An apparatus for delivering alternate user input between an alternate input device and an output device, the output device configured to receive input from a conventional input device, the output device not configured to receive input from the alternate input device, the apparatus including an input interconversion processor that receives the alternate user input from the alternate input device, a processing pipeline that converts the alternate user input to a conventional user input of a type normally received by the output device from the conventional input device, and an output port that transmits the conventional user input.

Concepts and technologies are disclosed herein for using deep learning models to obfuscate and optimize communications. A request can be received in a first language, from a user device, and at a first computing device storing a first neural network. The request can be translated using the first neural network into a modified request in a custom language. The modified request can be sent to a second computing device hosting an application. The first computing device can receive a modified response that is in the custom language, where the modified response can be created at the second computing device using the second neural network and based on a response from the application. The modified response can be translated into a response in the first language and sent to the user device.

A node for a VSAN includes a BMC, a processor, and a plurality of VSAN objects. The processor instantiates a Cluster Membership, Monitoring, and Directory Service (CMMDS) and a BMC Service Module (SM). The CMMDS implements a Security Policy and Data Model (SPDM) architecture. The CMMDS determines an inventory list of the VSAN objects and a SPDM authentication state for each of the objects, and provides the inventory list and the SPDM authentication states to the BMC SM. The BMC SM provides the inventory list and the SPDM authentication state to the BMC. The BMC determines that a first VSAN object is not authenticated based upon the SPDM authentication state of the first VSAN object, and directs the CMMDS to halt input/output (I/O) operations on the VSAN to the first VSAN object.

Technologies include an interface processor configured to be communicatively coupled to a memory and a first processor. The interface processor is to obtain, from a first module compiled from a first software language, first data having a first native type of the first software language. The interface processor is further to convert the first data into second data having a first interface type, convert the second data having the first interface type into third data having a second native type of a second software language, and provide the third data to a second module associated with the second software language. The first software language may be compiled to WebAssembly binary code. The second software language may also be compiled to WebAssembly binary code and may be different than the first software language.

Techniques for implementing a dynamic API bot for robotic process automation are disclosed. In some embodiments, a computer system performs operations comprising: providing a data file having a predefined template comprising dedicated fields for an identification of an API, a type of call method, metadata identifying one or more objects, and data of the object(s); providing a low-code no-code (LCNC) development platform configured to enable a user to develop a bot by dragging and dropping application components of the bot; receiving, via the LCNC development platform, a configuration of the bot comprising a configuration of the application components of the bot and an identification of the data file; and running the bot, the bot being configured to generate a request using the data file, converting the data of the object(s) into a payload in a format required by the API based on the data file.

Diffusing a root identity of an entity among association and event covenants in a multi-dimensional computing security system involves generating a first generation of diffusion of identities of entities participating in mediated association and generating a second generation of diffusion of identities of the entities through recombinant mediated association of the entities and at least one other entity. The second generation of diffusion of identities facilitates securely constraining a computing system action associated with one of the entities.

Techniques described herein relate to a method for managing applications. The method may include obtaining, by a binding manager associated with a first CSP, a first API call from a first application; the binding manager identifies a first CSP API associated with the first CSP; identifies a second CSP API associated with the first API call; make a first determination that the second CSP API does not match the first CSP API; and in response to the first determination: translates the first API call into a format associated with the first CSP API to obtain a translated API call; initiates performance of the translated API call; obtains a first CSP API call return object in first CSP API format; translates the first CSP API call return object to obtain a translated CSP API call return object; and provides the translated CSP API call return object to the first application.

One embodiment of the present invention sets forth a technique for executing one or more services in a technology stack. The technique includes deploying a first set of containers within an environment, wherein each container included in the first set of containers includes a first service that implements a first interface and a first shim that implements a second interface. The technique also includes transmitting a first request associated with the second interface to a first container included in the first set of containers, wherein the first request is processed by an instance of the first shim and an instance of the first service executing within the first container.

This application provides a parameter configuration method, including: receiving a configuration parameter of a service system and a service objective of the service system through a standard interface, performing parameter optimization on the configuration parameter to obtain a recommended parameter value that meets the service objective, and then outputting the recommended parameter value, to implement parameter configuration for the service system. The method abstracts parameter configuration problems in different service scenarios into a mathematical problem of inputting and expression through a standard interface. In this way, a universal parameter configuration method is provided, without case-by-case parameter configuration. In addition, an expert in the service field can independently complete parameter configuration without artificial intelligence experience, thereby improving configuration efficiency and reducing configuration costs.

The disclosure relates to processing application programming interface (API) requests. Embodiments include receiving, at an API wrapper, from a first caller, a first call to an API and sending the first call to the API. Embodiments include receiving, by the API wrapper, from one or more second callers, a second one or more calls to the API prior to receiving a response from the API to the first call. Embodiments include receiving, by the API wrapper, the response from the API to the first call and responding to the first call from the first caller with the response from the API to the first call. Embodiments include responding, by the API wrapper, to the second one or more calls from the one or more second callers with the response from the API to the first call without sending the second one or more calls to the API.