Abstract: There are disclosed devices, system and methods for mapping relationships between macro-clusters of a network object topology of a computer communication network. A remote network object of the network is selected that has a relationship with one macro-cluster that has a relationship with another macro-cluster. Flow log data, metric data and configuration data are gathered from at least the selected network object. Configuration data and time data are generated for the sets network objects of the two macro-clusters using the gathered flow log data, metric data and configuration data. Network topology information is created using the configuration data and time data. The network topology information includes topology information for the relationship between the macro-clusters, for each macro-cluster and for the sets of network objects of the macro-clusters. The topology information can be stored and used to determine whether performance issues occur in the macro-clusters or relationship over time.

Abstract: There are disclosed devices, system and methods for continual automated discovering of a topology of a computer network of physical network objects for an application. A first physical network object selects portions of sets of data messages being sent over time by the application and related network objects; and collects network configuration and time dimension information, and timeseries information from the portions of messages. A second physical network object receives the information and uses it to determine topology information for the application over time, which includes unique keys of, types of objects of, types of relationships between pairs of, groupings of, time dimension data of and metrics data of the physical network objects. The topology information can be stored; and can be queried to create and display a graph representation of the topology information that changes over time.

Abstract: There are disclosed devices, system and methods for mapping relationships between macro-clusters of a network object topology of a computer communication network. A remote network object of the network is selected that has a relationship with one macro-cluster that has a relationship with another macro-cluster. Flow log data, metric data and configuration data are gathered from at least the selected network object. Configuration data and time data are generated for the sets network objects of the two macro-clusters using the gathered flow log data, metric data and configuration data. Network topology information is created using the configuration data and time data. The network topology information includes topology information for the relationship between the macro-clusters, for each macro-cluster and for the sets of network objects of the macro-clusters. The topology information can be stored and used to determine whether performance issues occur in the macro-clusters or relationship over time.

Abstract: There are disclosed devices, system and methods for mapping relationships between macro-clusters of a network object topology of a computer communication network. A remote network object of the network is selected that has a relationship with one macro-cluster that has a relationship with another macro-cluster. Flow log data, metric data and configuration data are gathered from at least the selected network object. Configuration data and time data are generated for the sets network objects of the two macro-clusters using the gathered flow log data, metric data and configuration data. Network topology information is created using the configuration data and time data. The network topology information includes topology information for the relationship between the macro-clusters, for each macro-cluster and for the sets of network objects of the macro-clusters. The topology information can be stored and used to determine whether performance issues occur in the macro-clusters or relationship over time.

Abstract: There are disclosed devices, system and methods for creating and displaying a graph representation of a topology of a computer network of physical network objects for an application. A first physical network object selects portions of sets of data messages being sent over a period of time by the application and related network objects; and collects network configuration and time dimension information from the portions of messages. A second physical network object receives the information and uses it to determine topology information for the application over time, which includes unique keys of, types of objects of, types of relationships between pairs of, groupings of, metrics data of, and time dimension data for the physical network objects. The topology information is stored and queried at the second object to create and display various graph representations of the topology information as it changes over time.

Abstract: There are disclosed devices, system and methods for continual automated discovering of a topology of a computer network of network objects for an application. A first network object selects portions of sets of data messages being sent over time by the application and related network objects; and collects network configuration and time dimension information, and timeseries information from the portions of messages. A second network object receives the information and uses it to determine topology information for the application over time, which includes unique keys of, types of objects of, types of relationships between pairs of, groupings of, time dimension data of and metrics data of the network objects. The topology information can be stored; and can be queried to create and display a graph representation of the topology information that changes over time.

Abstract: A system and method for monitoring hosts and storage devices in a storage system includes a memory containing machine readable medium comprising machine executable code having stored thereon instructions for performing a method of managing application performance and a processor coupled to the memory. The processor is configured to execute the machine executable code to detect a first datasource for a storage device, determine one or more first storage identifiers associated with the storage device, record the first storage identifiers, detect a second datasource for a compute resource, determine a file system used by the compute resource, determine a second storage identifier associated with the file system, and in response to determining that the second storage identifier matches one of the first storage identifiers, record a first association between the file system and the compute resource and record a second association between the file system and the storage device.

Abstract: A method performed by a monitoring tool in a computer system, the method including: displaying a user interface including information regarding a first resource; running a correlation algorithm to determine whether other resources in the computer system show correlation for one or more performance metrics; selecting one or more other resources as suggestions based on results of the correlation algorithm; displaying selected resources in a list with the base resource and render a graph of performance metrics over time with performance data of the base resource and the suggested resources overlaid; and overlaying further performance data on the graph for a resource searched for, and selected by, the human user.

Abstract: A method of displaying health information of a system asset in a computer system, the method including: accessing a data log associated with the system asset, wherein the data log includes a store of the health information of the system asset, identifying a plurality of state entries in the store of the health information, each of the state entries including a timestamp and a state of the system asset at the respective time stamp, generating a timeline based on the state entries, the timeline having a plurality of chronological portions defined by the timestamps, wherein each portion of the timeline is assigned a visual cue based on a state associated with its respective state entries, and visually rendering the timeline upon a computer display.

Abstract: A system and method for monitoring hosts and storage devices in a storage system includes a memory containing machine readable medium comprising machine executable code having stored thereon instructions for performing a method of managing application performance and a processor coupled to the memory. The processor is configured to execute the machine executable code to detect a first datasource for a storage device, determine one or more first storage identifiers associated with the storage device, record the first storage identifiers, detect a second datasource for a compute resource, determine a file system used by the compute resource, determine a second storage identifier associated with the file system, and in response to determining that the second storage identifier matches one of the first storage identifiers, record a first association between the file system and the compute resource and record a second association between the file system and the storage device.

