Abstract: Techniques are disclosed for implementing cross-zone communication for computing zones executing different coding protocols. A server computer system may receive, via a proxy layer of a first instance of an application executing within a first computing zone according to a first set of coding protocols, a request for a service executed via a second instance of the application in a second computing zone according to a second, different set of coding protocols. The system may alter, via a remote layer of the first instance, a set of data specified in the request to comply with the second, set of protocols. The system may transmit, via the remote layer of the first instance to a remote layer of the second instance, the altered set of data. The system may advantageously provide a simplified development interface allowing for both development and testing within a local environment without deployment of multiple different services.

Abstract: A method for operating a graph database, including receiving, by a computer system, a query to a particular graph database, the query identifying a plurality of vertices of the particular graph database. The method further includes performing, by the computer system, hash operations on two or more of the plurality of vertices to generate respective hash values and dividing, using the respective hash values, the query into a plurality of sub-queries, each corresponding to a subset of the plurality of vertices. The method also includes sending, by the computer system, ones of the plurality of sub-queries to a plurality of database repositories for the particular graph database.

Abstract: An image compression method includes: obtaining a target image and a target code rate corresponding to the target image; determining a first code rate parameter corresponding to the target code rate; and inputting the target image and the first code rate parameter into an image compression model, that has been trained, for processing to obtain a compressed image with the target code rate, wherein the image compression model is obtained by training an initial image compression model based on multiple code rate parameters including the first code rate parameter.