Abstract:
A workload identifier program works in conjunction with an autonomic manager to calculate a workload representation during a pre-determined interval, calculate a similarity metric for the current workload representation by comparing the current workload representation to workload representations during the previous pre-determined intervals, comparing the similarity metric to a threshold value, and responsive to a determination that the similarity metric exceeds the threshold value, either: ( 1 ) issuing notifications to the autonomic manager so that the autonomic manager will ignore a plurality of data points and tune the application server with pre-determined recommendations designed for the dramatically increased workload (if the autonomic manager is a runtime autonomic manager), or ( 2 ) providing notification to the administrator about the dramatic increase in workload conditions by changing the color of the current interval (if the autonomic manager is a graphical autonomic manager).

Description:
FIELD OF THE INVENTION  
       [0001]     The present invention relates to electrical computer data processing in general, and, specifically, to monitoring and analysis of application server workload.  
       BACKGROUND OF THE INVENTION  
       [0002]     Application servers provide services to clients on a network or the World Wide Web through service providers. When a client asks an application server to run a program or provide data, it is called a service request. Different types of service requests require different service provider resources, and as the number of requests increase, the demands on service provider resources increase. Service provider resources may include, without limitation, central processing units, memory, thread pools, connection pools and session caches. Application servers run a resource allocation program, called an autonomic manager, to allocate system resources to the service providers.  
         [0003]     Autonomic managers record the number and type of service requests. The autonomic manager analyzes historical trends based upon data points in the service requests in order to predict the number and type of service requests the application server will have in the future. Using this workload prediction, the autonomic manager recommends ways to optimize allocation of the system resources to the service providers. The optimizing and reallocating of system resources is known as tuning.  
         [0004]     United States Patent Application US 2004/0054780 discloses an autonomic manager that measures and calculates the workload on a server cluster by analyzing the number and type of requests associated with each application in use. When the autonomic manager determines the workload is low, servers are removed from service, and when the load increases, servers are added into service. The manager can also change what application is running on specific servers if the load on one application increases and the load on another application decreases. The autonomic manager compares the current workload on the cluster to a predefined standard to determine whether the workload is high or low.  
         [0005]     Optimization recommendations from an autonomic manager are based upon historical trend analysis of workload data. When the load is constant, or when the changes in load occur gradually, the historical trend analysis provides satisfactory indications. But, in a situation where the workload changes dramatically the optimization recommendations will be based primarily on analysis of old workload data that may not be applicable to the current workload. Thus, in instances where the workload changes dramatically, the historical trend analysis of workload data may be misleading or inaccurate and prevent an improved allocation of resources to handle the new workload patterns.  
         [0006]     A need exists for an autonomic manager that can recognize dramatic changes in workload, and upon such recognition, cause the autonomic manager to ignore the data points of the historical trend analysis and either tune the application server in accordance with pre-determined recommendations for the recognized dramatic change, or notify the administrator so that appropriate action can be taken.  
       SUMMARY OF THE INVENTION  
       [0007]     The invention that meets the need identified above is a workload identifier program that works in conjunction with an autonomic manager, a configuration program, a rules file, a factors file, a weights file, an integer file and a threshold file.  
         [0008]     The autonomic manager retrieves appropriate factors from the factors file, monitors assigned servers, calculates data points for the retrieved factors, and compares the data points for each factor to one or more applicable rules in the rules file. If one or more rules in the rules file call for a change in resource allocation, the AM issues instructions for re-allocation of the resource specified by the rule. The configuration program ensures entry of a threshold value in the threshold file, selection of weighted factors or integer factors, and identification of whether the autonomic manager is a runtime autonomic manager or a graphical autonomic manager.  
         [0009]     The workload identifier program retrieves the most recent factor values for a selected application server from storage, calculates a workload representation for the selected application server during a pre-determined interval, calculates a similarity metric for the current workload representation by comparing the current workload representation to workload representations during the previous predetermined intervals, compares the similarity metric to the threshold value from the threshold file, and responsive to a determination that the similarity metric exceeds the threshold value, recognizes the current interval as a dramatically increased workload. Upon recognizing the current interval as a dramatically increased workload, the workload identifier program either: (1) issues notifications to the autonomic manager so that the autonomic manager will ignore the data points and tune the application server with pre-determined recommendations designed for the dramatically increased workload (if the autonomic manager is a runtime autonomic manager), or (2) provides notification to the administrator about the dramatic increase in workload conditions by changing the color of the current interval (if the autonomic manager is a graphical autonomic manager). 
     
    
     BRIEF DESCRIPTION OF DRAWINGS  
       [0010]     The novel features believed characteristic of the invention are set forth in the appended claims. The invention itself, however, as well as a preferred mode of use, further objectives and advantages thereof, will be understood best by references to the following detailed description of an illustrative embodiment when read in conjunction with the accompanying drawings, wherein:  
         [0011]      FIG. 1  illustrates an application server connected to a network.  
