, such as the Model Discovery Service. The tools that interpreted the Model-Markup would need to process the Source Content to extend the method signatures of all generated code to reference this shared context. The modified source content would be responsible for appropriately adding or removing data in the Model Context.
The Model Context may contain information not only about the software, but also about the infrastructure it is running on. The infrastructure-related data would include not only the infrastructure that the current call context is miming on, but also the collection of distributed infrastructure that has been involved in the call chain—for example, that the code is running on a Linux virtual machine, on a specific physical machine. Additionally, the execution environment and monitoring infrastructure could supplement the context with information such as amount of CPU/memory/bandwidth consumed by each of the steps and machines in the call chain.
For each reported event from the Run-time Model Reporting functionality, tools could look into the Model Context to discover the structure and run-time behaviour from the perspective of the models—for example which Application Module, Business Process, Business Process Step, Business Object, Business Object Method, etc is involved. The monitored information such as CPU or memory usage produced by the execution environment is also associated with this.
The notion of adding mark-up to the Source Content of software, to direct a transformation that generates either code or documentation, can be implemented using known techniques. An example of document production is the HTML output from Javadoc mark-up embedded in the comments of a Java source file. An example of mark-up affecting the generation of code is the directives embedded in Java classes in the Eclipse Modelling Framework (EMF), which affect the generation of automatically-produced code for model classes for functionality such as instance creation and persistence.
The known model based systems do not try to auto-generate models, or provide the kind of framework for managing relationships as shown in the described embodiments.
Nor do the known systems show that the annotation can drive both static and run-time discovery and analysis of the existing Enterprise business process, to automatically and simultaneously create both a documentation model and a computational model of the system. The resulting computational model can be used to automate the simulation, evaluation, and design of the system.
More details of an example of using a series of models for such purposes will now be described. If starting from scratch, a business process is designed using a business process modeling tool. The business process is selected from a catalog of available business processes and is customized by the business process modeling tool. An available business process is one that can be built and run. There will be corresponding templates for these as described below. Then non-functional characteristics such as reliability and performance requirements are specified.
Next the software entities such as products and components required to implement the business process are selected. This is done typically by searching through a catalog of product models in which the model for each product specifies what business process is implemented. This model is provided by an application expert or the product vendor.
Next the computing infrastructure such as virtual machines, operating systems, and underlying hardware, is designed. This can use templates as described in more detail below, and in above referenced previously filed application Ser. No. 11/741,878 “Using templates in automated model-based system design” incorporated herein by reference. A template is a model that has parameters and options, by filling in the parameters and selecting options a design tool transforms the template into a complete model of a deployable system. This application shows a method of modelling a business process having a number of computer implemented steps using software application components, to enable automatic deployment on a computing infrastructure, the method having the steps of:
automatically deriving a grounded model of the business process from an unbound model of the business process, the unbound model specifying the application components to be used for each of the computer implemented steps of the business process, without a complete design of the computing infrastructure, and the grounded model specifying a complete design of the computing infrastructure suitable for automatic deployment of the business process,
the deriving of the grounded model having the steps of providing an infrastructure design template having predetermined parts of the computing infrastructure, predetermined relationships between the parts, and having a limited number of options to be completed, generating a candidate grounded model by generating a completed candidate infrastructure design based on the infrastructure design template, and generating a candidate configuration of the software application components used by the unbound model, and evaluating the candidate grounded model, to determine if it can be used as the grounded model.
Next the physical resources from the shared resource pool in the data center are identified and allocated. Finally the physical resources are configured and deployed and ongoing management of the system can be carried out.
All of this can use SAP R/3 as an example, but is also applicable to other SAP or non-SAP systems. Templates as discussed below can include not only the components needed to implement the business process and the management components required to manage that business process, but also designs for computing infrastructure.
The model generation part can be implemented in various ways. One way is based on a six stage model flow called the Model Information Flow (MIF). This involves the model being developed in stages or phases which capture the lifecycle of the process from business requirements all the way to a complete running system. The six phases are shown in
Each stage of the flow has corresponding types of model which are stored in a Model Repository. Management services consume the models provided by the Model Repository and execute management actions to realize the transitions between phases, to generate the next model in the MIF. Those services can be for example:
Templates are used to capture designs that are known to instantiate successfully (using the management services mentioned above). An example of template describes a SAP module running on a Linux virtual machine (vm) with a certain amount of memory. The templates also capture management operations that it is known can be executed, for instance migration of vm of a certain kind, increasing the memory of a vm, deploying additional application server to respond to high load, etc. . . . If a change management service refers to the templates, then the templates can be used to restrict the types of change (deltas) that can be applied to the models.
