METHOD AND SYSTEM FOR DETERMINING COMPATIBILITY OF COMPUTER SYSTEMS
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`CROSS-REFERENCE TO RELATED APPLICATIONS
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`[0001]
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`This application is a continuation of U.S. Patent Application No. 14/341,471 filed on
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`July 25, 2014, which is a continuation of U.S. Patent Application No. 11/738,936 filed on April
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`23, 2007, which is a continuation-in-part of U.S. Patent Application No. 11/535,355 and also a
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`continuation-in-part of U.S. Patent Application No. 11/535,308 both filed on September 26,
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`2006, both of which claim priority from U.S. Provisional Patent Application No. 60/745,322filed
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`April 21, 2006, all incorporated herein by reference.
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`TECHNICAL FIELD
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`[0002]
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`The presentinvention relates to information technologyinfrastructures and has
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`particularutility in determining compatibility of computer systems in suchinfrastructures.
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`BACKGROUND
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`[0003]
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`As organizations have become morereliant on computers for performing day to day
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`activities, so to has the reliance on networks and information technology (IT) infrastructures
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`increased.
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`It is well knownthat large organizations having offices and otherfacilities in different
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`geographical locations utilize centralized computing systems connected locally over local area
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`networks (LAN) and across the geographical areas through wide-area networks (WAN).
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`[0004]
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`As these organizations grow, the amountof data to be processed and handled by the
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`centralized computing centers also grows. As a result, the IT infrastructures used by many
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`organizations have moved awayfrom reliance on centralized computing power and towards
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`more robust and efficient distributed systems. Distributed systems are decentralized computing
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`systems that use more than one computer operating in parallel to handle large amounts of data.
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`Concepts surrounding distributed systems are well knownin the art and a complete discussion
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`can be found in, e.g., “Distributed Systems: Principles and Paradigms”; Tanenbaum AndrewS.:
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`Prentice Hall; Amsterdam, Netherlands; 2002.
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`[0005]
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`While the benefits of a distributed approach are numerous and well understood,
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`there has arisen significant practical challenges in managing such systems for optimizing
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`efficiency and to avoid redundancies and/or under-utilized hardware.
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`In particular, one
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`challenge occurs due to the sprawl that can occur over time as applications and servers
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`proliferate. Decentralized control and decision making around capacity, the provisioning of new
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`applications and hardware, and the perception that the cost of adding server hardwareis
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`generally inexpensive, have created environments with far more processing capacity than is
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`required by the organization.
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`[0006]
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`Whencost is considered on a server-by-server basis, the additional cost of having
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`underutilized servers is often not deemedto be troubling. However, when multiple servers in a
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`large computing environment are underutilized, having too many servers can become a burden.
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`Moreover, the additional hardware requires separate maintenance considerations; separate
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`upgrades and requires the incidental attention that should instead be optimized to be more cost
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`effective for the organization. Heat production and power consumption can also be a concern.
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`Even considering only the cost of having redundant licenses, removing even a modest number
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`of servers from a large computing environment can savea significant amount of cost on a yearly
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`basis.
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`[0007]
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`As a result, organizations have become increasingly concerned with such
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`redundancies and how they can best achieve consolidation of capacity to reduce operating
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`costs. The cost-savings objective can be evaluated on the basis of consolidation strategies
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`such as, but notlimited to: virtualization strategies, operating system (OS) level stacking
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`strategies, database consolidation strategies, application stacking strategies, physical
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`consolidation strategies, and storage consolidation strategies.
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`[0008]
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`Virtualization involvesvirtualizing a physical system as a separate guest OS
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`instance on a host machine. This enables multiple virtualized systems to run on a single
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`physical machine, e.g. a server. Examples of virtualization technologies include VMware™,
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`Microsoft Virtual Server™, IBM LPAR™, Solaris Containers™, Zones™, etc.
