Abstract: A method, system, and article are provided for monitoring performance of hardware devices. Each hardware device is configured with an agent, and the server is configured with a coordinator. The agent collects device data at a first modifiable frequency and communicates the collected data to the coordinator at a second dynamically modifiable frequency. The collected data is periodically monitored and the first and second frequencies are modified subject to evaluation of the collected and monitored data.

Abstract: Management of a planner through use of a middleware layer. A computer system is configured with the middleware layer in communication with both a planner and a data repository. One or more modules are provided in the middleware layer to support the functionality of the planner. Application program interface calls are employed to call the modules, thereby mitigating duplication of the functionality in separate planners.

Abstract: A method and system for throttling a plurality of operations of a plurality of applications that share a plurality of resources. A difference between observed and predicted workloads is computed. If the difference does not exceed a threshold, a multi-strategy finder operates in normal mode and applies a recursive greedy pruning process with a look-back and look-forward optimization to select actions for a final schedule of actions that improve the utility of a data storage system. If the difference exceeds the threshold, the multi-strategy finder operates in unexpected mode and applies a defensive action selection process to select actions for the final schedule. The selected actions are performed according to the final schedule and include throttling of a CPU, network, and/or storage.

Abstract: Embodiments of the invention relate to selecting a data restore point with an optimal recovery time and recovery point. An exemplary embodiment includes generating a problem search criterion for an entity with corrupted data. Dependencies relied on by the entity to function are determined. At least one event signature match is found that comprises information for an event being logged in a event log, and is associated with the dependencies. At least one data restore point created prior to an occurrence of a particular event in the at least one event signature match is selected. The particular event having caused the data to be corrupted. The at least one data restore point is selected to restore data to a storage system with the corrupted data.

Abstract: An optimization method and system. The method includes receiving by a computing system a data footprint associated with data and a human resource model. The data footprint comprises a primary data section, a secondary data section, and an archive data section. A plurality of data storage strategies are associated with the primary data section, said secondary data section, and said archive data section. The plurality of data storage strategies are compared to each other. A data staging orchestrator software module is executed. The computing system determines based on results of executing the data staging orchestrator software module, an optimal migration time, an optimal migration speed, and an optimal migration cost for managing storage for portions of the data. The computing system executes a risk modulation software module and determines a risk associated with the managing.

Abstract: A data center power cost accounting system uses server and storage and cooling power consumption models and device maps, together with runtime application maps, to estimate the equipment power consumption and cooling power consumption of individual applications. An approximation of the cooling cost over a period of time, for any given application, can be pieced together by adding up the equipment utilized by the application and applying the cooling estimates obtained from computational fluid dynamics (CFD) simulations. The cooling estimates can further account for changes or variability in resource usage over time since the cooling estimates are based directly on utilization. The per application power consumption costs are obtained without having to install or depend on power measurement instruments or other hardware in the datacenters.

Abstract: According to the present invention, there is provided a SAN management system to provide autonomic management of a storage system using an action-centric approach. The SAN management system includes a policy specification logic block to maintain a policy specification associated with the managed system. In addition, the SAN management system includes a reasoning logic block to provide for the determining of action rules using a combination of logic and information obtained from the policy specification. Also, the SAN management system includes a learning logic block to couple the policy specification logic block with the reasoning logic block to improve an understanding of a managed system. The learning is continuous and provides for autonomic evolvement of the system in which reliance on manual input from a user is lessened.

Abstract: An optimization method and system. The method includes receiving by a computing system a data footprint associated with data and a human resource model. The data footprint comprises a primary data section, a secondary data section, and an archive data section. A plurality of data storage strategies are associated with the primary data section, said secondary data section, and said archive data section. The plurality of data storage strategies are compared to each other. A data staging orchestrator software module is executed. The computing system determines based on results of executing the data staging orchestrator software module, an optimal migration time, an optimal migration speed, and an optimal migration cost for managing storage for portions of the data. The computing system executes a risk modulation software module and determines a risk associated with the managing.

Abstract: An optimization method and system. The method includes receiving by a computing system a data footprint associated with data and a human resource model. The data footprint comprises a primary data section, a secondary data section, and an archive data section. A plurality of data storage strategies are associated with the primary data section, said secondary data section, and said archive data section. The plurality of data storage strategies are compared to each other. A data staging orchestrator software module is executed. The computing system determines based on results of executing the data staging orchestrator software module, an optimal migration time, an optimal migration speed, and an optimal migration cost for managing storage for portions of the data. The computing system executes a risk modulation software module and determines a risk associated with the managing.

Abstract: An automated disaster recovery (DR) planning system for a computing environment is provided. A discovery module discovers servers, networks, and storage devices in a computing environment. An expert knowledge base module captures best practices in planning, and capabilities, interoperability, limitation and boundary values for different DR technologies. A match-making module determines multiple DR plans as combinations of one or more replication technologies that can be used to satisfy DR requirements. And, an optimizer configured for assessing a feasible DR plan from said multiple DR plans, to deploy for DR planning of a primary computing environment.

