Embodiments of the invention generally relate to information technology (IT), and, more particularly, to license management.
Currently, software licenses are defined using plain text, in human readable format. For example, current license management systems use keywords to identify a license metric and a lack of formal, semantic description to reason license capability. Such a situation creates potential for error, as many manual efforts are required.
In general, a software license includes a collection of license metrics. Further, a license metric contains rich information, including expressive formulae and/or rules for capacity unit and capacity calculation. Also, high-level license metrics can be defined based on multiple basic license metrics. Therefore, in order to enable automatic reasoning, which includes but is not limited to software license requirement calculations, software license comparisons, import/export software license definition among different license management tools, etc., a need exists for a well-defined metamodel (that is, language) to specify a software license in order to provide automated license reasoning capable of handling complicated software licenses.
In one aspect of the present invention, techniques for generating license models based on license meta-mode for automatic license reasoning are provided. An exemplary computer-implemented method for modeling a software license using a metamodel can include steps of creating an object-oriented information model to describe a hardware infrastructure, a software deployment environment, and an organization structure corresponding to a software license deployment, creating a set of property functions to formulate one or more items of information related to the hardware infrastructure, one or more users, and the organization structure, creating a set of license metrics by defining license metric capacity unit and license metric capacity calculation logic that leverage at least one existing property function and/or at least one of the created property functions, and leveraging the license metrics to model the software license.
Another aspect of the invention or elements thereof can be implemented in the form of an article of manufacture tangibly embodying computer readable instructions which, when implemented, cause a computer to carry out a plurality of method steps, as described herein. Furthermore, another aspect of the invention or elements thereof can be implemented in the form of an apparatus including a memory and at least one processor that is coupled to the memory and operative to perform noted method steps. Yet further, another aspect of the invention or elements thereof can be implemented in the form of means for carrying out the method steps described herein, or elements thereof; the means can include hardware module(s) or a combination of hardware and software modules, wherein the software modules are stored in a tangible computer-readable storage medium (or multiple such media).
These and other objects, features and advantages of the present invention will become apparent from the following detailed description of illustrative embodiments thereof, which is to be read in connection with the accompanying drawings.
As described herein, an aspect of the present invention includes a license metamodel that enables generating license models for automatic license reasoning. The license metamodel provides a formal language that enables semantic description of software licenses. When a software license is defined using the metamodel, it is not only human readable, but also machine (that is, computer system) understandable, which further enables automatic license reasoning.
As noted above, in general, a software license is defined by a collection of license metrics. Further, a license metric includes a license capacity unit definition and license capacity calculation logic, wherein both components can be defined by expressions and/or rules. Both expressions and rules are defined using software/hardware deployment and organization information. Also, a new license metric can be defined based on a collection of existing license metrics.
By understanding information required to define a software license, a metamodel can be created to facilitate determination of a formal definition of a software license. In at least one embodiment of the invention, the metamodel includes multiple layers of components; namely, IT Environment metamodel, Property Function metamodel, License Capacity Unit metamodel, License Capacity Calculation metamodel, License Metric metamodel and Software License model.
In such an embodiment, an extensible markup language (XML) schema is used to implement the software license metamodel. In the XML schema, the software license type is defined as:
A software license contains a set of LicenseMetric, which is further defined by LicenseMetricType as:
A license metric includes MetricIndenfication, a collection of MetricDefinition or a LicenseMetricReference. MetricIndenfication contains information such as metric name or vendor to identify the license metric. LicenseMetricReference refers to another license metric. Also, MetricDefinition is further defined by MetricDefintionType:
A MetricDefinitionType includes defaultScope, a set of LicenseCapacityUnit and LicenseCapacityCalculation. The defaultScope is defined by extending MetricScopeType with Boolean attribute postAggregation, as follows:
MetricScopeType is further defined as:
It should be noted that MetricScope may have one or no parent MetricScope, and includes attributes of scopeType, scopeID, scopeName and scopeExpression. It should also be noted that the default scope defines the scope that calculation logic to which both LicenseCapacityUnit and LicenseCapacityCalculation apply. In the case when calculation of a software license requirement's scope (that is, request scope) is bigger than the default scope, and when the postAggregation is true, then the LicenseCapacityUnit and LicenseCapacityCalculation is applied to all of the individual scopes (in default scope type) and the result is linearly aggregated to the request scope. If postAggregation is false, the LicenseCapacityUnit and LicenseCapacityCalculation are applied to the request scope.
