Abstract: A method comprises receiving a list of names of compute resources of an enterprise network, the names of compute resources including at least one name of a virtual machine and at least one name of a host, for each of the list of names: assessing a particular name of the list of names for removable data and removing the removable data to generate a feature for that particular name, for each feature, determining distances based on at least one metric for every other feature, grouping features based on distances, each feature being in only one group, recommending groups of compute resources based on groups of features, each feature of a group of features being associated with a different compute resource, the group of compute resources corresponding to a particular group of features, and providing a report of recommended groups.

Abstract: A method comprising identifying a plurality of compute resources of an enterprise network, the compute resources including ports associated with each compute resource, each port being in communication with entities within and outside the enterprise network, for each identified compute resources, identifying a subset of ports associated with a particular compute resource based on a number of connections and a port number of each port, and the ports of the subset of ports being an N most frequently used ports of a particular compute resource of the plurality of compute resources, determining a port signature associated with the particular compute resource based on the identified subset of ports, and determining one or more applications of the enterprise network being executed by the particular compute resource based on the port signature associated with the particular compute resource and providing a report of the one or more applications of the enterprise network.

Abstract: An example system comprising one or more processors, memory containing instructions control one or more processors to receive network data from enterprise monitoring systems, each object being a digital device, virtual machine, virtual device, or application, analyze the network data to identify performance metric data related to objects of the enterprise system, performance metric data indicating performance of any number of objects in real time, receive a selection of an object identifier of an enterprise system, the object identifier identifying an object of the enterprise network, identify an object subset that includes the object identifier, the object subset including some objects of the enterprise network that are related by communication or performance of similar functions, if performance metrics from the network data for any objects in the object subset are performing outside of nominal thresholds, provide at least some performance metric data of those objects to the user interface.

Abstract: An example method comprises receiving flow packets from network traffic analyzing platforms, for each particular flow packet: identify the particular flow packet as belonging to one of at least two flow packet types based on a format, if the particular flow packet is sFlow, determine if the particular flow packet is an sFlow sample, counter record, or a third packet type, if the particular flow packet is the sFlow sample or counter record, identify a flow source of the particular flow packet and at least one metric, and update a flow source data structure else ignore the particular flow packet, and if the particular flow packet is a second flow packet type: if the particular flow packet is of a format that matches a template, identify the flow source, and update the flow source data structure to include the identified flow source and the at least one metric.

Abstract: A method comprising discovering workload attributes and identify dependencies, receiving utilization performance measurements including memory utilization measurements of at least a subset of workloads, grouping workloads based on the workload attributes, the dependencies, and the utilization performance measurements into affinity groups, determining at least one representative synthetic workload for each affinity group, each representative synthetic workload including a time slice of a predetermined period of time when there are maximum performance values for any number of utilization performance measurements among virtual machines of that particular affinity group, determining at least one cloud service provider (CSP)'s cloud services based on performance of the representative synthetic workloads, and generating a report for at least one of the representative synthetic workloads, the report identifying the at least one of the representative synthetic workloads and the at least one CSP's cloud services inclu

Abstract: A method comprises receiving a list of names of compute resources of an enterprise network, the names of compute resources including at least one name of a virtual machine and at least one name of a host, for each of the list of names: assessing a particular name of the list of names for removable data and removing the removable data to generate a feature for that particular name, for each feature, determining distances based on at least one metric for every other feature, grouping features based on distances, each feature being in only one group, recommending groups of compute resources based on groups of features, each feature of a group of features being associated with a different compute resource, the group of compute resources corresponding to a particular group of features, and providing a report of recommended groups.

Abstract: A method comprises receiving a list of names of compute resources of an enterprise network, the names of compute resources including at least one name of a virtual machine and at least one name of a host, for each of the list of names: assessing a particular name of the list of names for removable data and removing the removable data to generate a feature for that particular name, for each feature, determining distances based on at least one metric for every other feature, grouping features based on distances, each feature being in only one group, recommending groups of compute resources based on groups of features, each feature of a group of features being associated with a different compute resource, the group of compute resources corresponding to a particular group of features, and providing a report of recommended groups.

