Dell Products Inc.

Dell & Products L.p.

Trevor Scott Conn

Stephen J Todd

Nicole Reineke

Mustafa Al-Bado

Richard A Backhouse

Ahmed Khalid

One method includes obtaining a snapshot of a data confidence fabric billing manifest, broadcasting the snapshot to one or more nodes of the data confidence fabric, deploying, at the nodes, billing logic included in the data confidence fabric billing manifest, and executing the billing logic to obtain information concerning a trust service provided regarding data associated with the nodes. The trust service may include trust annotating the data with an assessment as to the relative trustworthiness of the data.

Smart contract deployment for DCF trust services billing

One example method includes receiving, by a trust provider from a third party proxy, an indication that the third party proxy has instantiated a smart contract on behalf of the trust provider, connecting wallets of a customer to an agent of a data confidence fabric, in response to a request from an application, providing a trust service that includes processing customer data by applying a trust function to the customer data, creating annotations for the customer data based on the trust function, providing the processed customer data to a recipient, calling the smart contract using successive ones of the customer wallets until the smart contract is successfully executed, transferring, from the customer wallet that resulted in successful execution of the smart contract to the third party proxy, a trust provider fee, and transferring the trust provider fee from a third party proxy wallet to a trust provider wallet.

Third-party proxies for crypto-based DCF

Executing functions in serverless platforms leveraging metadata is disclosed. Embodiments of the invention related to using metadata when placing and/or executing functions. The metadata includes request metadata, container or function metadata, node metadata, and/or data metadata. The metadata allows a function to be placed and executed in a manner that accounts for user intent, container requirements, node resources, and data location. Functions can be placed across different serverless platforms. Once the metadata is evaluated and a location is selected, a function is placed and executed at the selected location.

Intelligent function execution leveraging metadata

A method for maintaining a function registry includes: obtaining, by a function-as-a-service (FaaS) function registry manager of a FaaS environment, a user query parameter from a first client, wherein the FaaS environment includes a FaaS function registry; in response to the obtaining: comparing the user query parameter with metadata parameters of the FaaS function registry; identifying at least a first function in the FaaS function registry with metadata parameters that match the user query parameter; and providing a first function image and first function metadata associated with the at least the first function to the first client, wherein the first client performs code-ahead and real-time documentation using the first function image and the first function metadata.

Function registry in function-as-a-service environments

Generating policy-based confidence scores for data is disclosed. Data captured by a data confidence fabric is annotated when the data is created, mutated, transited or otherwise handled in the data confidence fabric. The annotations are weighted by a policy to generate policy-based confidence scores. The policy-based confidence scores are used in determining whether the data is sufficiently trusted for use by an application.

Data confidence fabric policy-based scoring

One example method is performed in connection with a data confidence fabric. This method includes generating information about data as the data transits a data confidence fabric, ingesting the information, mapping the ingested information to a timeline, evaluating the timeline, based on the evaluating, generating a recommendation for an action concerning the data, and implementing the action in the data confidence fabric. In this method, the evaluating includes determining if any unexpected time gaps occurred as the data transited the data confidence fabric.

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Leander, TX, United States of America

Trevor Scott Conn