Patent Application
20090235267
1. Field of the Invention
The present application relates generally to an improved data processing apparatus and method and more specifically to an apparatus and method for providing a consolidated display of resource performance trends.
2. Background of the Invention
With the proliferation and increased connectivity of different enterprises on the Internet, mechanisms have been developed for monitoring the performance of the computing system infrastructures and resources that support these enterprises. Such mechanisms typically gather metric data for monitoring the performance of the computing system infrastructure and resources using software agents. Mechanisms for graphing or charting the performance of the resources and infrastructure based on the gathered metric data may also be provided. Such graphing and charting mechanisms generate presentations of data across multiple views requiring a user to look at different charts for the relevant data and then aggregate this information, themselves in their own mind, on the fly in order to make evaluations.
In one illustrative embodiment, a method, in a data processing system, is provided for generating a consolidated representation of performance trends for a plurality of resources in the data processing system. The method may comprise retrieving recent performance measurement data for the plurality of resources and retrieving historical performance measurement data for the plurality of resources. The method may further comprise determining, for each resource in the plurality of resources, an associated performance trend based on an analysis of the recent performance measurement data and the historical performance measurement data. Moreover, the method may comprise generating a single consolidated graphical representation of the plurality of resources based on the associated performance trends. Each resource in the plurality of resources may have a separate representation within the single consolidated graphical representation positioned within the single consolidated graphical representation based on a recent performance trend and an associated historical performance trend. The method may further comprise outputting the single consolidated graphical representation.
In other illustrative embodiments, a computer program product comprising a computer useable or readable medium having a computer readable program is provided. The computer readable program, when executed on a computing device, causes the computing device to perform various ones, and combinations of, the operations outlined above with regard to the method illustrative embodiment.
In yet another illustrative embodiment, a system/apparatus is provided. The system/apparatus may comprise one or more processors and a memory coupled to the one or more processors. The memory may comprise instructions which, when executed by the one or more processors, cause the one or more processors to perform various ones, and combinations of, the operations outlined above with regard to the method illustrative embodiment.
These and other features and advantages of the present invention will be described in, or will become apparent to those of ordinary skill in the art in view of, the following detailed description of the exemplary embodiments of the present invention.
The invention, as well as a preferred mode of use and further objectives and advantages thereof, will best be understood by reference to the following detailed description of illustrative embodiments when read in conjunction with the accompanying drawings, wherein:
The illustrative embodiments provide a mechanism for providing a consolidated display of resource performance. The illustrative embodiments may gather performance metric data from one or more resources of a data processing system, such as an electronic enterprise, and use this performance metric data to generate a consolidated display of resource performance for the one or more resources showing both recent and historical performance for the one or more resources. These resources may be provided in an individual computing device or may be provided by a plurality of computing devices in a distributed data processing system.
Thus, the illustrative embodiments may be utilized in many different types of data processing environments including a distributed data processing environment, a single data processing device, or the like. In order to provide a context for the description of the specific elements and functionality of the illustrative embodiments,
As will be appreciated by one skilled in the art, the present invention may be embodied as a system, method or computer program product. Accordingly, 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, the present invention may take the form of a computer program product embodied in any tangible medium of expression having computer usable program code embodied in the medium.
Any combination of one or more computer usable or computer readable medium(s) may be utilized. The computer-usable or computer-readable medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection having one or more wires, a portable computer diskettes, 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 (CDROM), an optical storage device, a transmission media such as those supporting the Internet or an intranet, or a magnetic storage device. Note that the computer-usable or computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted, or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory. In the context of this document, a computer-usable or computer-readable medium may be any medium that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-usable medium may include a propagated data signal with the computer-usable program code embodied therewith, either in baseband or as part of a carrier wave. The computer usable program code may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc.
Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, 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).
The illustrative embodiments are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to the illustrative 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 or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus 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, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It shouldalso 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.