Abstract: A method comprising discovering workload attributes and identify dependencies, receiving utilization performance measurements including memory utilization measurements of at least a subset of workloads, grouping workloads based on the workload attributes, the dependencies, and the utilization performance measurements into affinity groups, determining at least one representative synthetic workload for each affinity group, each representative synthetic workload including a time slice of a predetermined period of time when there are maximum performance values for any number of utilization performance measurements among virtual machines of that particular affinity group, determining at least one cloud service provider (CSP)'s cloud services based on performance of the representative synthetic workloads, and generating a report for at least one of the representative synthetic workloads, the report identifying the at least one of the representative synthetic workloads and the at least one CSP's cloud services inclu

Abstract: An example method comprises receiving flow packets from network traffic analyzing platforms, for each particular flow packet: identify the particular flow packet as belonging to one of at least two flow packet types based on a format, if the particular flow packet is sFlow, determine if the particular flow packet is an sFlow sample, counter record, or a third packet type, if the particular flow packet is the sFlow sample or counter record, identify a flow source of the particular flow packet and at least one metric, and update a flow source data structure else ignore the particular flow packet, and if the particular flow packet is a second flow packet type: if the particular flow packet is of a format that matches a template, identify the flow source, and update the flow source data structure to include the identified flow source and the at least one metric.

Abstract: A method comprising discovering workload attributes and identify dependencies, receiving utilization performance measurements including memory utilization measurements of at least a subset of workloads, grouping workloads based on the workload attributes, the dependencies, and the utilization performance measurements into affinity groups, determining at least one representative synthetic workload for each affinity group, each representative synthetic workload including a time slice of a predetermined period of time when there are maximum performance values for any number of utilization performance measurements among virtual machines of that particular affinity group, determining at least one cloud service provider (CSP)'s cloud services based on performance of the representative synthetic workloads, and generating a report for at least one of the representative synthetic workloads, the report identifying the at least one of the representative synthetic workloads and the at least one CSP's cloud services inclu

Abstract: A method comprises receiving a list of names of compute resources of an enterprise network, the names of compute resources including at least one name of a virtual machine and at least one name of a host, for each of the list of names: assessing a particular name of the list of names for removable data and removing the removable data to generate a feature for that particular name, for each feature, determining distances based on at least one metric for every other feature, grouping features based on distances, each feature being in only one group, recommending groups of compute resources based on groups of features, each feature of a group of features being associated with a different compute resource, the group of compute resources corresponding to a particular group of features, and providing a report of recommended groups.

Abstract: A method comprising discovering workload attributes and identify dependencies, receiving utilization performance measurements including memory utilization measurements of at least a subset of workloads, grouping workloads based on the workload attributes, the dependencies, and the utilization performance measurements into affinity groups, determining at least one representative synthetic workload for each affinity group, each representative synthetic workload including a time slice of a predetermined period of time when there are maximum performance values for any number of utilization performance measurements among virtual machines of that particular affinity group, determining at least one cloud service provider (CSP)'s cloud services based on performance of the representative synthetic workloads, and generating a report for at least one of the representative synthetic workloads, the report identifying the at least one of the representative synthetic workloads and the at least one CSP's cloud services inclu

Abstract: A method comprising: receiving network traffic data from a network traffic monitoring platform, the network traffic data identifying communication between entities of an enterprise network and storage monitoring data from a server-based SAN monitoring platform, the storage monitoring data identifying communication between a software-only server-based SAN and entities of the enterprise network, parsing the received traffic data and storage monitoring data to identify object data and/or metric data, creating a metric table entry from metric data, creating an object table entry from object data linking metric table entries with object table entries, creating a link table entry from the linking of metric table entries with object table entries, for each link table entry, assigning an object performance threshold, comparing each metric table entries to the assigned object performance threshold, if an alarm trigger condition is satisfied based on the comparison, then triggering an alarm event and outputting an alar

Abstract: A monitoring device responds to status data to detect storms, analysis, and to attempt to remediate those storms. The monitoring device several types of storms, for each of which it has a technique for analysis of the storm. The monitoring device can determine if the storm is due to resource contention, excess or unbalanced performance activity, or network degradation. Once analyzed, the monitoring device analyzes the storm, and attempts to remediate the cause of the storm.