Templates sometimes have been used in specific tools to restrict choices. Another approach is to use constraints which provide the tool and user more freedom. In this approach constraints or rules are specified that the solution must satisfy. One example might be that there has to be at least one application server and at least one database in the application configuration. These constraints on their own do not reduce the complexity sufficiently for typical business processes, because if there are few constraints, then there are a large number of possible designs (also called a large solution space). If there are a large number of constraints (needed to characterize a solution), then searching and resolving all the constraints is really hard—a huge solution space to explore. Also it will take a long time to find which of the constraints invalidates a given possible design from the large list of constraints.
Templates might also contain instructions for managing change. For example they can contain reconfiguration instructions that need to be issued to the application components to add a new virtual machine with a new slave application server.
The deriving of the grounded model can involve specifying all servers needed for the application components. This is part of the design of the adaptive infrastructure and one of the principal determinants of performance of the deployed business process. The template may limit the number or type of servers, to reduce the number of options, to reduce complexity of finding an optimised solution for example.
The deriving of the grounded model from the unbound Model can involve specifying a mapping of each of the application components to a server. This is part of configuring the application components to suit the design of adaptive infrastructure. The template may limit the range of possible mappings, to reduce the number of options, to reduce complexity for example.
The deriving of the grounded model can involve specifying a configuration of management infrastructure for monitoring of the deployed business process in use. This monitoring can be at one or more different levels, such as monitoring the software application components, or the underlying adaptive infrastructure, such as software operating systems, or processing hardware, storage or communications.
More than one grounded model can be derived, each for deployment of the same business process at different times. This can enable more efficient use of resources for business processes which have time varying demand for those resources for example. Which of the grounded models is deployed at a given time can be switched over any time duration, such as hourly, daily, nightly, weekly, monthly, seasonally and so on. The switching can be at predetermined times, or switching can be arranged according to monitored demand, detected changes in resources such as hardware failures or any other factor.
Where the computing infrastructure has virtualized entities, the deriving of the grounded model can be arranged to specify one or more virtualized entities without indicating how the virtualised entities are hosted. It has now been appreciated that the models and the deriving of them can be simplified by hiding such hosting, since the hosting can involve arbitrary recursion, in the sense of a virtual entity being hosted by another virtual entity, itself hosted by another virtual entity and so on. The template can specify virtual entities, and map application components to such virtual entities, to limit the number of options to be selected, again to reduce complexity. Such templates will be simpler if they do not need to specify the hosting of the virtual entities. The hosting can be defined at some time before deployment, by a separate resource allocation service for example.
The grounded model can be converted to a bound model, by reserving resources in the adaptive infrastructure for deploying the bound model. At this point, the amount of resources needed is known, so it can be more efficient to reserve resources at this time than reserving earlier, though other possibilities can be conceived. If the grounded model is for a change in an existing deployment, the method can have the step of determining differences to the existing deployed model, and reserving only the additional resources needed.
The bound model can be deployed by installing and starting the application components of the bound model. This enables the business process to be used. If the grounded model is for a change in an existing deployment, the differences to the existing deployed model can be determined, and only the additional application components need be installed and started.
Two notable points in the modelling philosophy are the use of templates to present a finite catalogue of resources that can be instantiated, and not exposing the hosting relationship for virtualized resources. Either or both can help reduce the complexity of the models and thus enable more efficient processing of the models for deployment or changing after deployment.
Some embodiments can use an infrastructure capability model to present the possible types of resources that can be provided by a computing fabric. An instance of an infrastructure capability model contains one instance for each type of Computer System or Device that can be deployed and configured by the underlying utility computing fabric. Each time the utility deploys and configures one of these types, the configuration will always be the same. For a Computer System this can mean the following for example.
Same memory, CPU, Operating System
Same number of NICs with same I/O capacity
Same number of disks with the same characteristics
The templates can map the application components to computers, while the range of both application components and computers is allowed to vary. In addition the templates can also include some or all of the network design, including for example whether firewalls and subnets separate the computers in the solution. In embodiments described below in more detail, the Application Packaging Model together with the Custom Process Model show how the various application components can implement the business process, and are packaged within the Grounded Model.
