Patent application number | Description | Published |
20080205300 | CHECKING AND REPAIRING A NETWORK CONFIGURATION - Disclosed is a technique for correcting a configuration problem. The configuration problem is detected. It is determined whether there is at least one solution for the configuration problem in a knowledge data store. When it is determined that there is at least one solution in the knowledge data store, automatically selecting a solution to solve the configuration problem. When said solution can be automatically applied, automatically applying said solution. When said solution cannot be automatically applied, notifying a user. | 08-28-2008 |
20080209015 | CHECKING AND REPAIRING A NETWORK CONFIGURATION - A technique for performing configuration checking of a network is provided. A network data store is scanned for at least one transaction. At least one event is generated for the transaction. At least one configuration policy is associated with the event. The configuration policy is compared with configuration data associated with the event. It is determined whether the configuration policy has been violated based on the comparison. | 08-28-2008 |
20080294672 | SYSTEM AND METHOD FOR DISCLOSING RELATIONS BETWEEN ENTITIES IN SUPPORT OF INFORMATION TECHNOLOGY SYSTEM VISUALIZATION AND MANAGEMENT - A relationship visualization system provides a user interface by which a user may select from among entities, elements, and sub-elements as an initial point in a desired relationship for display. The system designates the selected entities, elements, and sub-elements originating endpoints for the desired relationship. The system displays the relationship between entities, elements, and sub-elements to facilitate visualization and management of the information technology system. The relationship comprises a data path. The display of the relationship comprises a graphical view and a tabular view. | 11-27-2008 |
20090222560 | METHOD AND SYSTEM FOR INTEGRATED DEPLOYMENT PLANNING FOR VIRTUAL APPLIANCES - A method and system for integrated server-storage deployment planning for virtual appliances is provided. One implementation involves determining a performance cost in deploying the virtual appliance to different pairings of candidate host and storage subsystems. A host and storage subsystem pair is preferentially selected among the candidate pairings, a pairing of a host and storage subsystem with certain performance cost to satisfy performance requirements of the virtual appliance. Deployment planning may further involve deploying a virtual appliance on one or more appropriate spatially proximate hosts and storage subsystems that exhibit certain preferable connectivity and path capacity to satisfy the performance requirements of the virtual appliance. | 09-03-2009 |
20090271415 | STORAGE AREA NETWORK MANAGEMENT MODELING SIMULATION - A method, system and computer program product are disclosed for simulating a storage area network including a set of correlated devices, each of the devices having a device agent. The method comprises the step of forming a set of simulation agents representing said device agents, including the steps of, (i) for each of the simulation agents, obtaining a set of agent profiles, and storing said agent profiles in a data store, and (ii) obtaining files describing class definitions for the simulation agents, and storing said files in the data store. With this information and data, a Visual Workbench is used to generate a display of said simulation agents. The preferred embodiment provides a framework and implementation that simulates the CIM agent of any SAN device. Each individual device CIM agent can be simulated in this framework based on the specification defined in an XML file and/or through snapshot mechanism. | 10-29-2009 |
20100211956 | METHOD AND SYSTEM FOR CONTINUOUS OPTIMIZATION OF DATA CENTERS BY COMBINING SERVER AND STORAGE VIRTUALIZATION - The invention provides a method and system for continuous optimization of a data center. The method includes monitoring loads of storage modules, server modules and switch modules in the data center, detecting an overload condition upon a load exceeding a load threshold, combining server and storage virtualization to address storage overloads by planning allocation migration between the storage modules, to address server overloads by planning allocation migration between the server modules, to address switch overloads by planning allocation migration mix between server modules and storage modules for overload reduction, and orchestrating the planned allocation migration to reduce the overload condition in the data center. | 08-19-2010 |