With reference now to the figures and in particular with reference to
With reference now to the figures,
In the depicted example, server 104 and server 106 are connected to network 102 along with storage unit 108. In addition, clients 110, 112, and 114 are also connected to network 102. These clients 110, 112, and 114 may be, for example, personal computers, network computers, or the like. In the depicted example, server 104 provides data, such as boot files, operating system images, and applications to the clients 110, 112, and 114. Clients 110, 112, and 114 are clients to server 104 in the depicted example. Distributed data processing system 100 may include additional servers, clients, and other devices not shown.
In the depicted example, distributed data processing system 100 is the Internet with network 102 representing a worldwide collection of networks and gateways that use the Transmission Control Protocol/Internet Protocol (TCP/IP) suite of protocols to communicate with one another. At the heart of the Internet is a backbone of high-speed data communication lines between major nodes or host computers, consisting of thousands of commercial, governmental, educational and other computer systems that route data and messages. Of course, the distributed data processing system 100 may also be implemented to include a number of different types of networks, such as for example, an intranet, a local area network (LAN), a wide area network (WAN), or the like. As stated above,
With reference now to
In the depicted example, data processing system 200 employs a hub architecture including north bridge and memory controller hub (NB/MCH) 202 and south bridge and input/output (I/O) controller hub (SB/ICH) 204. Processing unit 206, main memory 208, and graphics processor 210 are connected to NB/MCH 202. Graphics processor 210 may be connected to NB/MCH 202 through an accelerated graphics port (AGP).
In the depicted example, local area network (LAN) adapter 212 connects to SB/ICH 204. Audio adapter 216, keyboard and mouse adapter 220, modem 222, read only memory (ROM) 224, hard disk drive (HDD) 226, CD-ROM drive 230, universal serial bus (USB) ports and other communication ports 232, and PCI/PCIe devices 234 connect to SB/ICH 204 through bus 238 and bus 240. PCI/PCIe devices may include, for example, Ethernet adapters, add-in cards, and PC cards for notebook computers. PCI uses a card bus controller, while PCIe does not. ROM 224 may be, for example, a flash basic input/output system (BIOS).
HDD 226 and CD-ROM drive 230 connect to SB/ICH 204 through bus 240. HDD 226 and CD-ROM drive 230 may use, for example, an integrated drive electronics (IDE) or serial advanced technology attachment (SATA) interface. Super I/O (SIO) device 236 may be connected to SB/ICH 204.
An operating system runs on processing unit 206. The operating system coordinates and provides control of various components within the data processing system 200 in
As a server, data processing system 200 may be, for example, an IBM® eServer™ System p® computer system, running the Advanced Interactive Executive (AIX®) operating system or the LINUX® operating system (eServer, System p, and AIX are trademarks of International Business Machines Corporation in the United States, other countries, or both while LINUX is a trademark of Linus Torvalds in the United States, other countries, or both). Data processing system 200 may be a symmetric multiprocessor (SMP) system including a plurality of processors in processing unit 206. Alternatively, a single processor system may be employed.
Instructions for the operating system, the object-oriented programming system, and applications or programs are located on storage devices, such as HDD 226, and may be loaded into main memory 208 for execution by processing unit 206. The processes for illustrative embodiments of the present invention may be performed by processing unit 206 using computer usable program code, which may be located in a memory such as, for example, main memory 208, ROM 224, or in one or more peripheral devices 226 and 230, for example.
A bus system, such as bus 238 or bus 240 as shown in
Those of ordinary skill in the art will appreciate that the hardware in
Moreover, the data processing system 200 may take the form of any of a number of different data processing systems including client computing devices, server computing devices, a tablet computer, laptop computer, telephone or other communication device, a personal digital assistant (PDA), or the like. In some illustrative examples, data processing system 200 may be a portable computing device which is configured with flash memory to provide non-volatile memory for storing operating system files and/or user-generated data, for example. Essentially, data processing system 200 may be any known or later developed data processing system without architectural limitation.