The template selected can also be used to limit changes to the system, such as changes to the business process, changes to the application components, or changes to the infrastructure, or consequential changes from any of these. This can make the ongoing management of the adaptive infrastructure a more tractable computing problem, and therefore allow more automation and thus reduced costs. In some example templates certain properties have a range: for example 0 to n, or 2 to n. A change management tool (or wizard, or set of tools or wizards) only allows changes to be made to the system that are consistent with template. The template is used by this change management tool to compute the set of allowable changes, it only permits allowable changes. This can help avoid the above mentioned difficulties in computing differences between models of current and next state, if there are no templates to limit the otherwise almost infinite numbers of possible configurations. Some of the advantages or consequences of these features are as follows:
1. Simplicity: by using templates it becomes computationally tractable to build a linked tool set to integrate business process, application and infrastructure design and management through the entire lifecycle of design, deployment and change.
2. By limiting the number of possible configurations of the adaptive infrastructure, the particular computing problem of having to compute the differences between earlier and later states of complex models is eased or avoided. This can help enable a management system for the adaptive infrastructure which can determine automatically how to evolve the system from an arbitrary existing state to an arbitrary desired changed state. Instead templates fix the set of allowable changes and are used as configuration for a change management tool.
3. The template models formally relate the business process, application components and infrastructure design. This means that designs, or changes, to any one of these can be made dependent on the others for example, so that designs or changes which are inconsistent with the others are avoided.
The management system has an interface, optionally a 3D visual interface, to an infrastructure management operator 200. This operator can be service provider staff, or in some cases can be trained staff of the enterprise owning the process. The service provider staff may be able to view and manage the processes of different businesses deployed on the shared infrastructure. The operators of a given enterprise would be able to view and manage only their own processes. As discussed above, the interface can be coupled to the management system 210 to be able to interact with the various types of models, and with the infrastructure design template.
The adaptive infrastructure can include management infrastructure 283, for coupling to the monitoring and management tools 217 of the management system. The models need not be held all together in a single repository: in principle they can be stored anywhere.
At step 550, the system deploys the grounded model of the BP in the adaptive infrastructure. The deployed BP is monitored by a monitoring means of any type, and monitoring results are passed to the human operator. Following review of the monitoring results at step 570, the operator of the enterprise can design changes to the BP or the operator of the service provider can design changes to the infrastructure at step 575. These are input to the system, and at step 580 the system decides if changes are allowed by the same template. If no, at step 585, the operator decides either for a new template, involving a return to step 520, or for a redesign within the limitations of the same template, involving at step 587 the system creating a grounded model of the changes, based on the same template.
At step 590 the operator of the service provider causes deployment of the grounded model for test or live deployment. At step 595 the system deploys the grounded model of the changes. In principle the changes could be derived later, by generating a complete grounded model, and later determining the differences, but this is likely to be more difficult.
A business process model 15 has a specification of steps 1-N. There can be many loops and conditional branches for example as is well known. It can be a mixture of human and computer implemented steps, the human input being by customers or suppliers or third parties for example. At step 65, application components are specified for each of the computer implemented steps of the business process. At step 75, a complete design of computing infrastructure is specified automatically, based on an unbound model 25. This can involve at step 85 taking an infrastructure design template 35, and selecting options allowed by the template to create a candidate infrastructure design. This can include design of software and hardware parts. At step 95, a candidate configuration of software application components allowed by the template is created, to fit the candidate infrastructure design. Together these form a candidate grounded model.
At step 105, the candidate grounded model is evaluated. If necessary, further candidate grounded models are created and evaluated. Which of the candidates is a best fit to the requirements of the business process and the available resources is identified. There are many possible ways of evaluating, and many possible criteria, which can be arranged to suit the type of business process. The criteria can be incorporated in the unbound model for example.
There can be several grounded models each for different times or different conditions. For example, time varying non-functional requirements can lead to different physical resources or even a reconfiguration: a VM might have memory removed out-of-office hours because fewer people will be using it. One might even shutdown an underused slave application server VM. The different grounded models would usually but not necessarily come from the same template with different parameters being applied to generate the different grounded models.
The template, grounded and subsequent models can contain configuration information for management infrastructure and instructions for the management infrastructure, for monitoring the business process when deployed. An example is placing monitors in each newly deployed virtual machine which raise alarms when the CPU utilization rises above a certain level—e.g. 60%.