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`[0009]
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`OS-Level application stacking involves moving the applications and data from one or
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`more systems to the consolidated system. This can effectively replace multiple operating
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`system instanceswith a single OSinstance, e.g. system A running application X and system B
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`running application Y are moved onto system C running application Z such that system C runs
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`applications X, Y and Z, and system A and B are no longer required. This strategy is applicable
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`to all operation system types, e.g. Windows™, Linux™, Solaris™, AIX™, HP-UX™, etc.
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`[0010]
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`Database stacking combines one or more database instances at the database server
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`level, e.g. Oracle™, Microsoft SQL Server™, etc. Database stacking combines data within a
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`database instance, namely at the table level. Application stacking combines one or more
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`databaseinstances at the application serverlevel, e.g. J2EE™ application servers, Weblogic™,
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`WebSphere™, JBoss™, etc.
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`[0011]
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`Physical consolidation moves physical systems at the OS level to multi-system
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`hardware platforms such as Blade Servers™, Dynamic System Domains™, etc. Storage
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`consolidation centralizes system storage through storage technologies such as Storage Area
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`Networks (SAN), Network Attached Storage (NAS), etc.
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`[0012]
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`The consolidation strategies to employ and the systems and applications to be
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`consolidated are to be considered taking into account the specific environment. Consolidation
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`strategies should be chosen carefully to achieve the desired cost savings while maintaining or
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`enhancing the functionality and reliability of the consolidated systems. Moreover, multiple
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`strategies may often be required to achieve the full benefits of a consolidation initiative.
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`[0013]
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`Complex systems configurations, diverse business requirements, dynamic workloads
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`and the heterogeneous natureof distributed systems can cause incompatibilities between
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`systems. These incompatibilities limit the combinations of systems that can be consolidated
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`successfully.
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`In enterprise computing environments, the virtually infinite number of possible
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`consolidation permutations which include suboptimal and incompatibility system combinations
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`make choosing appropriate consolidation solutions difficult, error-prone and time consuming.
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`[0014]
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`It is therefore an object of the following to obviate or mitigate the above-described
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`disadvantages.
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`SUMMARY
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`[0015]
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`In one aspect, a method for determining a consolidation solution for a plurality of
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`computer systems is provided comprising obtaining a data set comprising a compatibility score
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`NUWBWNO
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`~—
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`for each pair of the plurality of computer systems, each the compatibility score being indicative
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`of the compatibility of one of the plurality of computer systems with respect to anotherof the
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`plurality of computer systems; determining one or more candidate transfer sets each indicating
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`one or more of the computer systems capable of being transferred to a target computer system;
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`selecting a desired one of the one or more candidate transfer sets; and providing the desired
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`one as a consolidation solution.
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`[0016]
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`In another aspect, there is provided method for determining compatibilities for a
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`plurality of computer systems comprising: obtaining at least one transfer set indicating one or
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`more of the computer systems capable of being transferred to a target computer system;
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`evaluating compatibilities of the one or more computer systems against the target computer
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`system to obtain a first compatibility score; evaluating compatibilities of each the one or more of
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`the computer systems against each other to obtain a second compatibility score; and computing
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`an overall compatibility score for the transfer set using the first and second compatibility scores.
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`[0017]
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`In yet another aspect, there is provided a computer program for determining
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`compatibilities for a plurality of computer systems comprising an audit engine for obtaining
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`information pertaining to the compatibility of the plurality of computer systems; an analysis
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`engine for generating a compatibility score for each pair of the plurality of systems based on the
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`information that is specific to respective pairs; and a client for displaying the compatibility score
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`on an interface, the interface being configured to enable a user to specify parameters
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`associated with a map summarizing the compatibility scores and to define and initiate a transfer
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`of one or more of the computer systems to a target computer system.
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`BRIEF DESCRIPTION OF THE DRAWINGS
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`[0018]
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`An embodimentof the invention will now be described by way of example only with
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`reference to the appended drawings wherein:
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`[0019]
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`Figure 1 is a block diagram of an analysis program for evaluating the compatibility of
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`computer systems to identify consolidation solutions.
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`[0020]
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`Figure 2 is a more detailed diagram of the analysis program depicted in Figure 1.