As mentioned above, the illustrative embodiments provide a mechanism for providing a consolidated display of resource performance. The illustrative embodiments may gather performance metric data from one or more resources of data processing system and use this performance metric data to generate a consolidated display of resource performance for the one or more resources showing both recent and historical performance for the one or more resources. These resources may be provided in an individual computing device or may be provided by a plurality of computing devices in a distributed data processing system. In one illustrative embodiment, these resources are provided in a plurality of computing devices of an electronic enterprise infrastructure comprising one or more distributed data processing systems. Each of the computing devices may have one or more associated agents executing thereon whose duty it is to collect performance metric information and provide that performance metric information to a central server computing device that executes a performance monitoring engine.
The one or more associated agents may monitor the performance of resources, e.g., memory, CPU, storage space, bandwidth, applications, etc., with regard to actual transactions originating from actual users or with regard to robotic, i.e. simulated, transactions during times of relative idleness of the data processing system. Such monitoring of performance may be performed in real-time to generate metrics indicative of the performance of these resources. In one illustrative embodiment, the performance of the resources is monitored to collect metric data regarding the end-user response time experience associated with a resource, e.g., an application. Typically, the agents produce real-time metric data records that are provided to the central server which then aggregates these records to generate a performance metric, such as average response time, average number of requests handled, etc.
In one illustrative embodiment, the performance monitoring engine may be a modified version of the International Business Machines (IBM) Tivoli Composite Application Manager for Response Time (ITCAMfRT) available from IBM Corporation of Armonk, N.Y. In such an embodiment, the ITCAMfRT is modified by the present invention so as to generate a single unified or consolidated chart representation of the performance of a plurality of resources with both their recent and historical performance being charted. Rather than the many different representations used in known systems to represent each resource individually or different metrics in different views, thereby requiring a user to navigate back and forth between views to gather the information they need, the illustrative embodiments permit a plurality, or even all, of the resources of an electronic system, and their associated performance metric information, to be represented in a single relational chart of recent and historical performance. In this way, the performance of resources may be compared to identify those requiring immediate attention and those that are not necessarily in need of immediate attention by a system administrator.
In one illustrative embodiment, the single consolidated representation of resource performance comprises a bubble chart. Each resource is represented in the bubble chart as a bubble having a size that represents the relative magnitude, or the relative importance, of the monitored resource. The position of the bubble in the bubble chart is dependent upon a performance trend of the associated resource both recently and historically. In one illustrative embodiment, portions of the bubble chart are associated with resources whose performance is categorized as slipping (e.g., historically performance is steady or increasing, but recently performance is decreasing), lagging (e.g., historically performance is decreasing and recently performance continues to decrease), leading (e.g., historically performance is steady or increasing and recently performance is increasing), and improving (historically performance is decreasing, but recently performance is increasing). The bubble representations in the bubble chart may be selectable such that additional detailed information regarding the associated resource and its associated performance measurements may be obtained in response to the selection of the bubble representation.
The computing devices 330, 340, and 350 have a plurality of resources 332-335, 342-345, and 352-355 as well as agent applications 336, 346, and 356. The agent applications 336, 346, and 356 monitor various performance metrics of the resources 332-335, 342-345, and 352-355 and generate data records that are returned to the central server 310. The central server 310 may aggregate these data records to generate performance measurements or information representative of the availability, response time, and other measures of performance of the resources 332-335, 342-345, and 352-355.
The central server 310 generates both recent performance measurement data or information as well as historical performance measurement data or information. Recent performance measurement data may be performance measurement data that has been generated based on gathered metric data within a predetermined shortened time period from a current time, e.g., within the past 10 minutes, 30 minutes, hour, etc. Historical performance measurement data is performance measurement data that was generated based on gathered metric data that is older than the predetermined shortened time period from a current time, e.g., over 1 hour old. Recent performance measurement data is maintained within a data structure maintained in a local storage device 318 associated with the performance monitoring application 315. Historical performance measurement data or information is warehoused data that is transmitted from the performance monitoring application 315 to a data warehouse storage system 380 on a periodic basis, e.g., every hour, 12 hours, 24 hours, etc., such as via the network 302. The particular definition of the separation of historical performance measurement data from recent, or live, performance data may be dependent upon the particular implementation. In general, however, the difference may be determined as historical performance measurement data is typically archived at in a storage device that is typically remotely located, but may be local in some implementations, while recent or live performance measurement data is not yet archived.
