Abstract: Some embodiments provide a novel method of providing user interactivity for a first image of a network. The method presents, in a display area of a graphical user interface (GUI), the first image of the network. The first image includes several component images corresponding to several network elements in the network. In some embodiments, none of the component images are GUI elements that are selectable in the GUI. The method detects a cursor action at a first location in the first image. The method identifies a particular component image by correlating the first location to a location of the particular component image in the first image. Then, the method performs a GUI action for a particular network element that corresponds to the particular component image.

Abstract: Some embodiments provide a novel graphical user interface (GUI) for displaying a visual representation of machines in a set of one or more datacenters. The GUI includes a display area, and a graph that includes several clusters and different sets of connection links between different pairs of clusters. Each cluster represents a set of one or more machines in the datacenters. Each set of connection links between a pair of clusters (1) represents data message flows exchanged between machines in the pair of clusters, and (2) includes at least two different subsets of connection links that are displayed using different appearances corresponding to different categories of data message flows and indicating quantity of data message flows.

Abstract: Some embodiments provide a method for providing a visualization of data flows for a logical network spanning a group of datacenters. The method receives a selection of a particular datacenter in the group of datacenters for which to display a flow visualization. The method generates a flow visualization for the particular datacenter including (i) representations of data flows between pairs of logical network compute nodes located within the particular datacenter, (ii) representations of data flows between logical network compute nodes located within the particular datacenter and logical network compute nodes at other datacenters in the group of datacenters, and (iii) representations of data flows between logical network compute nodes located within the particular datacenter and endpoints external to the group of datacenters. The method displays the generated flow visualization within a graphical user interface (GUI).

Abstract: Systems and methods are described for providing a graphical user interface (“GUI”) for graph-based visualizations of network flows using entity clustering. In an example, an application service can periodically execute a job for assigning network entities to clusters according to a clustering type. The job can also include creating metadata about each cluster. The application service can store the assignments in a cache. A user can select to display a visualization of the network in the GUI based on the clustering type. The application service can detect any entities without cluster assignments and create a best guess assignment for them. The GUI can then display a visualization of the network according to the selected clustering type.

Abstract: Some embodiments provide a novel method for receiving a plurality of attribute sets from a set of host computers, each attribute set associated with a group of one or more flows that is created by using a key to associate individual flows into the group of flows. The appliance, in some embodiments, merges two identified attribute sets into one merged attribute set and analyzes the merged attribute set to identify a set of properties of the flows in the groups of flows associated with the two attribute sets. In some embodiments, a visualization process includes identifying machines as members of groups and identifying machines that are connected. The visualization process, in some embodiments, also generates a graphical user interface that can be used to select groups of machines, domains, or individual machines and displays contextual attributes relevant to the selected group, domain, or machine.

Abstract: An example method of analyzing workloads executing in a network managed virtualized computing system includes: presenting, by a network analyzer, a first view of the workloads on a canvas to a first user; receiving, at the network analyzer, first user input to create a first label, the first label initially disassociated with security policies of a network manager managing a software defined network used by the workloads; receiving, at the network analyzer, second user input to assign the first label to at least one of the workloads; and presenting, by the network analyzer, a second view of the workloads on the canvas to the first user having a first group of the at least one workload and a second group having workloads other than the at least one workload.

Abstract: Some embodiments provide a novel method for receiving a plurality of attribute sets from a set of host computers, each attribute set associated with a group of one or more flows that is created by using a key to associate individual flows into the group of flows. The appliance, in some embodiments, merges two identified attribute sets into one merged attribute set and analyzes the merged attribute set to identify a set of properties of the flows in the groups of flows associated with the two attribute sets. In some embodiments, a visualization process includes identifying machines as members of groups and identifying machines that are connected. The visualization process, in some embodiments, also generates a graphical user interface that can be used to select groups of machines, domains, or individual machines and displays contextual attributes relevant to the selected group, domain, or machine.

Abstract: Some embodiments provide a novel method for receiving a plurality of attribute sets from a set of host computers, each attribute set associated with a group of one or more flows that is created by using a key to associate individual flows into the group of flows. The appliance, in some embodiments, merges two identified attribute sets into one merged attribute set and analyzes the merged attribute set to identify a set of properties of the flows in the groups of flows associated with the two attribute sets. In some embodiments, a visualization process includes identifying machines as members of groups and identifying machines that are connected. The visualization process, in some embodiments, also generates a graphical user interface that can be used to select groups of machines, domains, or individual machines and displays contextual attributes relevant to the selected group, domain, or machine.

Abstract: Lubricating grease compositions have a titanium complex grease component along with a mineral/synthetic oil-based component and a conventional soap or grease. The conventional soaps and greases may be lithium complex, calcium sulfonate, or aluminum complex-based, among others, with and without additives. The compositions are high performance geases, exhibiting improved drop point, extreme pressure, antiwear, oil separation, and shelf life properties.