Both LicenseCapacityUnit and LicenseCapacityCalculation are defined by PropertyFunctionType, which is further defined as:
PropertyFunctionType can be either FormulaBasedFunctionType, TableBasedFunctionType, ExternalFunctionType, or FunctionReference. FormulaBasedFunctionType is defined as:
FormulaBasedFunctionType extends the definition of FunctionType with an attribute of expression. The FunctionType is defined as:
FunctionType includes attribute functionID that identifies the function, attribute name that represents the name of the function, attribute is Numerical that indicates whether the output of the function is numerical or not, attribute is Scalar that indicates whether the output of the function is vector or not, and attribute is FixedValue that indicates whether the output of the function is a fixed value or not. TableBasedFunctionType extends FunctionType, and includes a collection of Columns and a collection of Rows, defined as follows:
Column is defined by ColumnType, which is further defined as:
Row is defined by RowType, which is further defined as:
A RowType includes a collection of Conditions and a collection of Results. The condition is defined based on ConditionType with columnName, wherein ConditionType is further defined as:
A ConditionType can be PointCondition, EnumerationCondition, or RangeCondition. A PointCondition is a ValueType, which is defined as:
EnumerationCondition is defined as a set of ValueType, as follows:
RangeCondtion is defined by a LowerBound and UpperBound, as follows:
ExternalFunction is defined by ExternalFunctionType, which is further defined as:
ExternalFunctionType allows specification of an external function such as a REST function, Web service, etc. There is an expression in the definition of FormulaBasedFunction and ScopeDefinition, the syntax of expression defined in JavaCC as:
The SCALAR_ENTITY in the syntax definition refers to objects defined in an IT environment, which can be defined by IT environment metamodel as the following XML Schema:
The ITEntityType is further defined as:
In the definition, attribute entityName can be referred to by SCALAR_ENTITY, and attribute tableName indicates the table that persists the entity. There is a collection of attributes that is defined by ITEntityAttributeType, which is further defined as:
ITEntityAttributeType has attributes including attributeName (name of the attribute), attributeType (data type of the attribute), is ID (whether the attribute is an ID for the entity) and is Array (whether the attribute is an array or not). ITEntityAttributeType may include AttributeMapping, which points to a column name of a table, or AttributeLookup, which specifies ForeignTableName, PrimaryKey and ForeignKey. In the case of AttributeLookup, the attribute itself is an object.
When license metrics and software licenses are formally defined using the above license metamodel, automatic license reasoning can be enabled. The automatic license reasoning includes, but is not limited to, automatic license requirement calculation, license metric analysis and comparison.
In accordance with at least one embodiment of the invention, and as additionally described herein, an example of automatic license reasoning can be a license requirement calculation which answers the question of a software license requirement (a tuple, includes license capacity unit, license capacity) for giving software, license metric type and software deployment scope. For example, assuming a software (for instance, Websphere Application Server) is deployed on a server with 4 CPU and software license metric NumberOfCPU (that is, license is calculated as number of CPUs in the deployed host) is used to calculate license requirement, the software license calculation uses the definition of software license metric of NumberOfCPU, accesses the information about the number of CPU of the host that deploys the Websphere Application Server, and returns <4, CPU> as the result of license requirement.
License requirement calculations can include the following steps. Upon receiving a license requirement calculation request (software_ID, metric_type, req_scope, scope_ID) from a software asset manager, wherein software_ID indicates the type of software, metric_type is name of the license metric, req_scope represents software deployment scope, which can be a virtual machine, a physical server, cluster, data center, etc., a license metric of metric_type is retrieved.
