Patent Application
20060089982
1. Field of the Invention
The present invention generally relates to data collection systems. More particularly, the present invention provides a method, system, and computer program product for capacity planning by function.
2. Related Art
Capacity planning involves balancing capacity with demand. Capacity is the amount of traffic or processing that a resource is capable of supporting; demand is the load that users or applications place upon that resource. Capacity planning is the process used to evaluate the current trends in resource usage and plan for growth and changes before problems occur. Capacity planning's benefits range from avoiding the inconvenience of running out of disk space to ensuring enough processing power to handle a global organization's computing workload.
Resource use metrics are generally collected and capacity planning projections are done on a server-by-server basis. In today's on-demand world (e.g., dynamic provisioning, server farms, etc.), however, these measurements and projections also should be done in dynamic groupings based on function, since understanding the performance of a business function outweighs the performance of an individual machine. Unfortunately, currently available methodologies fail to provide capacity planning by function.
In general, the present invention provides a method, system, and computer program product for capacity planning by function.
A first aspect of the present invention is directed to a method for capacity planning by function, comprising: periodically collecting metrics for a plurality of components in a dynamic system; periodically determining dynamic system membership for a function provided by the dynamic system; providing at least one summation formula; and determining system wide metrics by function using the component metrics, the dynamic system membership for the function, and the at least one summation formula.
A second aspect of the present invention is directed to a system for capacity planning by function, comprising: a system for periodically collecting metrics for a plurality of components in a dynamic system; a system for periodically determining dynamic system membership for a function provided by the dynamic system; a system for providing at least one summation formula; and a system for determining system wide metrics by function using the component metrics, the dynamic system membership for the function, and the at least one summation formula.
A third aspect of the present invention is directed to a program product stored on a recordable medium for capacity planning by function, which when executed comprises: program code for periodically collecting metrics for a plurality of components in a dynamic system; program code for periodically determining dynamic system membership for a function provided by the dynamic system; program code for providing at least one summation formula; and program code for determining system wide metrics by function using the component metrics, the dynamic system membership for the function, and the at least one summation formula.
A fourth aspect of the present invention is directed to a method for deploying an application for capacity planning by function, comprising: providing a computer infrastructure being operable to: periodically collect metrics for a plurality of components in a dynamic system; periodically determine dynamic system membership for a function provided by the dynamic system; provide at least one summation formula; and determine system wide metrics by function using the component metrics, the dynamic system membership for the function, and the at least one summation formula.
A fifth aspect of the present invention is directed to computer software embodied in a propagated signal for capacity planning by function, the computer software comprising instructions to cause a computer system to perform the following functions: periodically collect metrics for a plurality of components in a dynamic system; periodically determine dynamic system membership for a function provided by the dynamic system; provide at least one summation formula; and determine system wide metrics by function using the component metrics, the dynamic system membership for the function, and the at least one summation formula.
These and other features of this invention will be more readily understood from the following detailed description of the various aspects of the invention taken in conjunction with the accompanying drawings in which:
The drawings are merely schematic representations, not intended to portray specific parameters of the invention. The drawings are intended to depict only typical embodiments of the invention, and therefore should not be considered as limiting the scope of the invention. In the drawings, like numbering represents like elements.
As indicated above, the present invention provides a method, system, and computer program product for capacity planning by function.
The present invention gathers relationship data on the same interval as performance metrics in order to correlate the data by function. Automatically correlating this data is important to being able to properly perform on-demand capacity planning.
The present invention provides the means and intelligence for the flexible correlation of individual component metric values into dynamically grouped metrics. To accomplish this, the attributes of the larger dynamic (e.g., on-demand) system (whether it is a server pool, clustered system, application components running on varied hosts, etc.) are themselves monitored and recorded at a rate similar to the collection/aggregation of individual component performance metrics.
In a typical data-warehousing environment, the components that make up a dynamic system are considered attributes or dimensions of the component. The dynamic system magnifies one of the classic data warehousing conundrums of dealing with slowly changing attributes, since the dynamic provisioning of resources, required by on-demand capacity management, causes rapid and frequent system changes. The present invention handles the changing attributes as additional metrics of the dynamic system.