         [0012]      FIG. 2  illustrates the components of the workload identifier program in a storage.  
         [0013]      FIG. 3  is a flowchart of the autonomic manager.  
         [0014]      FIG. 4  is a flowchart of the configuration program.  
         [0015]      FIG. 5  is a flowchart of the workload identifier program. 
     
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT  
       [0016]     The principles of the present invention are applicable to a variety of computer hardware and software configurations. The term “computer hardware” or “hardware,” as used herein, refers to any machine or apparatus that is capable of accepting, performing login operations on, storing, or displaying data, and includes without limitation processors and memory; the term “computer software” or “software,” refers to any set of instructions operable to cause computer hardware to perform an operation. The term “computer,” as used herein, includes without limitation any useful combination of hardware and software, and a “computer program” or “program” includes without limitation any software operable to cause computer hardware to accept, perform logic operations on, store or display data. A computer program may, and often is, comprised of a plurality of smaller programming units, including without limitation subroutines, modules, functions, methods and procedures. Thus, the functions of the present invention may be distributed among a plurality of computers and computer programs. The invention is described best, though, as a single computer program that configures and enables one or more general purpose computers to implement the novel aspects of the invention. For illustrative purposes, the inventive computer program will be referred to as the “workload identifier program.” 
         [0017]     Additionally, the workload identifier program is described below with references to an exemplary network of hardware devices, as depicted in  FIG. 1 . A “network” 0  comprises any number of hardware devices coupled to and in communication with each other through a communications medium, such as the Internet. A “communications medium” includes without limitation any physical, optical, electromagnetic, or other medium through which hardware or software can transmit data. For descriptive purposes, exemplary network  100  has only a limited number of nodes, including workstation computer  105 , workstation computer  110 , server computer  115 , and persistent storage  120 . Network connection  125  comprises all hardware, software, and communications media necessary to enable communication between network nodes  105 - 120 . Unless otherwise indicated in context below, all network nodes use publicly available protocols or messaging services to communicate with each other through network connection  125 .  
         [0018]     Referring to  FIG. 2 , workload identifier program  500  typically resides in storage, represented schematically as storage  200  in  FIG. 2 . The term “storage,” as used herein, includes without limitation any volatile or persistent medium, such as an electrical circuit, magnetic disk, or optical disk, or a memory in which a computer can store data or software for any duration. A single storage may encompass and be distributed across a plurality of media. Thus,  FIG. 2  is included merely as a descriptive expedient and does not necessarily reflect any particular physical embodiment of storage  200 . Storage  200  may include additional data and programs. Of particular import to workload identifier  500 , storage  200  may include autonomic manager  300 , configuration program  400 , rules file  208 , factors file  220  weights file  230 , integer file  240 , and threshold file  250 . Rules file  208  contains a first set of rules that will be analyzed by autonomic manager  300  in response to data points generated by autonomic manager  300 , and a second set of rules that will be analyzed by workload identifier program  500  when a dramatic workload is recognized. Factors file  220  contains the factors for which autonomic manager  300  will monitor assigned servers and calculate data points. Examples of factors include, without limitation, total number of requests per second, requests per second for each application component, database connection requests per second, central processing unit usage, and the number of active applications. Weights file  230  contains weights to be assigned to each of the factors in factors file  220  by workload identifier program  500  when configured to use weighted factors in formulating a workload representation. Integer file  240  contains integer array formats to be used by workload identifier program  500  when configured to use integer factors in formulating a workload representation. Threshold file  250  contains a first set of threshold values for weighted factor workload representations and a second set of threshold values for integer workload representations.  
         [0019]     Referring to  FIG. 3 , autonomic manager  300  starts ( 302 ), sets an interval ( 310 ), and retrieves selected factors from factors file  220  ( 312 ). Autonomic manager  300  monitors assigned application servers ( 314 ), requests data for each selected factor from each of the selected application servers ( 316 ), receives the data from the selected application servers ( 318 ), and stores the data ( 320 ). Autonomic manager  300 , selects an application server ( 322 ), calculates data points for the values for each of the factors ( 324 ), uses these data points to analyze rules in rules file  208  ( 326 ), determines whether a change is to be made based upon the results of rules analysis ( 328 ). If one or more rules in rules file  208  call for a change in resource allocation, autonomic manager  300  issues instructions for re-allocation of the resource specified by the rule ( 330 ). Autonomic manager  300  determines whether there is another application server ( 332 ), and if so, goes to step  322 . If not, autonomic manager  300  determines whether there is another interval ( 334 ), and if so, goes to step  314 , or if not, stops ( 340 ).  