Additionally, a default_scope in the metric definition is retrieved and a determination is made as to whether req_scope equals default_scope. If req_scope does equal default_scope, license capacity unit and license capacity are calculated, and a result of tuple <license capacity, license capacity unit> is generated and returned to the requester. If req_scope does not equal default_scope, an additional determination is made as to whether req_scope is smaller than min_scope. If req_scope is smaller than min_scope, a request error is generated and returned. If req_scope is not smaller than min_scope, all instances of default_scope in req_scope are retrieved, and a determination is made as to whether postAggregation is true. If postAggregation is not true, all of the instances are linearly aggregated, license capacity unit and license capacity are calculated, and a result is generated and returned.
If postAggregation is true, a determination is made as to whether capacity unit is a fixed value (that is, a string). If capacity unit is not a fixed value, license capacity unit and capacity unit are calculated in each instance in default_scope, all of the calculation results are linearly aggregated, and a result is generated and returned. If capacity unit is a fixed value, license capacity is calculated in each instance in default_scope, all of the calculation results are linearly aggregated, license capacity unit is calculated, and results are generated and returned.
In connection with at least one embodiment of the invention, a formula-based function for capacity unit and/or a formula-based function for capacity calculation can consider a multitude of variables and/or parameters. Such parameters can include users, memory (in megabytes (MB), for instance), number of processors, disks (in gigabytes (GB), for instance), value unit, nodes, concurrent user, servers, desktop, site, virtual array, management points, number of internet protocol (IP) addresses scanned, number of scans, connector, client license, per user client access license (CAL), per device CAL, physical central processing unit (CPU), processors managed by a product, per application instance, per establishment authorization, additional processors, per telephony port user, per mailbox user, number of logical partitions (LPARs), number of processors chips, etc.
Additionally, as described herein, usage of a software license meta-model includes supporting software license metric information inter-operation among multiple software license management systems. At least one embodiment of the invention can include exporting and/or importing license metric information in XML format (wherein an XML schema is defined by the software license meta-model) for a license information exchange. Usage of a software license metamodel also includes supporting software license metric analysis. For example, at least one embodiment of the invention includes exporting license metric information in an XML format, wherein XML documents provide a standard formation that allows further analysis, such as root cause analysis for license cost.
With respect to system license management system B, the sequence begins at step 610, and step 612 includes receiving a license metric definition (for example, receiving the license metric definition exported in step 606 from software license management system A). Step 614 includes importing the license metric definition, and the sequence ends with step 616.
Similarly, as depicted in
Similarly, as depicted in
If req_scope does not equal default_scope in step 1008, the process continues onto step 1018, which includes determining whether req_scope is smaller than min_scope. If no (that is, req_scope is larger than min_scope), then the process continues onto step 1020, which includes linearly aggregating all of the instances. Further, step 1022 includes calculating a license capacity unit, step 1024 includes calculating license capacity, step 1026 includes returning the result, and the process ends at step 1028. If req_scope is smaller than min_scope in step 1018, an error request is returned in step 1030, and the process ends at step 1032.
Step 1104 includes creating a set of property functions to formulate one or more items of information related to the hardware infrastructure, one or more users, and the organization structure. As described herein, a property function is used to define a license capacity unit and/or a license capacity calculation. Additionally, creating a set of property functions can include identifying a collection of schema that defines the one or more property functions of the software license. The property functions can include a formula-based function, a table-based function, a generic function with input and output specification, and/or a reference to another function.
Step 1106 includes creating a set of license metrics by defining license metric capacity unit and license metric capacity calculation logic that leverage at least one existing property function and/or at least one of the created property functions. Creating a set of license metrics can include generating a schema that defines a license metric by name, by license capacity unit, and/or by license capacity calculation logic. Also, creating a set of license metrics can include generating a schema that defines a new license metric based on existing license metrics using a formula-based function, a table-based function, and/or a generic function with input and output specification.