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`[0021]
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`Figure 3 is a block diagram illustrating a sample consolidation solution comprised of
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`multiple transfers.
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`[0022]
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`Figure 4 is an example of a rule-based compatibility analysis map.
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`[0023]
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`Figure 5 is an example of a workload compatibility analysis map.
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`[0024]
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`Figure 6 is an example of an overall compatibility analysis map.
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`[0025]
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`Figure 7 is a schematic block diagram of an underlying architecture for implementing
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`the analysis program of Figure 1.
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`[0026]
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`Figure 8 is a table mapping audit data sources with consolidation strategies.
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`[0027]
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`Figure 9 is a process flow diagram of the compatibility and consolidation analyses.
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`[0028]
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`Figure 10 is a process flow diagram illustrating the loading of system data for
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`analysis.
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`[0029]
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`Figure 11 is a high level processflow diagram for a 1-to-1 compatibility analysis.
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`[0030]
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`Figure 12 is a table showing example rule sets.
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`[0031]
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`Figure 13 is a table showing example workload types.
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`[0032]
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`Figure 14 is a process flow diagram for the 1-to-1 compatibility analysis.
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`[0033]
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`Figure 15 is a flow diagram illustrating operation of the rule engine analysis.
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`[0034]
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`Figure 16 shows an example rule set.
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`[0035]
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`Figure 17 is a flow diagram of the 1-to-1 rule-based compatibility analysis.
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`[0036]
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`Figure 18 is a flow diagram illustrating the evaluation of a rule set.
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`[0037]
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`Figure 19 is an example of the rule-based compatibility analysis result details.
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`[0038]
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`Figure 20 is a flow diagram of workload data extraction process.
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`[0039]
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`Figure 21 is a flow diagram of the 1-to-1workload compatibility analysis.
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`[0040]
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`Figure 22 is an example of the workload compatibility analysis result details.
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`[0041]
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`Figure 23 is an example of the overall compatibility analysis result details.
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`[0042]
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`Figure 24(a) is a high level process flow diagram of the multi-dimensional
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`compatibility analysis.
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`[0043]
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`Figure 24(b) is a flow diagram showing the multi-dimensional analysis.
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`[0044]
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`Figure 24(c) is a flow diagram showing use of a rule set in an N-to-1 compatibility
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`analysis.
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`[0045]
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`Figure 24(d) is a flow diagram showing useof a rule set in an N-by-N compatibility
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`analysis.
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`[0046]
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`Figure 25 is a process flow diagram of the multi-dimensional workload compatibility
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`analysis.
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`[0047]
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`Figure 26 is an example multi-dimensional compatibility analysis map.
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`[0048]
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`Figure 27 is an example of the multi-dimensional compatibility analysis result details
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`for a rule set.
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`[0049]
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`Figure 28 is an example of the multi-dimensional workload compatibility analysis
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`result details.
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`[0050]
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`Figure 29 is a process flow diagram of the consolidation analysis.
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`[0051]
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`Figure 30 is a process flow diagram of an autofit algorithm used by the consolidation
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`analysis.
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`[0052]
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`Figure 31 is an example of a consolidation solution produced by the consolidation
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`analysis.
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`[0053]
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`Figure 32 shows an example hierarchy of analysis folders and analyses.
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`[0054]
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`Figure 33 shows the screen for creating and editing the analysis input parameters.
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`[0055]
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`Figure 34 shows an example of the rule set editor screen.
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`[0056]
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`Figure 35 shows an example of the screen for editing workload settings.
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`[0057]
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`Figure 36 shows an example screen to edit the importance factors used to compute
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`the overall compatibility score.
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`[0058]
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`Figure 37 is an example 1-to-1 compatibility map.
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`[0059]
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`Figure 38 is example configuration compatibility analysis details.
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`[0060]
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`Figure 39 is an example 1-to-1 compatibility map for business constraints.
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`[0061]
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`Figure 40 is an example 1-to-1 workload compatibility map.
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`[0062]
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`Figure 41 is an example workload compatibility report.