The central server 310 further comprises a consolidated chart generation engine 370 executing on the central server 310 which, in accordance with the illustrative embodiments, generates a consolidated chart representation of the performance measurements or information for the plurality of resources 332-335, 342-345, and 352-355. The consolidated chart generation engine 370 may further interface with other graphic representation engines 385 running on the central server 310, such as may be part of the performance monitoring engine 315, for example, so that a combination of representations may be generated and linked in such a manner that one representation may be obtained using graphical user interface elements of another representation. For example, elements of the consolidated chart generated by the consolidated chart generation engine 370 may be user selectable with the result of such selection being the accessing of representations of resource performance information that are generally known in the art. Thus, the consolidated chart may be an interface through which more detailed information of resources may be accessed, such as in a format that is more familiar with users of legacy systems. The consolidated chart may be provided to a user workstation 390 in response to a request from the user workstation 390 for data processing system performance information, for example.
The graphical user interface 400 may be generated by a representation engine of the performance monitoring engine 315 on a system administrator workstation 320, for example. The performance measurement data that is used to generate the representations in the various portions 430-450 of the graphical user interface 400 is recent performance measurement data stored in a local storage 318 of the performance monitoring engine 315 of the central server 310, for example. It can be seen from
A second portion 480 is provided for setting forth the details of each of the resources in the selected resource category, e.g., applications. As shown in
A third portion 490 is provided for graphing or charting a first performance measurement for a selected resource, e.g., a selected application from the list shown in the second portion 480. In the depicted example, the third portion 490 depicts the number of requests received by the selected application over a historical time period bridging Mar. 6, 2007 to Mar. 7, 2007. Similarly, a fourth portion 495 is provided for graphing or charting a second performance measurement for the selected resource, e.g., average response time, for the same historical time period.
As can be seen from
As discussed above, the illustrative embodiments provide mechanisms for generating a consolidated view of the recent and historical performance measurement data for a plurality of resources. This consolidated chart representation of the recent and historical performance data is able to more effectively convey availability, response time, and other performance measurement data so that a user may focus on trouble areas in a complex data processing system, such as an electronic enterprise or the like.
Bubbles may overlap each other with smaller sized bubbles being represented on top of larger sized bubbles for viewability reasons. Alternatively, since smaller sized bubbles represent relatively lower importance resources, larger sized bubbles may be allowed to obscure the viewability of the smaller sized bubbles in some implementations. Various colors, patterns, highlighting, flashing, pulsing, or any other known graphical technique may be used to accentuate the differences between bubbles so that it is easy for a user to distinguish bubbles from one another and distinguish relative importance of bubbles from one another.
The placement of the bubbles on the chart is dependent upon an analysis of the recent and historical trends in performance of the associated resources. In one illustrative embodiment, if performance of a resource is recently decreasing, as determined from an analysis of the most recent performance measurement data for the resource, but has been improving historically, as determined from an analysis of the historical performance data warehoused in the data warehouse storage system, then the bubble for representing the resource may be placed in a first portion, e.g., a quadrant, of the chart 500. If performance of a resource is recently decreasing, as determined from an analysis of the most recent performance measurement data for the resource, and has been decreasing historically, as determined from an analysis of the historical performance data warehoused in the data warehouse storage system, then the bubble for representing the resource may be placed in a second portion of the chart 500. Similarly, if performance of a resource is recently increasing, as determined from an analysis of the most recent performance measurement data for the resource, and has been improving historically, as determined from an analysis of the historical performance data warehoused in the data warehouse storage system, then the bubble for representing the resource may be placed in a third portion of the chart 500. If performance of a resource is recently increasing, as determined from an analysis of the most recent performance measurement data for the resource, but has been decreasing historically, as determined from an analysis of the historical performance data warehoused in the data warehouse storage system, then the bubble for representing the resource may be placed in a fourth portion of the chart 500.