Step 1108 includes leveraging the license metrics to model the software license. Also, the techniques depicted in
Further, the techniques depicted in
As also detailed herein, at least one embodiment of the invention includes automatically reasoning software license metrics. Such an embodiment includes providing a software license model editor for creating a software license metric definition using a software license metamodel and/or providing a software license loader for importing a software license metric definition in one of multiple formats to create a software license metric definition using software license metamodel, wherein the software license metric definition specifies identification of software license metric, capacity unit and capacity calculation. Additionally, such an embodiment includes deploying the software license metric definition, and receiving license requirement calculation request for a deployed software and returning the actual license requirement for the deployed software. Further such an embodiment includes receiving a software license metric analysis request for a software license and returning one or more expressions for license capacity unit and a license capacity calculation, a default scope of license capacity unit, one or more input parameters for expression of license capacity unit and/or license capacity calculation. Additionally, such an embodiment includes receiving a software license metric comparison request for two or more software license metric definitions and returning a differentiation between default scopes corresponding to the two or more software license metric definitions, one or more expressions in capacity unit and/or capacity calculation, and one or more input parameters of the expressions.
Further, as additionally detailed herein, at least one embodiment of the invention includes enabling interoperation between two software license management systems. Such an embodiment includes providing a software license model editor for creating a software license metric definition using a software license metamodel, exporting the software license metric definition in a format that conforms to the software license metamodel, and importing the software license metric definition in the format that conforms with the software license metamodel and deploying the software license metric definition.
The techniques depicted in
Additionally, the techniques depicted in
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in a computer readable medium having computer readable program code embodied thereon.
An aspect of the invention or elements thereof can be implemented in the form of an apparatus including a memory and at least one processor that is coupled to the memory and operative to perform exemplary method steps.
Additionally, an aspect of the present invention can make use of software running on a general purpose computer or workstation. With reference to
Accordingly, computer software including instructions or code for performing the methodologies of the invention, as described herein, may be stored in associated memory devices (for example, ROM, fixed or removable memory) and, when ready to be utilized, loaded in part or in whole (for example, into RAM) and implemented by a CPU. Such software could include, but is not limited to, firmware, resident software, microcode, and the like.
A data processing system suitable for storing and/or executing program code will include at least one processor 1202 coupled directly or indirectly to memory elements 1204 through a system bus 1210. The memory elements can include local memory employed during actual implementation of the program code, bulk storage, and cache memories which provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during implementation.
Input/output or I/O devices (including but not limited to keyboards 1208, displays 1206, pointing devices, and the like) can be coupled to the system either directly (such as via bus 1210) or through intervening I/O controllers (omitted for clarity).
Network adapters such as network interface 1214 may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening non-public or public networks. Modems, cable modem and Ethernet cards are just a few of the currently available types of network adapters.
As used herein, including the claims, a “server” includes a physical data processing system (for example, system 1212 as shown in
As noted, aspects of the present invention may take the form of a computer program product embodied in a computer readable medium having computer readable program code embodied thereon. Also, any combination of computer readable media may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using an appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of at least one programming language, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).
Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks. Accordingly, an aspect of the invention includes an article of manufacture tangibly embodying computer readable instructions which, when implemented, cause a computer to carry out a plurality of method steps as described herein.
The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, component, segment, or portion of code, which comprises at least one executable instruction for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
It should be noted that any of the methods described herein can include an additional step of providing a system comprising distinct software modules embodied on a computer readable storage medium; the modules can include, for example, any or all of the components detailed herein. The method steps can then be carried out using the distinct software modules and/or sub-modules of the system, as described above, executing on a hardware processor 1202. Further, a computer program product can include a computer-readable storage medium with code adapted to be implemented to carry out at least one method step described herein, including the provision of the system with the distinct software modules.
In any case, it should be understood that the components illustrated herein may be implemented in various forms of hardware, software, or combinations thereof, for example, application specific integrated circuit(s) (ASICS), functional circuitry, an appropriately programmed general purpose digital computer with associated memory, and the like. Given the teachings of the invention provided herein, one of ordinary skill in the related art will be able to contemplate other implementations of the components of the invention.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of another feature, integer, step, operation, element, component, and/or group thereof.
The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed.
At least one aspect of the present invention may provide a beneficial effect such as, for example, facilitating automatic software license requirement calculation.
The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.