Abstract: Systems and methods for increasing high availability of data in a multi-node storage network are provided. Aspects may include allocating data and mirrored data associated with nodes in the storage network to storage units associated with the nodes. Upon identifying additional nodes added to the storage network, data and mirrored data associated with the nodes may be dynamically reallocated to the storage units. Systems and methods for high availability takeover in a high availability multi-node storage network are also provided. Aspects may include detecting a fault associated with a node in the storage network, and initiating a takeover routine in response to detecting the fault. The takeover routine may be implemented to reallocate data and mirrored data associated with the nodes in the storage network among the operable nodes and associated storage units.

Abstract: Example embodiments provide various techniques for modeling network storage environments. To model a particular storage environment, component models that are associated with the components of the storage environment are loaded. Each component model is programmed to mathematically simulate one or more components of the storage environment. A system model is then composed from the component models and this system model is configured to simulate the storage environment.

Abstract: One or more techniques and/or systems are provided for configuring a storage environment. In particular, the storage environment may be configured with a symmetric frontend and an asymmetric backend. That is, an owner storage controller may be granted read/write access to a storage device owned by the owner storage controller, while a non-owner storage controller may be granted merely read access. In this way, the owner storage controller may execute, log, and/or commit a write command to the storage device, while the non-owner storage controller may merely execute, but not log and/or commit, a write command. Write buffers, log memories, and/or file system metadata may be synchronized between the owner storage controller and the non-owner storage controller, such that the non-owner storage controller may efficiently take ownership of the storage device in response to a failure of the owner storage controller.

Abstract: A network server analyzes a change in the network, including performing a machine-learning analysis of an extrapolation space. The server accesses observed data from multiple counters that each record samples for a metric in the network. The server performs a CART (classification and regression tree) analysis of the observed data to select the counters whose metrics affect a target network performance, such as latency. The server estimates an extrapolation space based on the observed data for the selected counters. The server then performs a machine-learning analysis of the extrapolation space based on a kriging model of the selected counters.

Abstract: Example embodiments provide various techniques for modeling network storage environments. To model a particular storage environment, component models that are associated with the components of the storage environment are loaded. Each component model is programmed to mathematically simulate one or more components of the storage environment. A system model is then composed from the component models and this system model is configured to simulate the storage environment.

Abstract: A method and apparatus for detecting an intermittent path to a storage system comprising accessing path statistics comprising indicia of path state of a path to a storage system, determining whether the path state has changed during a predefined period and, if the path state has changed at least a predefined number of times during the predefined period, identifying the path as intermittent. Once a path is deemed intermittent, the path is aged until either the path is no longer intermittent or the path is deemed dead.

Abstract: Systems and procedures may be used to coordinate the fail-back of multiple hosts in environments where the hosts share one or more data-storage resources. In one implementation, a procedure for coordinating fail-backs includes monitoring a failed data path to detect a restoration of the data path, polling remaining nodes in response to the restoration, and allowing the first node to resume communications if access has been restored to the remaining nodes.

Abstract: A method and apparatus for providing dynamic multi-pathing for an asymmetrical logical unit access (ALUA) based storage system. The method comprises identifying a first processor within a storage system as providing an optimized path to a disk array, identifying a second processor within a storage system as providing an unoptimized path to the disk array and, in response to failure of the optimized path, immediately switching from the optimized path to the unoptimized path.

Abstract: Systems and procedures may be used to coordinate the fail-back of multiple hosts in environments where the hosts share one or more data-storage resources. In one implementation, a procedure for coordinating fail-backs includes monitoring a failed data path to detect a restoration of the data path, polling remaining nodes in response to the restoration, and allowing the first node to resume communications if access has been restored to the remaining nodes.

Abstract: Example embodiments provide various techniques for modeling a storage environment at various times. A computer model can be composed to simulate a storage environment at various time periods. In an example, the computer model may simulate the storage environment in the past. As the storage environment is running, it continuously stores its existing state. This existing state can be accessed and a simulated workload may be applied to this previous state to identify an impact of the simulated workload on the existing state. A computer model may also simulate the storage environment in the future. Here, the future state of the storage environment may be projected from the existing state. Various extrapolation techniques may be used to project the future state of the storage environment.

Abstract: Systems, methods, apparatus and software can implement a SAN monitoring scheme for determining changes in SAN topology, such as device failure and state changes. These changes are recorded in a SAN topology data structure. Information in the SAN topology data structure is used, for example, to identify a suspect path or set of paths, and to make decisions about communications pathways used by a multipath device driver.

Abstract: A method, computer program product and system that enables dynamic determination of device attributes and dynamic configuration of device drivers for storage devices in a heterogeneous storage environment. Attributes of a device are dynamically determined by an application program, and those attributes are used by the application program to configure the device driver. The application program and the storage device being configured remain operational during the reconfiguration process.

Abstract: Systems, methods, apparatus and software can implement a multipathing driver using dynamically loadable device policy modules that provide device specific functionality for providing at least one of input/output (I/O) operation scheduling, path selection, and I/O operation error analysis. Because the device policy modules include device specific functionality, various different devices from different manufacturers can be more efficiently and robustly supported.

Abstract: A method for controlling data traffic within a storage area network can be provided. The method can comprise analyzing data for a path in a storage area network to determine whether the path should be identified as a less preferred path, and controlling data traffic routing to avoid use of a path identified as a less preferred path. In some embodiments, the data can be obtained from a host bus adaptor in the path. In some embodiments, the controlling can comprise throttling traffic over a path identified as a less preferred path.

Abstract: Example embodiments provide various techniques for modeling network storage environments. To model a particular storage environment, component models that are associated with the components of the storage environment are loaded. Each component model is programmed to mathematically simulate one or more components of the storage environment. A system model is then composed from the component models and this system model is configured to simulate the storage environment.

Abstract: Example embodiments provide various techniques for modeling a storage environment at various times. A computer model can be composed to simulate a storage environment at various time periods. In an example, the computer model may simulate the storage environment in the past. As the storage environment is running, it continuously stores its existing state. This existing state can be accessed and a simulated workload may be applied to this previous state to identify an impact of the simulated workload on the existing state. A computer model may also simulate the storage environment in the future. Here, the future state of the storage environment may be projected from the existing state. Various extrapolation techniques may be used to project the future state of the storage environment.

Abstract: Systems, methods, apparatus and software can make use of persistent reservation commands to establish the port of a shared device that is to be used as an active port by one or more host computer systems coupled to the shared device. Information about one or more paths used to transmit data between a host computer system and the shared device can be used by other host computer systems.

Abstract: Systems, methods, apparatus and software can implement a multipathing driver using dynamically loadable device policy modules that provide device specific functionality for providing at least one of input/output (I/O) operation scheduling, path selection, and I/O operation error analysis. Because the device policy modules include device specific functionality, various different devices from different manufacturers can be more efficiently and robustly supported.