The particular point at which the bubble for a resource is placed in the various portions of the chart 500 is dependent upon the amount by which performance is increasing and/or decreasing both recently and historically. The performance measure that is used in the generation of the chart 500 may be any performance measure generated based on the recent and historical performance measurements generated based on metric data records gathered from the various agents in the distributed data processing system. Alternatively, an overall performance measurement, for recent performance and separately for historical performance, based on a variety of performance measurements may be generated based on one or more established functions that combine these various performance measurements to generate an overall measurement of the performance of the resource.
In one illustrative embodiment, the analysis of the recent and historical performance measurement data generates a percentage change in the performance measurement over the recent and historical time periods. The change in recent performance measurement may be used to map the center of the bubble along one axis of the chart 500 while the change in historical performance measurement may be used to map the center of the bubble along a second axis of the chart 500. From the placement of the center of the bubble on the chart 500, the bubble may be drawn having a size corresponding to the determined importance level of the associated resource.
The bubble that is generated in this manner may be selectable via a user interface, such as via a computer mouse, keyboard, or other known user interface. If the bubble is selected in this manner, detailed performance measurement information may be provided to the user in a “drill-down” manner, For example, a representation similar to that shown in
A second portion 520 (e.g., bottom left quadrant) of the chart 500 is associated with applications whose performance trend is evaluated to be a “lagging” category 560. This “lagging” category 560 represents those applications whose performance measurements, e.g., availability and response time measurements, indicate that the application has historically been decreasing in performance and has recently continued to decrease in performance. A third portion 530 (e.g., upper right quadrant) of the chart 500 is associated with applications whose performance trend is evaluated to be a “leading” category 570. This “leading” category 570 represents those applications whose performance measurements, e.g., availability and response time measurements, indicate that the application has historically been increasing in performance and has recently continued to increase in performance. A fourth portion 540 (e.g., lower right quadrant) of the chart 500 is associated with applications whose performance trend is evaluated to be an “improving” category 580. This “improving” category 580 represents those applications whose performance measurements, e.g., availability and response time measurements, indicate that the application has historically been decreasing in performance and has recently started to increase in performance.
With specific reference to the example shown in
The “EmployeeClub” application is lagging in this example and thus, is depicted in the second portion 560 of the chart 500. However, the EmployeeClub application has a much lower importance than any of the other monitored applications represented in the chart 500. The size of the bubble 593 associated with the EmployeeClub application indicates to the user that this application, while lagging in its performance, is not critical to the electronic enterprise and thus, it is not urgent that the performance problems associated with this application be immediately addressed.
Two applications, i.e. the “Payroll” application and the “InternalBlogServer” application, are indicated as “slipping” in performance in this example and thus, have their bubble representations presented in the first portion 550 of the chart 500. This means that each application has been performing well historically, but has suffered some response time degradations recently. The sizes of the bubbles 594 and 595 indicate that the Payroll application (bubble 594) is much more important than the InternalBlogServer application (bubble 595). Thus, the Payroll application will receive attention before the InternalBlogServer application.
The “CustomerServiceWeb” application is depicted as “improving” and has its associated bubble 596 positioned in the fourth portion 580. The bubble 596 size indicates that it is a relatively important application. However, since it is improving in performance, it may be less important to direct attention to this application than important applications present in the slipping and lagging portions 510 and 520 of the chart 500.
Thus, from this one consolidated chart 500 representation of the performance trends of the resources of the distributed data processing system, it can be determined which resources have been performing well and are continuing to perform well, which resources are performing well but historically have not been performing well, which resources have historically been performing well but have recently started to slip in performance, and which resources have historically and recently not been performing well. Moreover, from this one consolidated chart 500 representation, it can be determined the relative importance of such resources appearing in these different performance trend categories. Thus, the focus points of the efforts of a system administrator may be quickly determined so that the system administrator's time is efficiently utilized in addressing the most urgent of issues existing in the distributed data processing system.