20110022562 | SYSTEM AND METHOD FOR SEMANTIC INFORMATION EXTRACTION FRAMEWORK FOR INTEGRATED SYSTEMS MANAGEMENT - The invention provides an enterprise administration system and method. The system includes a user interface module configured to enter administration terms or select a predetermined script of administration terms, a knowledge base configured to store system information, a meta information module configured to use the system information to store entity-objective indexes, and a workflow mapping module configured to map the administration terms to system information extraction tasks to extract relevant entities and objectives and apply a rule to the extracted entities and objectives for presenting the extracted entities and objectives in a ranked order. | 01-27-2011 |
20110106938 | Multi-Level Offload of Model-Based Adaptive Monitoring for Systems Management - 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. | 05-05-2011 |
20110208622 | DATA CENTER POWER COST ACCOUNTING SYSTEM - 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. | 08-25-2011 |
20110314069 | DATA LIFECYCLE MANAGEMENT WITHIN A CLOUD COMPUTING ENVIRONMENT - Embodiments of the present invention provide lifecycle storage management for data within a Cloud computing environment. Specifically, a set of policies can be defined that allow for automatic valuation of the data and migration of the data between a set of storage tiers. Before a policy set is deployed, it can be assessed to determine effects it will have on cost, performance, and data location. Based on data characteristics and access patterns, a set of policy recommendations can be provided that predict the value of the data over time, and offer an improved migration strategy for moving the data between the set of storage tiers as the value of the data changes. | 12-22-2011 |
20110314164 | INTELLIGENT NETWORK STORAGE PLANNING WITHIN A CLUSTERED COMPUTING ENVIRONMENT - Embodiments of the present invention provide an integrated host and subsystem port selection methodology that uses performance measurements combined with information about active data paths. This technique also helps in resilient fabric planning by selecting ports from redundant fabrics. In a typical embodiment, host port to storage port pairs that create a path between a host and a storage device will be identified. From these pairs, a set of host port to storage port candidates for communicate data from the host to the storage device will be identified based on a set of resiliency constraints. Then, a specific host port to storage port pair will be selected from the set based on a lowest joint workload measurement. A path will then be created between the specific host port and storage port, and data will be communicated from the host to the storage device via the path. | 12-22-2011 |
20120011316 | INTELLIGENT STORAGE PROVISIONING WITHIN A CLUSTERED COMPUTING ENVIRONMENT - Embodiments of the present invention provide an approach for intelligent storage planning and planning within a clustered computing environment (e.g., a cloud computing environment). Specifically, embodiments of the present invention will first determine/identify a set of storage area network volume controllers (SVCs) that is accessible from a host that has submitted a request for access to storage. Thereafter, a set of managed disk (mdisk) groups (i.e., corresponding to the set of SVCs) that are candidates for satisfying the request will be determined. This set of mdisk groups will then be filtered based on available space therein, a set of user/requester preferences, and optionally, a set of performance characteristics. Then, a particular mdisk group will be selected from the set of mdisk groups based on the filtering. | 01-12-2012 |
20120042061 | CALIBRATING CLOUD COMPUTING ENVIRONMENTS - In general, embodiments of present invention provide an approach for calibrating a cloud computing environment. Specifically, embodiments of the present invention provide an empirical approach for obtaining end-to-end performance characteristics for workloads in the cloud computing environment (hereinafter the “environment”). In a typical embodiment, different combinations of cloud server(s) and cloud storage unit(s) are determined. Then, a virtual machine is deployed to one or more of the servers within the cloud computing environment. The virtual machine is used to generate a desired workload on a set of servers within the environment. Thereafter, performance measurements for each of the different combinations under the desired workload will be taken. Among other things, the performance measurements indicate a connection quality between the set of servers and the set of storage units, and are used in calibrating the cloud computing environment to determine future workload placement. Along these lines, the performance measurements can be populated into a table or the like, and a dynamic map of a data center having the set of storage units can be generated. | 02-16-2012 |
