Abstract: Some embodiments provide a method for evaluating locations of applications in a multi-cloud network with applications located in different cloud datacenters of one or more cloud providers. The method receives data for flows collected from the cloud datacenters. The data for each flow indicates a source and destination of the flow and applications to which at least one of the source and destination of the flow belong. The method uses network topology data to identify a subset of the flows as egress flows, each of which is charged by a cloud provider at which the flow source is located. Based on data from the cloud providers, the method determines a cost for each of the egress flows and a cost associated with each of the applications. The method provides these costs to users of the network for the users to optimize locations of the applications in the different cloud datacenters.

Abstract: An application reconciliation to improve flow-based applications. Generating a first application source graph based on first discovery information. Generating a second application graph based on first discovery information. Clustering the applications generated in the second graph of connected components. Performing a reconciliation of the connected components to cluster applications with similar members to obtain a reduced output of clustered applications.

Abstract: A property-based application discovery. Generating a first application member properties graph based on first discovery information. Generating a second application member properties graph based on second discovery information. Creating a distance matrix based upon the first application member properties graph and the second application member properties graph. Performing a dimension reduction operation on the distanced matrix to obtain a reduced similarity matrix. Performing a property based application discovery operation using the reduced similarity matrix to obtain a reduced output of clustered applications.

Abstract: Automated provision and assignment of meaningful business names for auto discovered Applications and Tiers is disclosed. Properties of members of a virtual computing environment are automatically determined. Performing a tokenization process on text corresponding to the members to obtain information from the text. Utilizing a document generation operation to obtain tokens from the text. Performing a text mining operation on the text to obtain Term Frequency (TF) data, Document Frequency (DF) information, an Inverse Document Frequency (IDF), and TF-IDF data, and utilizing the TF-IDF data to automatically generate and assign a name to the Application/Tiers of said virtual computing environment.