Abstract: Computer systems attempt to manage resource pools of a dynamic number of similar resources and work tasks in order to optimize system performance. Work requests are received into the resource pool having a dynamic number of resources instances. An instance-throughput curve is determined that relates a number of resource instances in the resource pool to throughput of the work requests. A slope of a point on the instance-throughput curve is estimated with stochastic gradient approximation. The number of resource instances for the resource pool is selected when the estimated slope of the instance-throughput curve is zero.

Abstract: A process in a computer system creates and uses a meta-scheduler with meta-contexts that execute on meta-virtual processors. The meta-scheduler includes a set of schedulers with scheduler-contexts that execute on virtual processors. The meta-scheduler schedules the scheduler-contexts on the meta-contexts and schedules the meta-contexts on the meta-virtual processors which execute on execution contexts associated with hardware threads.

Abstract: The invention enables server administrators (SAs) to improve their productivity and performance. With the methods and systems described herein, the prior art needed to search for appropriate tools for appropriate tasks is minimized and/or eliminated. Easier scripting and automation that does not require implementation across tools is provided. A consistent logical place is provided for all resources to be used. Standardization of tools enables improvements in service quality. Tools may be provided using one unambiguous authoritative data model, which eliminates data inconsistencies between sources. With the invention, updates to service delivery clients may be delivered more quickly. The invention also reduces costs for developing, deploying, and maintaining a tightly integrated service delivery client. Integration may be provided from the bottom up rather than after the fact.

Abstract: Techniques are disclosed for combining multiple benchmarks for use in assessing characteristics of a computing system. For example, a method for configuring and running multiple benchmarks includes the following steps. A multiple benchmark specification is obtained. The multiple benchmark specification includes multiple individual benchmark specifications and a multiple benchmark workflow describing an ordering according to which the multiple individual benchmarks are to be configured and run. The multiple benchmarks are configured and run according to the ordering identified in the multiple benchmark workflow. Results of the multiple benchmark runs are recorded. One or more specifications or results associated with at least one of the multiple benchmarks are utilized as part of a benchmark specification for at least another of the multiple benchmarks so as to provide consistency between at least the one and the other of the multiple benchmarks.

Abstract: Automated or autonomic techniques for managing deployment of one or more resources in a computing environment based on varying workload levels. The automated techniques may comprise predicting a future workload level based on data associated with the computing environment. Then, an estimation is performed to determine whether a current resource deployment is insufficient, sufficient, or overly sufficient to satisfy the future workload level. Then, one or more actions are caused to be taken when the current resource deployment is estimated to be insufficient or overly sufficient to satisfy the future workload level. Actions may comprise resource provisioning, resource tuning and/or admission control.

Abstract: In one embodiment, functional system elements are added to an autonomic manager to enable automatic online sample interval selection. In another embodiment, a method for determining the sample interval by continually characterizing the system workload behavior includes monitoring the system data and analyzing the degree to which the workload is stationary. This makes the online optimization method less sensitive to system noise and capable of being adapted to handle different workloads. The effectiveness of the autonomic optimizer is thereby improved, making it easier to manage a wide range of systems.

Abstract: In one embodiment, functional system elements are added to an autonomic manager to enable automatic online sample interval selection. In another embodiment, a method for determining the sample interval by continually characterizing the system workload behavior includes monitoring the system data and analyzing the degree to which the workload is stationary. This makes the online optimization method less sensitive to system noise and capable of being adapted to handle different workloads. The effectiveness of the autonomic optimizer is thereby improved, making it easier to manage a wide range of systems.

Abstract: Techniques for constructing and using models in accordance with service level management are disclosed. In one aspect of the invention, a technique for constructing a model (e.g., a system model) representative of a resource for use in managing a service associated with the resource, comprises the following steps/operations. A set of resource metrics is obtained in accordance with a resource abstract model (RAM) associated with the resource. Then, a model representative of the resource is constructed based on at least a portion of the set of resource metrics obtained from the resource abstract model.

Abstract: An adaptive throttling system for minimizing the impact of non-production work on production work in a computer system is provided. The adaptive throttling system throttles production work and non-production work to optimize production. The adaptive throttling system allows system administrators to specify a quantified limit on the performance impact of non-production or utility work on production work. The throttling rate of the utility is then automatically determined by a supervisory agent, so that the utilities' impact is kept within the specified limit. The adaptive throttling system adapts dynamically to changes in workloads so as to ensure that valuable system resources are well utilized and utility work is not delayed unnecessarily.

Abstract: Techniques are provided for use in accordance with relates to computing utilities. For example, in one aspect of the invention, a method for use in a computing utility, wherein the computing utility comprises a plurality of application service provider systems and a utility controller, and each application service provider system comprising an application controller, comprises the following steps. An application request to one of the plurality of application service provider systems is obtained. Then, in response to the application request, at least one of: (i) the application controller of the application service provider system to which the application request is directed computes a value of a business metric associated with a resource action; and (ii) the utility controller computes a value of a business metric associated with a resource action.