20120047265 | PERFORMANCE ISOLATION FOR STORAGE CLOUDS - Embodiments of the present invention provide performance isolation for storage clouds. Under one embodiment, workloads across a storage cloud architecture are grouped into clusters based on administrator or system input. A performance isolation domain is then created for each of the clusters, with each of the performance isolation domains comprising a set of data stores associated with a set of storage subsystems and a set of data paths that connect the set of data stores to a set of clients. Thereafter, performance isolation is provided among a set of layers of the performance isolation domains. Such performance isolation is provided by (among other things): pooling data stores from separate performance isolation domains into separate pools; assigning the pools to device adapters, RAID controller, and the set of storage subsystems; preventing workloads on the device adapters from exceeding capacities of the device adapters; mapping the set of data stores to a set of Input/Output (I/O) servers based on an I/O capacity and I/O load of the set of I/O servers; and/or pairing ports of the set of I/O servers with ports of the set of storage subsystems, the pairing being based upon availability, connectivity, I/O load, and I/O capacity. | 02-23-2012 |
20120079097 | PROACTIVE IDENTIFICATION OF HOTSPOTS IN A CLOUD COMPUTING ENVIRONMENT - The present invention proactively identifies hotspots in a cloud computing environment through cloud resource usage models that use workload parameters as inputs. In some embodiments the cloud resource usage models are based upon performance data from cloud resources and time series based workload trend models. Hotspots may occur and can be detected at any layer of the cloud computing environment, including the server, storage, and network level. In a typical embodiment, parameters for a workload are identified in the cloud computing environment and inputted into a cloud resource usage model. The model is run with the inputted workload parameters to identify potential hotspots, and resources are then provisioned for the workload so as to avoid these hotspots. | 03-29-2012 |
20120110260 | AUTOMATED STORAGE PROVISIONING WITHIN A CLUSTERED COMPUTING ENVIRONMENT - Embodiments of the present invention provide an approach for automatic storage planning and provisioning within a clustered computing environment (e.g., a cloud computing environment). Specifically, embodiments of the present invention will receive planning input for a set of storage area network volume controllers (SVCs) within the clustered computing environment, the planning input indicating a potential load on the SVCs and its associated components. Along these lines, analytical models (e.g., from vendors) can be also used that allow for a load to be accurately estimated on the storage components. Regardless, configuration data for a set of storage components (i.e., the set of SVCs, a set of managed disk (Mdisk) groups associated with the set of SVCs, and a set of backend storage systems) will also be collected. Based on this configuration data, the set of storage components will be filtered to identify candidate storage components capable of addressing the potential load. Then, performance data for the candidate storage components will be analyzed to identify an SVC and an Mdisk group to address the potential load. This allows for storage provisioning planning to be automated in a highly accurate fashion. | 05-03-2012 |
20120116743 | OPTIMIZING STORAGE CLOUD ENVIRONMENTS THROUGH ADAPTIVE STATISTICAL MODELING - Embodiments of the present invention provide an approach for adapting an information extraction middleware for a clustered computing environment (e.g., a cloud environment) by creating and managing a set of statistical models generated from performance statistics of operating devices within the clustered computing environment. This approach takes into account the required accuracy in modeling, including computation cost of modeling, to pick the best modeling solution at a given point in time. When higher accuracy is desired (e.g., nearing workload saturation), the approach adapts to use an appropriate modeling algorithm. Adapting statistical models to the data characteristics ensures optimal accuracy with minimal computation time and resources for modeling. This approach provides intelligent selective refinement of models using accuracy-based and operating probability-based triggers to optimize the clustered computing environment, i.e., maximize accuracy and minimize computation time. | 05-10-2012 |