The custom model is converted to an unbound model 25 with inputs such as application performance 31, application packaging 21, and application constraints 27. The unbound model can specify at least the application components to be used for each of the computer implemented steps of the business process, without a complete design of the computing infrastructure. The unbound model is converted to a grounded model 55 with input from models of infrastructure capability 33, and an infrastructure design template 35.
Deployment of the grounded model can involve conversion to a bound model 57, then conversion of the bound model to a deployed model 63. The bound model can have resources reserved, and the deployed model involves the applications being installed and started.
An adaptive infrastructure management service 350 can configure and ignite virtual machines in the adaptive infrastructure 280, according to the bound model, to create a partially deployed model. Finally a software deployment service 360 can be used to take a partially deployed model and install and start application components to start the business process, and create a fully deployed model.
At step 410, remaining options in the selected template are filled in. This can involve selecting for example disk sizes, numbers of dialog processes, number of servers, server memory, network bandwidth, server memory, network bandwidth, database time allowed and so on. At step 420, a candidate grounded model is created by the selections. Step 430 involves evaluating the candidate grounded model e.g. by building a queuing network, with resources represented, and with sync points representing processing delays, db delays and so on. Alternatively the evaluation can involve deploying the model in an isolated network with simulated inputs and conditions.
At step 440, the evaluation or simulation results are compared with goals for the unbound model. These can be performance goals such as maximum number of simultaneous users with a given response time, or maximum response time, for a given number of users. At step 450, another candidate grounded model can be created and tested with different options allowed by the template. At step 460 the process is repeated for one or more different templates. At step 470, results are compared to identify which candidate or candidates provides the best fit. More than one grounded model may be selected, if for example the goals or requirements are different at different times for example. In this case, the second or subsequent grounded model can be created in the form of changes to the first grounded model.
There are many commercial storage virtualization products on the market from HP, IBM, EMC and others. These products are focused on managing the storage available to physical machines and increasing the utilization of storage. Virtual machine technology is a known mechanism to run operating system instances on one physical machine independently of other operating system instances. It is known, within a single physical machine, to have two virtual machines connected by a virtual network on this machine. VMware is a known example of virtual machine technology, and can provide isolated environments for different operating system instances running on the same physical machine.
There are also many levels at which virtualization can occur. For example HP's cellular architecture allows a single physical computer to be divided into a number of hard partitions or nPARs. Each nPAR appears to the operating system and applications as a separate physical machine. Similarly each nPAR can be divided into a number of virtual parititions or vPARs and each vPAR can be divided into a number of virtual machines (e.g. HPVM, Xen, VMware).
The next part of this document describes in more detail with reference to
A custom model can have a 1-1 correspondence between an instance of an AlService and a BusinessProcess. The AIService is the information service that implements the business process.
A business process can be decomposed into a number of business process steps (BPsteps), so instances of a BusinessProcess class can contain 1 or more BPSteps. An instance of a BPStep may be broken into multiple smaller BPSteps involving sequences, branches, recursions and loops for example. Once the BusinessProcess step is decomposed into sufficient detail, each of the lowest level BPSteps can be matched to an ApplicationComponent. An ApplicationComponent is the program or function that implements the BPStep. For SAP, an example would be the SAP transaction named VA01 in the SD (Sales and Distribution package) of SAP R/3 Enterprise. Another example could be a specific Web Service (running in an Application Server).
BPStep can have stepType and stepParams fields to describe not only execution and branching concepts like higher-level sequences of steps, but also the steps themselves. The stepType field is used to define sequential or parallel execution, loops, and if-then-else statements. The stepParams field is used to define associated data. For example, in the case of a loop, the stepParams field can be the loop count or a termination criterion. The set of BPSteps essentially describes a graph of steps with various controls such as loops, if-then-else statements, branching probabilities, etc.
The relation BPStepsToApplicationComponentMapping is a complex mapping that details how the BPStep is mapped to the ApplicationComponent. It represents, in a condensed form, a potentially complex mix of invocations on an Application Component by the BPStep, such as the specific dialog steps or functions invoked within the ApplicationComponent or set of method calls on a Web Service, and provided details of parameters, such as the average number of line items in a sales order.
