In one example, an application monitoring server may include a metric parser to receive performance metrics associated with an endpoint. Example performance metrics may be in a source format. Further, the metric parser may parse the received performance metrics. Furthermore, the application monitoring server may include a resource extractor to apply a transformation definition to the parsed performance metrics to determine a plurality of resources in a destination format. Example plurality of resources may be associated with an application being executed in the endpoint. Further, the resource extractor may present information associated with the plurality of resources on a graphical user interface.

In one example, an application monitoring server may include a metric parser to receive performance metrics associated with an endpoint. Example performance metrics may be in a source format. Further, the metric parser may parse the received performance metrics. Furthermore, the application monitoring server may include a resource extractor to apply a transformation definition to the parsed performance metrics to determine a plurality of resources in a destination format. Example plurality of resources may be associated with an application being executed in the endpoint. Further, the resource extractor may present information associated with the plurality of resources on a graphical user interface.

In one example, an application monitoring server may include a metric parser to receive performance metrics associated with an endpoint. Example performance metrics may be in a source format. Further, the metric parser may parse the received performance metrics. Furthermore, the application monitoring server may include a resource extractor to apply a transformation definition to the parsed performance metrics to determine a plurality of resources in a destination format. Example plurality of resources may be associated with an application being executed in the endpoint. Further, the resource extractor may present information associated with the plurality of resources on a graphical user interface.

In one example, an application monitoring server may include a metric parser to receive performance metrics associated with an endpoint. Example performance metrics may be in a source format. Further, the metric parser may parse the received performance metrics. Furthermore, the application monitoring server may include a resource extractor to apply a transformation definition to the parsed performance metrics to determine a plurality of resources in a destination format. Example plurality of resources may be associated with an application being executed in the endpoint. Further, the resource extractor may present information associated with the plurality of resources on a graphical user interface.

A method for sharing content is provided. An image of content is obtained. An address is generated based on the image using a set of predefined rules. The address is associated with the content. The content is provided to a computing device in response to the computing device accessing the address.

A system and method for a non-transient computer readable medium containing program instructions for causing a computer to perform a method for compressing data comprising the steps of receiving a data string for compression, the data string including a plurality of data elements, creating a template based on processing the data string, the template including common information across all data elements of the data string, creating one or more entries, wherein the one or more entries include information that is different to the template, and storing the template and the one or more entries.

A system and method for a non-transient computer readable medium containing program instructions for causing a computer to perform a method for compressing data comprising the steps of receiving a data string for compression, the data string including a plurality of data elements, creating a template based on processing the data string, the template including common information across all data elements of the data string, creating one or more entries, wherein the one or more entries include information that is different to the template, and storing the template and the one or more entries.

A first file and a second file are retrieved from a database, in which the first and second files include an unstructured text stream. Metadata of the first and second files are extracted. The extracted metadata include a description category, entity source, geographic region, and a set of sub-files linked to the file. A data structure indicative of relationship between the first and second files is generated. Weighting factor is applied to the generated data structure, which indicates a degree of relationship between the first file and the second file. The relationship and the degree of the relationship are determined based on the extracted metadata of the first and second files. In response to a user requesting the first file, it is determined whether the second file should be provided in conjunction with the first file based on the weighting factor as applied to the data structure.

A first file and a second file are retrieved from a database, in which the first and second files include an unstructured text stream. Metadata of the first and second files are extracted. The extracted metadata include a description category, entity source, geographic region, and a set of sub-files linked to the file. A data structure indicative of relationship between the first and second files is generated. Weighting factor is applied to the generated data structure, which indicates a degree of relationship between the first file and the second file. The relationship and the degree of the relationship are determined based on the extracted metadata of the first and second files. In response to a user requesting the first file, it is determined whether the second file should be provided in conjunction with the first file based on the weighting factor as applied to the data structure.

Data is organized in a hierarchical data tree having nodes, and is formatted in human-readable data according to a schema. The data is canonically ordered in correspondence with a canonical ordering of a schema dictionary generated from the schema. The canonically ordered data is encoded into binary, including for each node, removing a label of the node, and adding a sequence number of the node corresponding to the canonical ordering, in binary.