Abstract: Examples are disclosed for searching data associated with devices in a heterogeneous data center. In some examples, data may be gathered for a database. The data may be associated with a heterogeneous data center having devices from multiple vendors. The database may be indexed to link data for a given device to an attribute, association or usage context for the given device. Responsive to a search request, data for a given device from among the devices in the heterogeneous data center may be provided based on a comparison of the search request to the indexed database. Other examples are described and claimed.

Abstract: A virtualized storage system comprises at least one host, at least one virtual array, a backend array and a management server. The host requests storage operations to the virtual array, and the virtual array executes storage operations for the host. The backend array, coupled to the virtual array, comprises physical storage for the virtual array. The management server determines the efficiency for the virtual array. The management server determines an input throughput data rate between the host and the virtual array based on storage operations between host and virtual array. The management server also determines an output throughput data rate, from the virtual array to the backend array. The output throughput data rate is based on the storage operations that require access to the backend array. The management server determines the efficiency of the virtual array using the input throughput data rate and the output throughput data rate.

Abstract: Described herein is a system and method for detecting underutilized capacity within a storage system environment. The technique comprises collecting performance data of various storage objects within a storage system environment for various performance measures at designated time intervals. The collected performance data may be formatted and stored to a database. One or more parameters may be received specifying at least one performance measure, at least one threshold value, and/or at least one time period. The performance data for target storage objects may be analyzed according to the received parameters to determine any underutilized storage objects. A report may be generated according to the parameters listing the storage objects and address locations of any underutilized storage objects. The report may comprise various information corresponding to the underutilized storage object, such as the business units, tiers, data centers, and levels of service they are associated with.

Abstract: A method of retrieving hierarchical information, the method including receiving a request on an interface of a server, the request identifying a base node and an expansion node, the base node and the expansion node being hierarchically-arranged data objects in a data memory in communication with the server, parsing the request to determine the base node in the hierarchical information, parsing the request to determine the expansion node in the hierarchical information, retrieving a base record associated with the base node, retrieving an expansion record associated with the expansion node and referenced by the base record, inserting information from the base record and information from the expansion record into a response, and returning the response to a client computer in response to the request.

Abstract: A method of displaying health information of a system asset in a computer system, the method including: accessing a data log associated with the system asset, wherein the data log includes a store of the health information of the system asset, identifying a plurality of state entries in the store of the health information, each of the state entries including a timestamp and a state of the system asset at the respective time stamp, generating a timeline based on the state entries, the timeline having a plurality of chronological portions defined by the timestamps, wherein each portion of the timeline is assigned a visual cue based on a state associated with its respective state entries, and visually rendering the timeline upon a computer display.

Abstract: A method performed by a monitoring tool in a computer system, the method including: displaying a user interface including information regarding a first resource; running a correlation algorithm to determine whether other resources in the computer system show correlation for one or more performance metrics; selecting one or more other resources as suggestions based on results of the correlation algorithm; displaying selected resources in a list with the base resource and render a graph of performance metrics over time with performance data of the base resource and the suggested resources overlaid; and overlaying further performance data on the graph for a resource searched for, and selected by, the human user.

Abstract: Described herein is a system and method for detecting underutilized capacity within a storage system environment. The technique comprises collecting performance data of various storage objects within a storage system environment for various performance measures at designated time intervals. The collected performance data may be formatted and stored to a database. One or more parameters may be received specifying at least one performance measure, at least one threshold value, and/or at least one time period. The performance data for target storage objects may be analyzed according to the received parameters to determine any underutilized storage objects. A report may be generated according to the parameters listing the storage objects and address locations of any underutilized storage objects. The report may comprise various information corresponding to the underutilized storage object, such as the business units, tiers, data centers, and levels of service they are associated with.

Abstract: Examples are disclosed for searching data associated with devices in a heterogeneous data center. In some examples, data may be gathered for a database. The data may be associated with a heterogeneous data center having devices from multiple vendors. The database may be indexed to link data for a given device to an attribute, association or usage context for the given device. Responsive to a search request, data for a given device from among the devices in the heterogeneous data center may be provided based on a comparison of the search request to the indexed database. Other examples are described and claimed.

Abstract: Machine implemented method and system is provided for managing resources within an operating environment having a plurality of computing systems and a plurality of virtual machines. The resources are monitored and resource utilization is compared to configured threshold values for managing over utilization. If resource utilization reaches the threshold value, then the resource is identified as being over utilized. One or more data structures are used to display and verify the over utilization on a display device. The root cause of the over utilization is identified and then corrective action may be taken to reduce the over utilization.

Abstract: A virtualized storage system comprises at least one host, at least one virtual array, a backend array and a management server. The host requests storage operations to the virtual array, and the virtual array executes storage operations for the host. The backend array, coupled to the virtual array, comprises physical storage for the virtual array. The management server determines the efficiency for the virtual array. The management server determines an input throughput data rate between the host and the virtual array based on storage operations between host and virtual array. The management server also determines an output throughput data rate, from the virtual array to the backend array. The output throughput data rate is based on the storage operations that require access to the backend array. The management server determines the efficiency of the virtual array using the input throughput data rate and the output throughput data rate.