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`[0063]
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`Figure 42 is an example workload details report with stacked workloads.
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`[0064]
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`Figure 43 is an example of a 1-to-1 overall compatibility map.
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`[0065]
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`Figure 44 is an example of the 1-to-1 overall compatibility details report.
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`[0066]
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`Figure 45 showsthe workload details of the overall compatibility report.
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`[0067]
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`Figure 46 shows example transfers on a compatibility map with net effectoff.
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`[0068]
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`Figure 47 shows example transfers on a compatibility map with net effect on.
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`[0069]
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`Figure 48 is an example multi-dimensional compatibility details report.
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`[0070]
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`Figure 49 shows an example of the consolidation analysis (autofit) input screen.
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`[0071]
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`Figure 50 is an example overall compatibility map for the consolidation solution.
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`[0072]
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`Figure 51 is an example consolidation summary report.
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`[0073]
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`Figure 52 shows the example transfers that comprise the consolidation solution.
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`DETAILED DESCRIPTION OF THE DRAWINGS
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`Analysis Program Overview
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`0DDNn
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`[0074]
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`A block diagram of an analysis program 10 for determining compatibilities in
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`computing environment 12 is provided in Figure 1. The analysis program 10, accessed through
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`a computerstation 14, gathers data 18 pertaining to a collection of systems to be consolidated
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`16. The analysis program 10 uses the gathered data 18 to evaluate the compatibility of the
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`computer systems 28 and provide a roadmap 20 specifying how the original set of systems can
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`be consolidated to a smaller number of systems 22.
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`[0075]
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`The following provides an overview of the principles and functionality related to the
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`analysis program 10 andits environment depicted in Figure 2.
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`System Data Parameters
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`[0076]
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`A distinct data set is obtained for each system 16 to contribute to the combined
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`system data 18 shownin Figure 2. Each data set comprises one or more parametersthat relate
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`preferably to technical 24, business 26 and workload 28 characteristics or features of the
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`respective system 16. The parameters can be evaluated by scrutinizing program definitions,
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`properties, objects, instances and any other representation or manifestation of a component,
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`feature or characteristic of the system 16.
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`In general, a parameter is anything related to the
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`system 16 that can be evaluated, quantified, measured, compared etc.
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`[0077]
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`Examples of technical parameters relevant of the consolidation analysis include the
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`operating system, OS version, patches, application settings, hardware devices, etc.
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`[0078]
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`Examples of business parameters of systems relevant to the consolidation analysis
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`include the physical location, organization department, data segregation requirements, owner,
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`service level agreements, maintenance windows, hardware lease agreements, software
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`licensing agreements, etc.
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`[0079]
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`Examples of workload parameters relevant to consolidation analysis include various
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`resourceutilization and capacity metrics related to the system processor, memory, disk storage,
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`disk I/O throughput and network bandwidth utilization.
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`System and Entity Models
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`[0080]
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`The system data parameters associated with a system 16 comprise the system
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`model usedin the analyses.
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`[0081]
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`In the following examples, a source system refers to a system from which
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`applications and/or data are to be moved, and a target server or system is a system to which
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`such applications and/or data are to be moved. For example, an underutilized environment
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`having two systems 16 can be consolidated to a target system (one of the systems) by moving
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`applications and/or data from the source system (the other of the systems) to the target system.
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`[0082]
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`The computer systems 16 may be physical systems, virtual systems or hypothetical
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`models.
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`In contrast to actual physical systems, hypothetical systems do not currently exist in
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`the computing environment 12. Hypothetical systems can be defined and includedin the
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`analysis to evaluate various types of “what if’ consolidation scenarios. Hypothetical targets can
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`be used to simulate a case where the proposed consolidation target systems do not exist in the
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`environment12, e.g. for adding a system 16. Similarly, hypothetical source systems can be
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`used to simulate the case where a new application is to be introduced into the environment 12
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`and “forward consolidated” onto existing target systems 16.