A BPStep may have a set of non-functional requirements (NonFunctionalRequirements) associated with it: performance; availability, security, and others. Availability and security requirements could be modelled by a string: “high”, “medium”, “low”. Performance requirements are specified in terms of for example a number of registered users (NoUsersReq), numbers of concurrent users of the system, the response time in seconds and throughput requirement for the number of transactions per second. Many BPSteps may share the same set of non-functional requirements. A time function can be denoted by a string. This specifies when the non-functional requirements apply, so different requirements can apply during office-hours to outside of normal office hours. Richer time varying functions are also possible to capture end of months peaks and the like.
For an example of a Custom Model the well-known Sales and Distribution (SD) Benchmark will be discussed. This is software produced by the well known German company SAP. It is part of the SAP R/3 system, which is a collection of software that performs standard business functions for corporations, such as manufacturing, accounting, financial management, and human resources. The SAP R/3 system is a client server system able to run on virtually any hardware/software platform and able to use many different database management systems. For example it can use an IBM AS/400 server running operating system OS/400 using database system DB2; or a Sun Solaris (a dialect of Unix) using an Oracle database system; or an IBM PC running Windows NT using SQL Server.
SAP R/3 is designed to allow customers to choose their own set of business functions, and to customize to add new database entities or new functionality. The SD Benchmark simulates many concurrent users using the SD (Sales and Distribution) application to assess the performance capabilities of hardware. For each user the interaction consists of 16 separate steps (Dialog Steps) that are repeated over and over. The steps and their mapping to SAP transactions are shown in
On the right hand side a line leads from the SD Benchmark BPStep to the functional requirements shown as six BPSteps, with stepType=Step—one for each SAP transaction shown in
The Unbound Model is used to calculate resource demands. As shown in
The Application Packaging Model describes the internal structure of the software: what products are needed and what modules are required from the product. An ApplicationComponent can be contained in an ApplicationModule. An ApplicationModule might correspond to a JAR (Java archive) file for an application server, or a table in a database. In the case of SAP it might be the module to be loaded from a specific product into an application server such as SD or Fl (Financials). The application packaging model can have a DiskFootPrint to indicate the amount of disk storage required by the ApplicationModule. In the case of the ApplicationComponent VA01 in
Other examples of constraints include ordering: the database needs to be started before the application server. Further constraints might be used to encode deployment and configuration information. The constraints can be contained all in the templates, or provided in addition to the templates, to further limit the number of options for the grounded model.
The purpose of the Application Performance Model is to define the resource demands for each BPStep. There are two types of resource demand to consider.
The IndirectComponentResourceDemand is recursive. So there will be a tree like a call-graph or activity-graph.
A complete Application Performance Model would contain similar information for all the BPSteps shown in
The following are some examples of attributes that can appear in IndirectComponentResourceDemands and ComponentResourceDemands.
CPUProperties can be expressed in SAPs or in other units. There are various ways to express MemProperties, NetIOProperties and DiskIOProperties.
There is one instance of an Application Performance Model for each instance of a Custom Model. This is because, in the general case, each business process will have unique characteristics: a unique ordering of BPSteps and/or a unique set of data characteristics for each BPStep. The DirectComponentResourceDemands and IndirectComponentResourceDe-mands associations specify the unique resource demands for each BPStep. These demands need to be calculated from known characteristics of each ApplicationComponent derived from benchmarks and also traces of installed systems.
The Component Performance Model contains known performance characteristics of each ApplicationComponent. A specific Application Performance Model is calculated by combining the following:
Taken together, the models of the Unbound Model specify not only the non-functional requirements of a system, but also a recipe for how to generate and evaluate possible software and hardware configurations that meet those requirements. The generation of possible hardware configurations is constrained by the choice of infrastructure available from a specific Infrastructure Provider, using information in an Infrastructure Capability Model, and by the selected template.
A general principle that applies to deployable software elements described in the Unbound Model, such as the ApplicationExecutionComponent or ApplicationExecutionService, is that the model contains only the minimum number of instances of each type of element necessary to describe the structure of the application topology. For example, in the case of SD only a single instance of a Dialog Work Process ApplicationExecutionComponent associated with a single instance of an Application Server ApplicationExecutionService is needed in the Unbound Model to describe the myriad of possible ways of instantiating the grounded equivalents of both elements in the Grounded Model. It is the template and packaging information that determines exactly how these entities can be replicated and co-located.
As discussed above, two notable features of the modelling philosophy described are:
1. Present a template having a finite catalogue of resources that can be instantiated, so that there are a fixed and finite number of choices. For example, small-xen-vm 1-disk, medium-xen-vm 2-disk, large-xen-vm 3-disk, physical-hpux-machine etc. This makes the selection of resource type by any capacity planning tool simpler. It also makes the infrastructure management easier as there is less complexity in resource configuration—standard templates can be used.