Currently, component/measurement data warehouse schemas, such as Tivoli's implementation (as of Tivoli Data Warehouse v1.2, available from International Business Machines, Inc. of Armonk, N.Y.), have a two sided structure. The component side of the schema tracks individual components such as servers, applications, application components, and interfaces. Metric values are stored in attribute tables to describe nearly static information about these components. Component hierarchies may also be recorded to show nearly static relationships between components. The measurement side of the schema describes the individual measurements that are made against the components. A measurement fact table stores the measurement data along with the required link to the component being measured. The present invention provides a third specialized schema to hold the dynamic system attributes as if they were non-numeric metrics of the system. This system schema records the dynamic system membership, measured at, or near, the pace of the individual component metric measurements. Component instances are recorded in the component schema and dynamic system membership is contained in a membership table in the new system schema. The measurements made against the existing components of the dynamic system are recorded, by relationship, to the measurement schema, in the system schema.
To facilitate the calculation of numeric metric measurements against the dynamic system, several steps are taken. First, the dynamic system is recorded in the component structure as a component itself. Second, for all desired metrics, the appropriate “summation” formulas are identified/provided. These formulas provide the ability to determine appropriate system wide metrics from the metrics values collected for the system components supporting each function of interest. For example, one summation formula may be the standard deviation of the average of the metric values collected for the system components supporting a function. Other examples may include the average of all averaged values for a metric, the maximum of all maximum metric values, the minimum of all the minimum metric values, etc. Many other summation formulas are also possible. These calculations relate to, and are derived from, the types of metric values commonly stored in a data warehouse, including minimum, maximum, average, and/or total measured values, recorded in a given time interval. These system formulas, and their appropriateness towards individual metrics, are stored as part of the system schema and the relationship is formed to the measurement schema. Lastly, ETLs (extract, transform, and load scripts) consult the dynamic system summation formulas to populate the dynamic system measurements in the system schema.
In summary, the invention includes the following:
(1) The incremental extraction/determination of dynamic system membership;
(2) Data-warehouse schema enhancement to store the component, measurement, and attribute data for the dynamically provisioned system;
(3) Standard system summation formulas for desired metrics, and the ability to accommodate user defined system summation formulas; and
(4) ETLs to fill the new system schema, and provide the means for deriving system metrics from member metric measurements.
Referring to
In step S2, dynamic system membership by function is periodically determined for at least one predetermined function provided by the dynamic system. The dynamic system membership is determined at, or near, the rate of the individual component metric measurements. For example, in a dynamic system comprising a pool of servers (server A, server B, server C, . . . , server N), dynamic system membership for the servers in the pool which support a given function X is periodically determined. This example is illustrated in greater detail with reference to
In
At a time T1, the membership determining system 212 determines that servers 204A, 204B, and 204E of the server pool 202 support function X. The dynamic system membership in server pool 202 for function X at time T1 is indicated by reference numeral 214 in
In accordance with the present invention, a function can comprise any type of task, process, etc., performed by one or more of the components of a system being monitored. For example, function X may comprise the “view item” function of an on-line auction system (e.g., users may request to view an item up for bid on an on-line auction site such as Ebay®). To this extent, assuming that the “view item” function is supported by the server pool 202 (
Referring back to the flow diagram 100 depicted in
In step S5, one or more standard and/or user defined “summation” formulas are identified/provided for at least one desired metric. The summation formula(s) determined in step S5 are stored in step S6. The summation formulas provide the ability to form appropriate system wide metrics by function from the metric values collected for the system components supporting each function of interest. For example, one summation formula may comprise the average value of a metric determined for each of the components supporting a given function at a given time. Many other types of summation formulas are also possible, depending on the type of system being monitored, the functions provided by such systems, etc. In step S7, the system wide metrics by function are calculated using the dynamic system membership by function, summation formulas, and component metrics by a system wide metric determining system 222.
In Table 2, the summation formula used is the average of Metric A for each of the components supporting function X at a given time. At time T1, for example, the summation formula calculates a value of 76% for function X. That is, the average value of Metric A for the servers 204A, 204B, and 204E that support function X at T1 is 76%. Similarly, at times T2 and T3, the summation formula calculates values of 95% and 16%, respectfully, which indicate that the average value of Metric A for the servers 204A, 204C, 204D, and 204N that support function X at T2 is 95%, while the average value of Metric A for the servers 204B and 204C that support function X at time T3 is 16%. Similar data can be calculated for other metrics using the same/different summation formulas to provide a wide variety of information that can be used for capacity planning by function.