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`[0083]
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`Hypothetical systems can be created through data imports, cloning from actual
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`systems models, and manual specification by users, etc. The system model can be minimal
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`(sparse) or include as much data as an actual system model. These system models may also
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`be further modified to address the analysis requirements.
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`[0084]
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`The compatibility analysis can also be generalized to evaluate entities beyond
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`physical, virtual or hypothetical systems. For example, entities can be componentsthat
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`comprise systems such as applications and database instances. By analysing the compatibility
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`of database instances and database servers with database stacking rule sets, database
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`consolidation can also be assessed. Similarly, application consolidation can be evaluated by
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`analyzing application servers and instances with application stacking rules. The entity could
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`also be a logical application system and technical data can pertain to functional aspects and
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`specifications of the entity.
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`[0085]
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`It will therefore be appreciated that a “system” or “computer system”hereinafter
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`referred, can encompassany entity which is capable of being analysed for any type of
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`compatibility and should not be considered limited to existing or hypothetical physical or virtual
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`systems etc.
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`Consolidation and Transfers
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`[0086]
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`Consolidation as described above can be considered to include one or more
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`“transfers”. The actual transfer describes the movementof a single source entity onto a target,
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`wherein the specification identifies the source, target and transfer type. The transfer type (or
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`consolidation strategy) describes how a sourceentity is transferred onto a target, e.g.
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`virtualization, OS stacking etc.
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`[0087]
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`A transfer set 23 (see Figure 3) can be considered one or moretransfers that involve
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`a common target, wherein the set specifies one or more source entities, the target and a
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`transfer type.
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`[0088]
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`A consolidation solution (or roadmap) is one or more transfer sets 23 based on a
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`common pool of source and target entities. As can be seen in Figure 2, the consolidation
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`roadmap can beincluded in the analysis results 20. Each source or target entity is referenced
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`at most onetime by the transfer sets that comprise the solution.
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`[0089]
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`Figure 3 shows how an example pool 24 of 5 systems ($1, S2, S3, S4 and S5) can
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`be consolidated through 2 transfer sets 23: stack S1 and S2 onto S3, and stack S4 onto S5.
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`The transfer sets 23 include 3 transfers, and each system 16 is referenced bythe transfer sets
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`23 only once.
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`In the result, a consolidated pool 26 of 2 systems is achieved.
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`[0090]
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`It will be appreciated that the principles described herein support many
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`transformation strategies and consolidation is only one example.
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`we
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`Compatibility Analyses
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`[0091]
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`The following discusses compatibilities between systems 16 based on the
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`parameters to determine if efficiencies can be realized by consolidating either entire systems 16
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`or aspects or components thereof.
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`[0092]
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`The analyses employdifferential rule sets 28 to evaluate and quantify the
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`compatibility of systems 16 with respect to technical configuration and business related factors
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`comprised in the gathered system data 18. Similarly, workload compatibility of a set of systems
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`16 is assessed using workload stacking and scoring algorithms 30. The results of configuration,
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`business and workload compatibility analyses are combined to produce an overall compatibility
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`score for a set of systems 16.
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`[0093]
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`In addition to compatibility scores, the analysis provides details that account for the
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`actual scores. The scores can be presentedin color coded maps 32, 34 and 36 thatillustrate
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`patterns of the compatibility amongst the analyzed systems as shownin Figures 4, 5 and 6
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`respectively.
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`Analysis Modes
`
`[0094]
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`A collection of systems 16 to be consolidated can be analyzed in one of three
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`modes: 1-to-1 compatibility, multi-dimensional compatibility and consolidation analyses. These
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`analyses share many common aspects but can be performed independently.
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`[0095]
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`The 1-to-1 compatibility analysis evaluates the compatibility of every possible
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`source-target pair combination in the collection of systems 16 on a 1-to-1 basis. This analysis is
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`useful in assessing single transfer consolidation candidates.
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`In practice, it may be prudent to
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`consolidate systems 16 incrementally and assess the impact of each transfer before proceeding
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`with additional transfers.