2. Do not expose the hosting relationship for virtualized resources. The DMTF Virtualization System Profile models hosting relationship as a “HostedDependency” association. This does not seem to be required if there is only a need to model a finite number of resource types, so it does not appear in any of the models discussed here. This keeps the models simpler since there is no need to deal with arbitrary recursion. It does not mean that tools that process these models can't use the DMTF approach internally if that is convenient. It may well be convenient for a Resource Directory Service and Resource Assignment Service to use this relationship in their internal models.
An instance of an infrastructure capability model contains one instance for each type of ComputerSystem or Device that can be deployed and configured by the underlying utility computing fabric. Each time the utility deploys and configures one of these types the configuration will always be the same. For a ComputerSystem this means the following.
The master application server is coupled to a box labelled AI_GroundedExecutionService:AppServer, indicating it can be used to run such a software element. It has an associated AIDeploymentSetting box which contains configuration information and deployment information sufficient to allow the AI_GroundedExecutionService to be automatically installed, deployed and managed. The AI_GroundedExecutionService:AppServer is shown as containing three components, labelled AI_GroundedExecutionComponents, and each having an associated AIDeploymentSetting box. A first of these components is a dialog work process, for executing the application components of steps of the business process, another is an update process, responsible for committing work to persistent storage, and another is an enqueue process, for managing locks on a database. As shown, the range attribute is 2 . . . n for the update and the dialog work process, meaning multiple instances of these parts are allowed.
The slave application server has a GroundedExecutionService having only one type of AI_GroundedExecutionComponent for any number of dialog work processes. The slave application server is shown having a rangeP=Time function, meaning it is allowed to be active at given times. Again the service and the execution component each have an associated AIDeploymentSetting box.
The master and slave application servers and the database computer system have an operating system shown as AI_disk: OSDisk. The master application server is shown with an AI_Disk: CIDisk as storage for use by the application components. For the network, each computer system has a network interface shown as AI_Nic1, coupled to the network shown by AI_Network: subnet1.
The database computer system is coupled to a box labelled AI_GroundedExecutionService: Database, which has only one type of AI_GroundedExecutionComponent, SD DB for the database. Again the service and the execution component each have an associated AIDeploymentSetting box. AIDeploymentSetting carries the configuration and management information used to deploy, configure, start, manage and change the component. Further details of an example of this are described below with reference to
Optionally the template can have commands to be invoked by the tools, when generating the grounded model, or generating a changed grounded model to change an existing grounded model. Such commands can be arranged to limit the options available, and can use as inputs, parts of the template specifying some of the infrastructure design. They can also use parts of the unbound model as inputs.
The Grounded Model may be generated by a design tool as it transforms the Unbound Model into the Grounded Model. It can be regarded as a candidate Grounded Model until evaluated and selected as the chosen Grounded Model. The following are some of the characteristics of the example Grounded Model of
The management system is arranged to make these choices to derive the Grounded Model from the template using the Unbound Model. In the example shown, the criteria used for the choice includes the total capacity of the system, which must satisfy the time varying Performance Requirements in the Custom Model. The required capacity is determined by combining these Performance Requirements with the aggregated ResourceDemands [Direct and Indirect] of the Application Performance Model. If the first choice proves to provide too little capacity, or perhaps too much, then other choices can be made and evaluated. Other examples can have different criteria and different ways of evaluating how close the candidate grounded model is to being a best fit.
In some examples the server may only have an OS disk attached; that is because the convention in such installations is to NFS mount the CI disk to get its SAP executable files. Other example templates could have selectable details or options such as details of the CIDisk and the DBDisk being 100 GB, 20 MB/sec, non Raid, and so on. The OS disks can be of type EVA800. The master and slave application servers can have 2 to 5 dialog work processes. Computer systems are specified as having 3 GB storage, 2.6 GHz CPUs and SLES 10-Xen operating system for example. Different parameters can be tried to form candidate Grounded Models which can be evaluated to find the best fit for the desired performance or capacity or other criteria.
The Grounded Model therefore specifies the precise number and types of required instances of software and hardware deployable entities, such as GroundedExecutionComponent, GroundedExecutionService, and AIComputerSystem. AIDeploymentSettings can include for example:
GroundedComponents to share the same GroundedDeploymentSettings (c.f. a notion of typing) with specific parameters or overrides provided by SettingData. Both the GroundedDeploymentSettings and SettingData are interpreted by the Deployment Service during deployment.