Abstract: Embodiments of the invention relate to selecting a data restore point with an optimal recovery time and recovery point. An exemplary embodiment includes generating a problem search criterion for an entity with corrupted data. Dependencies relied on by the entity to function are determined. At least one event signature match is found that comprises information for an event being logged in a event log, and is associated with the dependencies. At least one data restore point created prior to an occurrence of a particular event in the at least one event signature match is selected. The particular event having caused the data to be corrupted. The at least one data restore point is selected to restore data to a storage system with the corrupted data.

Abstract: A data center power cost accounting system uses server and storage and cooling power consumption models and device maps, together with runtime application maps, to estimate the equipment power consumption and cooling power consumption of individual applications. An approximation of the cooling cost over a period of time, for any given application, can be pieced together by adding up the equipment utilized by the application and applying the cooling estimates obtained from computational fluid dynamics (CFD) simulations. The cooling estimates can further account for changes or variability in resource usage over time since the cooling estimates are based directly on utilization. The per application power consumption costs are obtained without having to install or depend on power measurement instruments or other hardware in the datacenters.

Abstract: A method and system for throttling a plurality of operations of a plurality of applications that share a plurality of resources. A difference between observed and predicted workloads is computed. If the difference does not exceed a threshold, a multi-strategy finder operates in normal mode and applies a recursive greedy pruning process with a look-back and look-forward optimization to select actions for a final schedule of actions that improve the utility of a data storage system. If the difference exceeds the threshold, the multi-strategy finder operates in unexpected mode and applies a defensive action selection process to select actions for the final schedule. The selected actions are performed according to the final schedule and include throttling of a CPU, network, and/or storage.

Abstract: An optimization method and system. The method includes receiving by a computing system a data footprint associated with data and a human resource model. The data footprint comprises a primary data section, a secondary data section, and an archive data section. A plurality of data storage strategies are associated with the primary data section, said secondary data section, and said archive data section. The plurality of data storage strategies are compared to each other. A data staging orchestrator software module is executed. The computing system determines based on results of executing the data staging orchestrator software module, an optimal migration time, an optimal migration speed, and an optimal migration cost for managing storage for portions of the data. The computing system executes a risk modulation software module and determines a risk associated with the managing.

Abstract: A program storage device for managing resources in a storage system that is based on server resource usage is disclosed. The program storage device performs a method that allocates a command window to each of the servers accessing the resources, achieves an equilibrium state that balances the size of each server's command window and the amount of free resources, and maintains the equilibrium state by continually adjusting the size of each command window. The command window defines a limit on the number of outstanding storage requests that each server may maintain. The invention initially allocates a minimum sized command window.

Abstract: According to the present invention, there is provided a SAN management system to provide autonomic management of a storage system using an action-centric approach. The SAN management system includes a policy specification logic block to maintain a policy specification associated with the managed system. In addition, the SAN management system includes a reasoning logic block to provide for the determining of action rules using a combination of logic and information obtained from the policy specification. Also, the SAN management system includes a learning logic block to couple the policy specification logic block with the reasoning logic block to improve an understanding of a managed system. The learning is continuous and provides for autonomic evolvement of the system in which reliance on manual input from a user is lessened.

Abstract: According to the present invention, there is provided a SAN management system to provide autonomic management of a storage system using an action-centric approach. The SAN management system includes a policy specification logic block to maintain a policy specification associated with the managed system. In addition, the SAN management system includes a reasoning logic block to provide for the determining of action rules using a combination of logic and information obtained from the policy specification. Also, the SAN management system includes a learning logic block to couple the policy specification logic block with the reasoning logic block to improve an understanding of a managed system. The learning is continuous and provides for autonomic evolvement of the system in which reliance on manual input from a user is lessened.

Abstract: An automated disaster recovery (DR) planning system for a computing environment is provided. A discovery module discovers servers, networks, and storage devices in a computing environment. An expert knowledge base module captures best practices in planning, and capabilities, interoperability, limitation and boundary values for different DR technologies. A match-making module determines multiple DR plans as combinations of one or more replication technologies that can be used to satisfy DR requirements. And, an optimizer configured for assessing a feasible DR plan from said multiple DR plans, to deploy for DR planning of a primary computing environment.

Abstract: When an alarm condition relating to a performance goal of a storage system is detected, a storage management system invokes an N-step lookahead engine for simulating operation of the storage system when there are multiple actions that could be taken by the storage system for eliminating the alarm condition. The N-step lookahead engine generates N possible system states based on a current state of the storage system. The N possible states are based on a cost model of each of the multiple actions. Each cost model is based on an action, a behavior implication of the action, a resource implication of the action and a transient cost of the action. An action is selected that generates a system state that optimizes the stability, a prerequisite and a transient cost of invoking the selected action.

Abstract: A method and structure for managing resources in a storage system that is based on server resource usage is disclosed. The method allocates a command window to each of the servers accessing the resources, achieves an equilibrium state that balances the size of each server's command window and the amount of free resources, and maintains the equilibrium state by continually adjusting the size of each command window. The command window defines a limit on the number of outstanding storage requests that each server may maintain. The invention initially allocates a minimum sized command window.