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`[0096]
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`The multi-dimensional compatibility analysis evaluates the compatibility of transfer
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`sets that can involve multiple sources being transferred to a common target. The analysis
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`produces a compatibility score for each specified transfer set 23 by evaluating the compatibility
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`of the systems 16 that comprise the transfer set 23.
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`we
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`VMware, Inc.
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`Exhibit1002
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`VMware, Inc. Exhibit 1002 Page 11
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`[0097]
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`The consolidation analysis searches for a consolidation solution that minimizes the
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`numberof remaining source and target entities after the proposed transfers are applied, while
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`meeting requisite compatibility constraints. This analysis employs the multi-dimensional
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`compatibility analysis described above to evaluate the compatibility of postulated transfer sets.
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`[0098]
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`The analysis program 10 performs consolidation analysesforvirtualization and
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`stacking strategies as will be explained in greater detail below, however, it will be appreciated
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`that other consolidation strategies may be performed according to similar principles.
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`Analysis Program Architecture
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`[0099]
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`A block diagram of the analysis program 10 is shownin Figure 7. The flow of data
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`18 through the program 10 begins as an audit engine 40 pulls audit data 18 from audited
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`environments 42. The data works its way up to the web client 44 which displays an output on a
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`user interface, e.g. on computer 14. The program 10 is preferably a client-server application
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`that is accessed via the web client 44.
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`[00100]
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`An audit engine 40 communicates over one or more communication protocols with
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`audited environments 42 comprised of the actual systems 16 being analysed. The audit engine
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`40 typically uses data acquisition adapters to communicate directly with the end points (e.g.
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`servers) or through software systems that manage the end points (e.g. management
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`frameworks 46 and/or agent instrumentation 48 and/or direct access 50).
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`[00101]
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`Alternatively, system data 18 can be imported from third party tools, e.g. inventory
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`applications, performance monitoring tools etc., or can be obtained through user data entry.
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`Examples of such third-party data having file formats that can be imported include comma
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`separated values (CSV), extensible markup language (XML) and well formatted text files such
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`as those generated by the UNIX™ system activity reporter (SAR).
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`[00102]
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`The audit engine 40, uses a set of audit request templates 52 that define the data 18
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`to acquire from the systems 16. Once collected, the data 18 is stored in an audit data repository
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`54. Data 18 referenced by the analysis rule sets 28 and required by the workload analysis 30
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`are extracted and stored in separate data caches 56 and 58 respectively.
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`23782470.1
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`VMware, Inc. Exhibit 1002 Page 12
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`NABWNO
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`~—
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`[00103] Aliases 60, differential rule sets 28, workload data types 30 and benchmark
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`specifications comprise some of the analysis-related metadata 62 definitions used by the
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`program 10. Aliases 60 extract and normalize system data 18 from a variety of data sources to
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`a common model for analysis. Rule sets 28 examine system compatibility with respect to
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`technical configuration and business-related factors. The workload definitions 30 specify the
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`system resource parameters and benchmarksfor analyzing workload compatibility.
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`[00104]
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`An analysis engine 64 is also provided, which comprises compatibility and
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`consolidation analysis engines 66 and 68 respectively. The compatibility analysis evaluates the
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`compatibility of systems 16 through rule sets 28 and workload stacking algorithms 30. The
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`consolidation analysis engine 68 leverages the compatibility analysis and employs constraint-
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`based optimization algorithms to find consolidation solutions that allows the environment 12 to
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`operate with fewer systems 16.
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`[00105]
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`|The program 10 has a report engine 70 that utilizes report templates 72 for
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`generating reports that convey the analysis results. Typically, the program 10 includes a web
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`interface layer 74 that allows webclient 44 users to enter settings, initiate an audit or analysis,
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`view reports etc.
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`Analysis Data Sources
`
`[00106]
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`The audit data 18 can be acquired using tools such as the table 76 shownin Figure 8
`
`that illustrate the various types of configuration settings that are of interest and from which
`
`sources they can be obtained. Figure 8 also provides a mapping to where the sample workload
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`data can be obtained.