Abstract: Electronic contracts or “eContracts” for representing service level agreements are provided. In one illustrative embodiment, the eContract may comprise information pertaining to: (a) descriptions of business transactions in IT terms; (b) financial implications of business transaction service levels; and (c) reporting to be done in business terms. Of course, the eContract may comprise other terms and conditions. In an illustrative aspect of the invention, a system for managing IT resources in terms of business financials comprises an electronic contract authoring system or “ecAuthoring system,” an electronic contract manager module or “ecManager,” and one or more electronic contract agent modules or “ecAgents” that may run on IT elements (e.g., components of the network) that are being managed. Analysts interact with the ecAuthoring system to construct eContracts. An eContract is input to an ecManager that interprets the contract to report on and optimize IT resources based on business financials.

Abstract: Methods and systems are described for learning correlation rules used in event management. In one aspect of the invention, a method comprises the steps of: (a) marking one or more event groupings; (b) employing a machine learning program to learn the underlying concept of these groupings; (c) including a rule right-hand side; and (d) putting the new rule in the Rule DB. A system to implement this method may comprise components for: (1) interactive visualization and user interface control; (2) query-based learning; (3) Event DB access; and (4) correlation Rule DB access.

Abstract: Methods and arrangements for planning and scheduling change management requests in computing systems are disclosed. Included are an arrangement for deciding whether or not an RFC should be done, an arrangement for assigning individual tasks to acceptable servers for each RFC to be done, and an arrangement for assigning the start times to said individual tasks for each RFC to be done.

Abstract: Techniques for use in accordance with application performance decomposition are provided which take advantage of the communications protocol used to carry a transaction between application components in a distributed computing network. Specifically, the invention extends the communications protocol by embedding data, such as timestamp and duration measurement data, in the protocol itself, rather than extending or altering the application or transaction data carried by the protocol as in existing approaches. Thus, the invention provides natural correlation of interactions of distributed application components on such transactions without modification to the application or transaction data. Because the correlation is performed in-line with the application component interactions, minimal data management overhead is required, and correlated performance decomposition is made possible in real-time for the transaction.

Abstract: A process in a computer system creates and uses a meta-scheduler with meta-contexts that execute on meta-virtual processors. The meta-scheduler includes a set of schedulers with scheduler-contexts that execute on virtual processors. The meta-scheduler schedules the scheduler-contexts on the meta-contexts and schedules the meta-contexts on the meta-virtual processors which execute on execution contexts associated with hardware threads.

Abstract: The described implementations relate to calendar event scheduling. One system includes a storage component configured to store scheduling constraints relating to at least one user. The system also includes a declarative calendar component configured to automatically schedule declarative calendar events for the at least one user based upon the scheduling constraints.

Abstract: Computer systems attempt to manage resource pools of a dynamic number of similar resources and work tasks in order to optimize system performance. Work requests are received into the resource pool having a dynamic number of resources instances. An instance-throughput curve is determined that relates a number of resource instances in the resource pool to throughput of the work requests. A slope of a point on the instance-throughput curve is estimated with stochastic gradient approximation. The number of resource instances for the resource pool is selected when the estimated slope of the instance-throughput curve is zero.

Abstract: Techniques for data-driven validation, completion and construction of event relationship networks (ERNs) are provided. Event relationship networks are widely used in event management system design. To date, ERNs are constructed purely based on human expertise and there is no automatic or event semi-automatic method that validates or completes ERNs. The present invention provides techniques for automatically validating and completing existing ERNs and/or constructing new ERNs, based on collected event data.

Abstract: Electronic contracts or “eContracts” for representing service level agreements are provided. In one illustrative embodiment, the eContract may comprise information pertaining to: (a) descriptions of business transactions in IT terms; (b) financial implications of business transaction service levels; and (c) reporting to be done in business terms. Of course, the eContract may comprise other terms and conditions. In an illustrative aspect of the invention, a system for managing IT resources in terms of business financials comprises an electronic contract authoring system or “ecAuthoring system,” an electronic contract manager module or “ecManager,” and one or more electronic contract agent modules or “ecAgents” that may run on IT elements (e.g., components of the network) that are being managed. Analysts interact with the ecAuthoring system to construct eContracts. An eContract is input to an ecManager that interprets the contract to report on and optimize IT resources based on business financials.

Abstract: Techniques are provided for generically controlling one or more resources associated with at least one computing system. In one aspect of the invention, the technique comprises evaluating one or more performance metrics associated with the one or more resources given one or more configurations of the one or more resources. The technique then causes a change in the one or more configurations of the one or more resources based on the performance metric evaluating step. The one or more performance metrics and the one or more configurations are expressed in generic formats.