20120203742 | REMOTE DATA PROTECTION IN A NETWORKED STORAGE COMPUTING ENVIRONMENT - Embodiments of the present invention provide an approach for protecting and restoring data within a networked (e.g. cloud) storage computing environment through asynchronous replication and remote backup of data and its associated metadata. Under embodiments of the present invention, data backup and recovery functionality provides data backups by detecting incremental updates to the data and its associated metadata at specific points in time determined by policies. The policies are configurable based on user requirements. Multiple copies of the data backups can be made and stored in separate compressed files at backup/disaster recovery locations. The backups of data and its associated metadata, which includes file system configuration information can be used to restore the state of a computer file system to that of a given point-in-time. Accordingly, a data protection approach is disclosed for protecting data at both the file system level and application level. | 08-09-2012 |
20120233310 | COMPREHENSIVE BOTTLENECK DETECTION IN A MULTI-TIER ENTERPRISE STORAGE SYSTEM - Embodiments of the present invention provide approaches (e.g., online methods) to analyze end-to-end performance issues in a multi-tier enterprise storage system (ESS), such as a storage cloud, where data may be distributed across multiple storage components. Specifically, performance and configuration data from different storage components (e.g., nodes) is collected and analyzed to identify nodes that are becoming (or may become) performance bottlenecks. In a typical embodiment, a set of components distributed among a set of tiers of an ESS is identified. For each component, a total capacity and a current load are determined. Based on these values, a utilization of each component is determined. Comparison of the utilization with a predetermined threshold and/or analysis of historical data allows one or more components causing a bottleneck to be identified. | 09-13-2012 |
20120254640 | ALLOCATION OF STORAGE RESOURCES IN A NETWORKED COMPUTING ENVIRONMENT BASED ON ENERGY UTILIZATION - Embodiments of the present invention provide an approach to provision storage resources (e.g., across an enterprise storage system (ESS) such as a general parallel file system (GPFS) or the like) for different workloads in an energy efficient manner. The system evaluates different energy profiles/workloads' energy consumption characteristics of storage devices to determine an allocation plan that reduces the energy cost (e.g., results in the lowest cost/energy consumption for handling a storage workload). In a typical embodiment, energy consumption characteristics for handling a particular storage workload will be determined. Thereafter, a type of storage device capable of handling the workload will be determined. Then, an allocation plan that results in the most efficient energy consumption for handling the workload will be developed. In general, the allocation plan is based upon the energy consumption characteristics and an energy efficiency algorithm. The energy efficiency algorithm serves to identify storage device(s) that can handle the workload in such a way as to reduce total energy consumption and, accordingly, costs. Along these lines, the energy efficiency algorithm may also consider other factors such as capacity and load of storage devices and service level agreement (SLA) terms in addition to energy costs (e.g., over times of day and/or days of week). In any event, at least one storage device can then be selected for handling the storage workload according to the allocation plan. | 10-04-2012 |
20130219033 | END-TO-END PROVISIONING OF STORAGE CLOUDS - Embodiments discussed in this disclosure provide an integrated provisioning framework that automates the process of provisioning storage resources, end-to-end, for an enterprise storage cloud environment. Such embodiments configure and orchestrate the deployment of a user's workload and, at the same time, provide optimization across a multitude of storage cloud resources. Along these lines, input is received in the form of workload requirements and configuration information for available system resources. Based on the input, a set (at least one) of storage cloud configuration plans is developed that satisfy the workload requirements. A set of scripts is then generated that orchestrate the deployment and configuration of different software and hardware components based on the plans. | 08-22-2013 |
20130282910 | INTELLIGENT STORAGE PROVISIONING WITHIN A CLUSTERED COMPUTING ENVIRONMENT - Embodiments of the present invention provide an approach for intelligent storage planning and planning within a clustered computing environment (e.g., a cloud computing environment). Specifically, embodiments of the present invention will first determine/identify a set of storage area network volume controllers (SVCs) that is accessible from a host that has submitted a request for access to storage. Thereafter, a set of managed disk (mdisk) groups (i.e., corresponding to the set of SVCs) that are candidates for satisfying the request will be determined. This set of mdisk groups will then be filtered based on available space therein, a set of user/requester preferences, and optionally, a set of performance characteristics. Then, a particular mdisk group will be selected from the set of mdisk groups based on the filtering. | 10-24-2013 |