`
`In Figure 8, a numberof strategies 78 and sub-strategies 80 map to
`
`various configuration and workload sources, collectively referred to by numeral 82. As
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`discussed making reference to Figure 8, the strategies 78 may relate to database consolidation,
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`OS-level stacking, application server stacking, virtualization, and many others. Each strategy
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`78 includes a set of sub-strategies 80, which in turn map to specific rule sets 28. The rule sets
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`28, which will be explained in greater detail below, determine whetheror not a particular setting
`
`or system criterion/criteria have been met and thus how different one system 16 is to the next.
`
`The rule sets 28 canalso indicate the cost of remediating such differences.
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`23782470.1
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`SYDWnffWN
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`[00107]
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`The table 76 lists the supported consolidation strategies and the relevant data
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`sources that should be audited to perform the corresponding consolidation analysis.
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`In general,
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`collecting more basis data 18 improvesthe analysis results. The table 76 enables the analysis
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`program 10 to locate the settings and information of interest based on the strategy 78 or sub-
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`strategy 80 (and in turn the rule set 28) that is to be used to evaluate the systems 16 in the
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`environment 12. The results can be used to determine source/target candidates for analysing
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`the environment for the purpose of, e.g. consolidation, compliance measuresetc.
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`Analysis Process Overview
`
`[00108]
`
`Referring now to Figure 9, a process flow diagram illustrates the data flow for
`
`performing the compatibility and consolidation analyses discussed above. The flow diagram
`
`outlines four processes: a data load and extraction process(A), a 1-to-1 compatibility analysis
`
`process (B), a multi-dimensional compatibility analysis process (C), and a consolidation analysis
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`process(D).
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`[00109]
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` Inprocess A, the system data 18 collected via audits or imports as discussed above
`
`is prepared for use by the analyses. The compatibility and consolidation analyses processesB,
`
`C and D can be performed independently. The analyses share a common analysis input
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`specification and get system data 18 from the data repository 54 and caches 56 and 58. The
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`multi-dimensional compatibility and consolidation analyses take additional inputs in the form of a
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`consolidation solution and autofit input parameters 84 and 86 respectively.
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`[00110]
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`The 1-to-1 compatibility analysis process B evaluates the compatibility of each
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`system pair on a 1-to-1 basis.
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`In contrast, the multi-dimensional analysis process C evaluates
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`the compatibility of each transfer set 23 in the consolidation solution that was specified as part
`
`of its input.
`
`[00111]
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`|The consolidation analysis process D searchesfor the best consolidation solution
`
`that fulfills the constraints defined by the autofit input 86. The consolidation analysis employs
`
`the multi-dimensional compatibility analysis C to assess potential transfer set candidates.
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`27
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`Data Load and Extraction
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`VMware, Inc. Exhibit 1002 Page 14
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`[00112]
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`A process flow diagram for the data load and extraction processA is illustrated in
`
`Figure 10. System data including technical configuration, business related and workload
`
`collected through audits, data import and user input are prepared for use by the analyses
`
`processesB, C and D.
`
`[00113] When system data 18 andattributes are loaded into the analysis program 10, they
`
`are stored in the audit data repository 54 and system attribute table 55, respectively. As well,
`
`system data 18 referenced by rule set items 28, workload types 30 and benchmarks are
`
`extracted and loaded into their respective caches 56, 58. Alias specifications 60 describe how
`
`data can be extracted and if necessary, normalized from a variety of data sources.
`
`[00114]
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`The data repository 54 and caches 56 and 58thus store audited data 18, system
`
`attributes, the latest rule set data, historical workload data and system workload benchmarks.
`
`1-to-1 Compatibility Analysis
`
`[00115]
`
`A high level flow diagram of the 1-to-1 compatibility analysis is shown in Figure 11.
`
`The 1-to-1 compatibility analysis can take into account analysis input, including input regarding
`
`the systems 16 to be analyzed, rule set related parameters, workload related parameters,
`
`workload benchmarks and importance factors 88 used to compute overall scores.
`
`[00116]
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`The compatibility analysis evaluates the compatibility