In step S8, the system wide metrics by function determined in step S7 are stored (e.g., in metric storage system 210,
Referring now to
Data 502 (e.g., component metrics, dynamic system membership by function, summation formulas, system wide metrics by function) used in the practice of the present invention can be stored locally to computer system 500, for example, in storage unit 504, and/or may be provided to computer system 500 over a network 505. Storage unit 504 can be any system capable of providing storage for data and information under the present invention. As such, storage unit 504 may reside at a single physical location, comprising one or more types of data storage, or may be distributed across a plurality of physical systems in various forms. In another embodiment, storage unit 504 may be distributed across, for example, a local area network (LAN), wide area network (WAN) or a storage area network (SAN) (not shown). Network 505 is intended to represent any type of network over which data can be transmitted. For example, network 505 can include the Internet, a wide area network (WAN), a local area network (LAN), a virtual private network (VPN), a WiFi network, a personal area network (PAN), or other type of network. To this extent, communication can occur via a direct hardwired connection or via an addressable connection in a client-server (or server-server) environment that may utilize any combination of wireline and/or wireless transmission methods. In the case of the latter, the server and client may utilize conventional network connectivity, such as Token Ring, Ethernet, WiFi or other conventional communications standards. Where the client communicates with the server via the Internet, connectivity could be provided by conventional TCP/IP sockets-based protocol. In this instance, the client would utilize an Internet service provider to establish connectivity to the server.
As shown, computer system 500 generally includes a processing unit 506, memory 508, bus 510, input/output (I/O) interfaces 512 and external devices/resources 514. Processing unit 506 may comprise a single processing unit, or may be distributed across one or more processing units in one or more locations, e.g., on a client and server. Memory 508 may comprise any known type of data storage and/or transmission media, including magnetic media, optical media, random access memory (RAM), read-only memory (ROM), etc. Moreover, similar to processing unit 506, memory 508 may reside at a single physical location, comprising one or more types of data storage, or be distributed across a plurality of physical systems in various forms.
I/O interfaces 512 may comprise any system for exchanging information to/from an external source. External devices/resources 514 may comprise any known type of external device, including speakers, a CRT, LED screen, handheld device, keyboard, mouse, voice recognition system, speech output system, printer, monitor/display (e.g., display 516), facsimile, pager, etc.
Bus 510 provides a communication link between each of the components in computer system 500, and likewise may comprise any known type of transmission link, including electrical, optical, wireless, etc. In addition, although not shown, other components, such as cache memory, communication systems, system software, etc., may be incorporated into computer system 500.
Shown in memory 508 is a capacity planning system 518, which may be provided as a computer program product. Capacity planning system 518 includes a metric collection system 520 for monitoring a plurality of components 552 of a dynamic (e.g., on demand) system 550 and for periodically collecting metrics for the plurality of the components 552, and a membership determining system 522 for periodically determining membership by function of the components 552 of the dynamic system 550. Also provided in memory 508 of capacity planning system 518 is a summation formula system 524 for providing standard and/or user defined summation formulas, and a system wide metric determining system 526 for determining system wide metrics by function using the dynamic system membership by function provided by the membership determining system 522, summation formulas provided by the summation formula system 524, and component metrics provided by the metric collection system 520.
It should be appreciated that the teachings of the present invention can be offered as a business method on a subscription or fee basis. For example, computer system 500 could be created, maintained, supported, and/or deployed by a service provider that offers the functions described herein for customers. That is, a service provider could be used to provide capacity planning by function, as described above.
It also should be understood that the present invention can be realized in hardware, software, a propagated signal, or any combination thereof. Any kind of computer/server system(s)—or other apparatus adapted for carrying out the methods described herein—is suited. A typical combination of hardware and software could be a general purpose computer system with a computer program that, when loaded and executed, carries out the respective methods described herein. Alternatively, a specific use computer, containing specialized hardware for carrying out one or more of the functional tasks of the invention, could be utilized. The present invention can also be embedded in a computer program product or a propagated signal, which comprises all the respective features enabling the implementation of the methods described herein, and which—when loaded in a computer system—is able to carry out these methods. Computer program, propagated signal, software program, program, or software, in the present context mean any expression, in any language, code or notation, of a set of instructions intended to cause a system having an information processing capability to perform a particular function either directly or after either or both of the following: (a) conversion to another language, code or notation; and/or (b) reproduction in a different material form.
The foregoing description of the preferred embodiments of this invention has been presented for purposes of illustration and description. It is not intended to be exhaustive or to limit the invention to the precise form disclosed, and obviously, many modifications and variations are possible. Such modifications and variations that may be apparent to a person skilled in the art are intended to be included within the scope of this invention as defined by the accompanying claims.