It should be appreciated that while the example implementation shown in
As shown in
The controller 610 may provide these metric data records to the performance monitoring engine 640. The performance monitoring engine 640 may perform various analysis of the received metric data records to aggregate these metric data records into performance measurement data or information for the resources monitored by the agent applications. The performance measurement data or information may be stored in the recent performance measurement local storage device 650. Periodically, data in the recent performance measurement local storage device 650 may be migrated by the performance monitoring engine 640 to a remotely located data warehouse storage system via the network interface 620 for warehousing until needed. The periodicity of such migrations may be user defined, such as in a configuration file or the like, associated with the performance monitoring and representation engine 600.
The consolidated chart generation engine 660, in response to a request received from a system administrator workstation or the like, via the system administrator interface 630, may access recent performance measurement data or information in the recent performance measurement local storage device 650 and historical performance measurement data or information in the remotely located data warehouse, via the network interface 620. The recent and historical performance measurement data may be analyzed by the consolidated chart generation engine 660 to generate a consolidated chart identifying the recent and historical performance trends of a plurality of resources in a single chart. Moreover, the consolidated chart generation engine 660 may obtain relative importance data, such as from a configuration file or the like, or automatically determine the relative importance of resources based on an analysis of a portion of the recent and/or historical performance measurement data. This relative importance information may be used by the consolidated chart generation engine 660 to generate representations of the resources that indicate their relative importance.
The detailed representation generation engine 670 may generate other detailed graphical representations of individual application historical performance measurements, or only recent performance measurements for a subset of resources, or the like. These detailed representations may be linked to the representations of resources in the consolidated chart generated by the consolidated chart generation engine 660 such that the selection of an element in the consolidated chart may result in the presentation of a detailed representation generated by the detailed representation generation engine 670. The consolidated chart and detailed representations may be presented to a user via their workstation and the system administrator interface 630 in response to a request from the user.
As shown in
The performance monitoring and representation engine may further retrieve, or generate, relative importance measurement data for the various resources (step 730). The recent and historical performance measurement data are used to identify a position within a consolidated representation at which a representation for each resource is to be centered (step 740). A size of the representation for each resource is determined based on the relative importance measurement data (step 750). The consolidated representation of resources of the data processing system is generated with representations for each resource being positioned at the positions determined in step 740 and having sizes determined in step 750 (step 760). Detailed graphical representations of performance measurement data for each of the resources is generated (step 770) and these detailed graphical representations are linked with user selectable representations of the corresponding resources in the consolidated representation of resources (step 780). The consolidated representation of resources is returned to the source of the request (step 790).
A determination is made as to whether a selection of a resource representation in the consolidated representation is received (step 800). If not, the operation determines if an exit condition has occurred, e.g., system administrator logs off of the system or the like (step 810). If not, the operation returns to step 800. If an exit condition has occurred, the operation terminates.
If a selection of a resource representation in the consolidated representation is received, then a corresponding linked detailed graphical representation is returned to the source of the request (step 820). The operation then returns to step 800.
Thus, the illustrative embodiments provide mechanisms for generating and presenting a consolidated representation of the recent and historical performance trends of a plurality of resources in a single representation. The mechanisms of the illustrative embodiments alleviate the frustration of using multiple views to present historical performance measurement data for resources or using a limited view of only recent performance measurement data for a limited number of resources. With the consolidated representation of the illustrative embodiments, a user may quickly obtain an understanding of the recent and historical performance trends of resources and their relative importance such that efforts may be quickly directed to areas where these efforts are most needed to efficiently improve the overall performance of the data processing system.
As noted above, it should be appreciated that the illustrative embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment containing both hardware and software elements. In one exemplary embodiment, the mechanisms of the illustrative embodiments are implemented in software or program code, which includes but is not limited to firmware, resident software, microcode, etc.
A data processing system suitable for storing and/or executing program code will include at least one processor coupled directly or indirectly to memory elements through a system bus. The memory elements can include local memory employed during actual execution 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 execution.
Input/output or I/O devices (including but not limited to keyboards, displays, pointing devices, etc.) can be coupled to the system either directly or through intervening I/O controllers. Network adapters 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 private or public networks. Modems, cable modems and Ethernet cards are just a few of the currently available types of network adapters.
The description of the present invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiment was chosen and described in order to best explain the principles of the invention, the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.