Not all attributes are set in the Grounded Model. For example, it does not make sense to set MAC addresses in the Grounded Model, since there is not yet any assigned physical resource.
Other templates can be envisaged having any configuration. Other examples can include a decentralised secure SD template, a decentralised highly available SD template, and a decentralised, secure and highly available SD template.
A Bound Model Instance for a SD system example could have in addition to the physical resource assignment, other parameters set such as subnet masks and MAC addresses. A Deployed Model could differ from the Bound Model in only one respect. It shows the binding information for the management services running in the system. All the entities would have management infrastructure in the form of for example a management service. The implementation mechanism used for the interface to the management services is not defined here, but could be a reference to a Web Service or a SmartFrog component for example. The management service can be used to change state and observe the current state. Neither the state information made available by the management service, nor the operations performed by it, are necessarily defined in the core of the model, but can be defined in associated models.
One example of this could be to manage a virtual machine migration. The application managing the migration would use the management service running on the PhysicalComputerSystem to do the migration. Once the migration is completed, the management application would update the deployed model and bound models to show the new physical system. Care needs to be taken to maintain consistency of models. All previous model instances are kept in the model repository, so when the migration is complete, there would be a new instance (version) of the bound and deployed models.
It is not always the case that for the MIF all tools and every actor can see all the information in the model. In particular it is not the case for deployment services having a security model which requires strong separation between actors. For example, there can be a very strong separation between the utility management plane and farms of virtual machines. If a grounded model is fed to the deployment services of the management plane for an enterprise, it will not return any binding information showing the binding of virtual to physical machines, that information will be kept inside the management plane. That means there is no way of telling to what hardware that farm is bound or what two farms might be sharing. What is returned from the management plane could include the IP address of the virtual machines in the farms (it only deals with virtual machines) and the login credentials for those machines in a given farm. The management plane is trusted to manage a farm so that it gets the requested resources. Once the deployment service has finished working, one could use application installation and management services to install, start and manage the applications. In general different tools will see projections of the MIF. It is possible to extract from the MIF models the information these tools require and populate the models with the results the tools return. It will be possible to transform between the MIF models and the data format that the various tools use.
The software parts such as the models, the model repository, and the tools or services for manipulating the models, can be implemented using any conventional programming language, including languages such as Java, or C compiled following established practice. The servers and network elements can be implemented using conventional hardware with conventional processors. The processing elements need not be identical, but should be able to communicate with each other, e.g. by exchange of IP messages.
The foregoing description of embodiments 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 modifications and variations are possible in light of the above teachings or may be acquired from practice of the invention. The embodiments were chosen and described in order to explain the principles behind the invention and its practical applications to enable one skilled in the art to utilize the invention in various embodiments and with various modifications as are suited to the particular use contemplated. Other variations can be conceived within the scope of the claims.
This application relates to copending US applications of even date titled “MODEL BASED DEPLOYMENT OF COMPUTER BASED BUSINESS PROCESS ON DEDICATED HARDWARE” (applicant reference number 200702144), titled “VISUAL INTERFACE FOR SYSTEM FOR DEPLOYING COMPUTER BASED PROCESS ON SHARED INFRASTRUCTURE” (applicant reference number 200702356), titled “MODELLING COMPUTER BASED BUSINESS PROCESS FOR CUSTOMISATION AND DELIVERY” (applicant reference number 200702363), titled “MODELLING COMPUTER BASED BUSINESS PROCESS AND SIMULATING OPERATION” (applicant reference number 200702377), titled “SETTING UP DEVELOPMENT ENVIRONMENT FOR COMPUTER BASED BUSINESS PROCESS”, (applicant reference number 200702145), and titled “INCORPORATING DEVELOPMENT TOOLS IN SYSTEM FOR DEPLOYING COMPUTER BASED PROCESS ON SHARED INFRASTRUCTURE”, (applicant reference number 200702601), and previously filed US application titled “DERIVING GROUNDED MODEL OF BUSINESS PROCESS SUITABLE FOR AUTOMATIC DEPLOYMENT” (Ser. No. 11/741,878) all of which are hereby incorporated by reference in their entirety.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/US07/88322 | 12/20/2007 | WO | 00 | 6/15/2010 |