Abstract: A monitoring device responds to status data pushed from a network device, and also manages a link with another network device, the link allowing the monitoring device to pull status data from the second network device. The monitoring device receives packets including status, the data indicating activity for one or more clock ticks. The monitoring device can compute statistical measures, rather than the network device. The monitoring device maintains the status data in a buffer. The monitoring device lags actual activity, but has is more likely to capture delayed packets. The network device sends packets as wrappers, each wrapper indicating sets of status information. When the information in a wrapper crosses a clock tick boundary, the monitoring device allocates reported activity among clock ticks, assuming that activity follows a uniform distribution.

Abstract: A method comprising: receiving object identifiers associated with each entity of an enterprise network, receiving relationship data indicating directionality of data flow between two or more entities of enterprise network, receiving search query which includes at least one of an object identifier associated with one of the entities or relationship data indicating directionality of data flow associated with one of the entities, traversing a portion of topology to identify objects of the portion of the topology and a pivot point, the pivot point being directionally coupled to at least three objects, identifying two mini-topologies based on two of the least three objects of the pivot point, traversing each of the two mini-topologies to identify further objects within the portion of the topology, generating a partial topology based on the traversal of the portion of the topology and of the mini-topologies, and providing information including objects identified in the partial topology.

Abstract: A monitoring device responds to status data pushed from a network device, and also manages a link with another network device, the link allowing the monitoring device to pull status data from the second network device. The monitoring device receives packets including status, the data indicating activity for one or more clock ticks. The monitoring device can compute statistical measures, rather than the network device. The monitoring device maintains the status data in a buffer. The monitoring device lags actual activity, but has is more likely to capture delayed packets. The network device sends packets as wrappers, each wrapper indicating sets of status information. When the information in a wrapper crosses a clock tick boundary, the monitoring device allocates reported activity among clock ticks, assuming that activity follows a uniform distribution.

Abstract: A method comprising discovering workload attributes and identify dependencies, receiving utilization performance measurements including memory utilization measurements of at least a subset of workloads, grouping workloads based on the workload attributes, the dependencies, and the utilization performance measurements into affinity groups, determining at least one representative synthetic workload for each affinity group, each representative synthetic workload including a time slice of a predetermined period of time when there are maximum performance values for any number of utilization performance measurements among virtual machines of that particular affinity group, determining at least one cloud service provider (CSP)'s cloud services based on performance of the representative synthetic workloads, and generating a report for at least one of the representative synthetic workloads, the report identifying the at least one of the representative synthetic workloads and the at least one CSP's cloud services inclu

Abstract: Computing devices, each of which monitors information in a monitoring environment, take on the role of a controller for some of them, separating the (real or virtual) elements of the environment into subsets. Computing devices provide their results to a unification device, which combines them into a monitoring parameter. Each computing device monitors its parameters based on a timestamp, so unification devices can determine whether results from those computing devices represent the same state of the environment. Unification devices divide the results from their computing devices into uniform durations. Even if results don't reflect the same environment state, unification devices can still approximate results for unification. Elements can be reassigned on time boundaries, or can be duplicated, with unification devices still able to unify results. Predicted queries can be pre-computed.

Abstract: A method comprising discovering workload attributes and identify dependencies, receiving utilization performance measurements including memory utilization measurements of at least a subset of workloads, grouping workloads based on the workload attributes, the dependencies, and the utilization performance measurements into affinity groups, determining at least one representative synthetic workload for each affinity group, each representative synthetic workload including a time slice of a predetermined period of time when there are maximum performance values for any number of utilization performance measurements among virtual machines of that particular affinity group, determining at least one cloud service provider (CSP)'s cloud services based on performance of the representative synthetic workloads, and generating a report for at least one of the representative synthetic workloads, the report identifying the at least one of the representative synthetic workloads and the at least one CSP's cloud services inclu