         [0020]      FIG. 4  depicts a flow chart for configuration program  400 . Configuration program  400  starts ( 402 ) and prompts the user to enter one or more threshold values, and stores the threshold values in threshold file  250  ( 410 ). Configuration program  400  prompts the user to select a weighted format or an integer format ( 420 ). Configuration program  400  determines whether the user selected weighted format or integer format ( 430 ). If the user chose weighted format, configuration program  400  prompts the user to review the current weights applied to each of the factors and make any changes that may be desired ( 450 ). If the user chose integer format, configuration program  400  prompts the user to review the current integer formats and make any changes that may be desired ( 440 ). Configuration program  400  prompts the user to indicate whether autonomic manager  300  is a runtime autonomic manager or a graphical autonomic manager ( 460 ). Configuration program  400  stops ( 470 ).  
         [0021]      FIG. 5  depicts a flow chart for workload identifier program  500 . Workload identifier program  500  starts ( 502 ), selects a server for examination ( 510 ), and retrieves the most recent factor values for the selected application server from storage  210  ( 512 ). Using the most recent factor values, workload identifier program  500  calculates a workload representation for the selected server ( 514 ).  
         [0022]     Workload identifier program  500  may calculate the workload representation in two ways, depending on whether the user configured workload identifier program  500  to use a weighted factor data structure or an integer array format. If configured for a weighted factor data structure, workload identifier program  500  calculates the workload representation as a set of weighted factor values by placing the most recent factor values for the application server in a standard data structure, retrieving the weights for each factor from weights file  230 , and applying the appropriate weight to each of the factor values in the data structure. Suitable standard data structures include without limitation a matrix, or a multiple variable vector. If configured for an integer array format, workload identifier program  500  calculates the workload representation by retrieving an integer array format from integer file  240  and placing the most recent factor values for the application server, into the integer array format.  
         [0023]     When using an integer array format, the integer array format preferably comprises a byte array divided into equal subsections. For example, a byte array having 16 bits may be divided into four subsections sections each containing 4 bits. Division of a byte array limits the number of factors that may be represented in the array; however, this limitation may be overcome by combining similar factors within a single sub-section of the byte array. Each subsection represents a factor. Subsections may be given different weights based upon location in the array, and factors may then be assigned a weight based upon the factors placement in the array. The values of the byte array sub-sections represent the weight of that factor. For example, if one factor was central processing unit (cpu) usage with a maximum value of 15, and the cpu usage factor was 20% of the cpu capacity, the value of 15 may be represented as the byte array 1111, and the factor representing 20% usage would be set to 3, represented by the byte array 0011. Using byte arrays, the workload identifier program can represent a complex workload representation as a small integer set that can be compared so that the similarity of the integer representation would be proportional to the similarity of the weighted factors  
         [0024]      500  takes the current workload representation and calculates a similarity metric ( 515 ). As used herein, the term similarity metric means a value derived by comparing the workload representation for the current interval to the stored workload representation values for each of the previous intervals ( 515 ). When using weighted factors, workload identifier program  500  calculates a standard mathematical similarity metric for the data structure. When using integer factors, workload identifier  500  determines the similarity metric by calculating the percentage difference of the integer values representing the workload representation being compared. The threshold value for a weighted factor comparison comprises the valid bounds for the similarity metric and depends upon the specific similarity metric computation utilized. The threshold for a integer factor comparison would be the maximum allowed percentage difference.  
         [0025]     Workload identifier program  500  retrieves the threshold value from threshold file  250  ( 516 ), and determines whether the similarity metric is greater than the threshold value ( 518 ). If the threshold value is exceeded, workload identifier  500  determines whether autonomic manager  300  is a runtime autonomic manager, or a graphical autonomic manager ( 520 ). If autonomic manager  300  is a runtime autonomic manager, workload identifier program  500  instructs autonomic manager  300  to ignore all data points and to only examine the most recent interval ( 522 ). Additionally, workload identifier program  500  instructs autonomic manager  300  to cancel any pending tuning instructions. Workload identifier program  500  determines whether autonomic manager  300  is a graphical autonomic manager ( 524 ), and if so, workload identifier program  500  changes the background color of the current period with the workload on the graphical display to identify the change in workload to the administrator, so that the administrator may make reallocations ( 526 ). Workload identifier program  500  determines whether the user desires advice ( 528 ) and if so, workload identifier program  500  instructs autonomic manager  300  to provide re-allocation recommendations to the user ( 530 ). Workload identifier program  500  determines whether there is another server ( 540 ), and if so goes to step  510 , or if not, stops ( 550 ).  
         [0026]     A preferred form of the invention has been shown in the drawings and described above, but variations in the preferred form will be apparent to those skilled in the art. The preceding description is for illustrative purposes only, and the invention should not be construed as limited to the specific form shown and described. The scope of the invention should be limited only by the language of the following claims.