20140129717 | ALLOCATION OF STORAGE RESOURCES IN A NETWORKED COMPUTING ENVIRONMENT BASED ON ENERGY UTILIZATION - The present invention provides an approach to provision storage resources (e.g., across an enterprise storage system) for different workloads in an energy efficient manner. Typically, energy consumption characteristics for handling a particular storage workload will be determined. Thereafter, a type of storage device capable of handling the workload will be determined. Then, an allocation plan that results in the most efficient energy consumption for handling the workload will be developed. The allocation plan is based upon the energy consumption characteristics and an energy efficiency algorithm. The energy efficiency algorithm serves to identify storage device(s) that can handle the workload in such a way as to reduce total energy consumption and, accordingly, costs. The energy efficiency algorithm may also consider other factors such as capacity and load of storage devices and service level agreement (SLA) terms. At least one storage device can then be selected for handling the storage workload. | 05-08-2014 |
20140149791 | REMOTE DATA PROTECTION IN A NETWORKED STORAGE COMPUTING ENVIRONMENT - Embodiments of the present invention provide an approach for protecting and restoring data within a networked (e.g. cloud) storage computing environment through asynchronous replication and remote backup of data and its associated metadata. Under embodiments of the present invention, data backup and recovery functionality provides data backups by detecting incremental updates to the data and its associated metadata at specific points in time determined by policies. The policies are configurable based on user requirements. Multiple copies of the data backups can be made and stored in separate compressed files at backup/disaster recovery locations. The backups of data and its associated metadata, which includes file system configuration information can be used to restore the state of a computer file system to that of a given point-in-time. Accordingly, a data protection approach is disclosed for protecting data at both the file system level and application level. | 05-29-2014 |
20140156926 | AUTOMATED STORAGE PROVISIONING WITHIN A CLUSTERED COMPUTING ENVIRONMENT - The present invention provides an approach for automatic storage planning and provisioning within a clustered computing environment (e.g., a cloud computing environment). The present invention will receive planning input for a set of storage area network volume controllers (SVCs), the planning input indicating a potential load on the SVCs and its associated components. Configuration data for a set of storage components (i.e., the set of SVCs, a set of managed disk (Mdisk) groups associated with the set of SVCs, and a set of backend storage systems) will also be collected. Based on this configuration data, the set of storage components will be filtered to identify candidate storage components capable of addressing the potential load. Then, performance data for the candidate storage components will be analyzed to identify an SVC and an Mdisk group to address the potential load. | 06-05-2014 |
20140173015 | PERFORMANCE ISOLATION FOR STORAGE CLOUDS - Embodiments of the present invention provide performance isolation for storage clouds. Under one embodiment, workloads across a storage cloud architecture are grouped into clusters based on administrator or system input. A performance isolation domain is then created for each of the clusters, with each of the performance isolation domains comprising a set of data stores associated with a set of storage subsystems and a set of data paths that connect the set of data stores to a set of clients. Thereafter, performance isolation is provided among a set of layers of the performance isolation domains. | 06-19-2014 |
20140330961 | COMPREHENSIVE BOTTLENECK DETECTION IN A MULTI-TIER ENTERPRISE STORAGE SYSTEM - Embodiments of the present invention provide approaches (e.g., online methods) to analyze end-to-end performance issues in a multi-tier enterprise storage system (ESS), such as a storage cloud, where data may be distributed across multiple storage components. Specifically, performance and configuration data from different storage components (e.g., nodes) is collected and analyzed to identify nodes that are becoming (or may become) performance bottlenecks. In a typical embodiment, a set of components distributed among a set of tiers of an ESS is identified. For each component, a total capacity and a current load are determined. Based on these values, a utilization of each component is determined. Comparison of the utilization with a predetermined threshold and/or analysis of historical data allows one or more components causing a bottleneck to be identified. | 11-06-2014 |