Salesforce Com, Inc.

Salesforce, Inc.

Oracle International Corporation

Ignacio Agustin Manzano

Agustin Lopez Gabeiras

Andrew Craig Bragdon

Diego Gabriel Larralde

Gaston Alberto Lodieu

Jiang Wu

Paulo Gustavo Veiga

Nicolas Hernan Battiato

Leandro Luck

Antonio Garrote

Fernando Alberto Zavalia Paunero

Pedro Colunga

Guillermo Coscarelli

Leandro Damián Lück

Daniel Fujii

Juan Ignacio Vimberg

Emilio Lopez Gabeiras

Martin Battaglia

Juan Cruz Nores

Guido Agustin Martinez

Luis Contreras

Ariel Morelli Andres

Ignacio Rodriguez

Ezequiel Block

Robert M O'Dell

Anand Nair

Eduardo Cominguez

Christian Vallejos

Peter Gorski

Ignacio Raik

Mariano Mirabelli

Rodrigo Pazos

Vijay Gopalakrishnan

Subhash Periasamy

Berkay Polat

Balasubramanian Narasimhan

Pablo Grosso

Saebom Kwon

Udayakumar Dhansingh

Álvaro David Gaita

Maria Florencia Vimberg

Diego Saint Esteben

Disclosed herein are system, method, and computer program product embodiments for implementing automatic taxonomy tags in an API microgateway. The API microgateway may receive a plurality of API requests for an API managed by a customer in a period of time and route the plurality of API request to an instance of the API according to a policy of the API. The API microgateway may aggregate metrics information related to the plurality of API requests. The aggregated metrics information may include request features, response features, policy features, and performance features. In response to a cluster of the metrics information corresponding to a tag in a tag prediction system, the aggregated metrics information may be labeled with the tag. The tag and the aggregated metrics information may be added to an access log and sent to the customer.

Automatic microgateway taxonomy tags

In the present disclosure, systems and methods are described for allowing a non-code user to create to transform a database in an ETL pipeline. Specifically, as disclosed herein, a user can take a database and receive a ruleset to apply to the database in an ETL pipeline. The data linting system may take the database and extract a schema and a data sample from it. Further, the data linting system may use the schema and data sample to create two rulesets. With these rulesets, the data linting system combines them to create a final ruleset which may be validated using the data sample. The data linting system then sends the final ruleset and the validation report to the user. With this system, the user only needs to give it a database and will receive a ruleset that is able to be immediately used in an ETL pipeline.

Automatic data linting rules for ETL pipelines

Disclosed herein are system, method, and device embodiments for a data bridge adapter in a data integration platform that models any application programming interface as an entity-relationship model. This technique allows an individual using an integration platform to map and transform the entity-relationship model without having to create any custom code. The user may specify target parameters as part of an ETL process, and the entity relationship model may allow appropriate data and API calls to be generated to pass the data to the specified target. By creating an entity-relationship model from any API, the technique further supports versioning, schema change resolution, compatibility detection and other features. Furthermore, data visualization software may use the entity-relationship model to allow users to explore and analyze the data represented in the entity-relationship model.

Data virtualization adapter in an integration platform

Disclosed herein are system, method, and computer program product embodiments for self-paced migration of an application programming language (API) gateway. An embodiment operates by receiving a functional test suite corresponding to an application programming interface (API). The embodiment generates a knowledge graph of information by combining a test result graph of information based on a result of execution of one or more tests in the functional test suite with a metadata linked graph of information based on metadata corresponding to the one or more APIs. The embodiment then generates an alert message corresponding to the function test suite based on the knowledge graph of information.

Impact analysis based on API functional testing

Disclosed herein are system, method, and device embodiments for implementing dynamic codeless logging in an integration platform system. An integration platform may provide a declaratively-configurable asset pre-configured to implement a logging functionality associated with a log point, package the declaratively-configurable asset within an integration application, and receive a selection of the log point associated with the declaratively-configurable asset. In addition, the integration application may generate log information corresponding to the log point based on the selection of the log point and the logging functionality. Further, the integration platform may present the log information within a graphical user interface.

Codeless logging in an integration platform

Disclosed herein are system, method, and computer-readable medium embodiments for providing the ability to automate identification of endpoints of an API for potential health checks based on machine learning and/or similarity search algorithms. The algorithms analyze an API specification according to the algorithm's training and/or search among reference APIs. Rather than having to manually generate health check tests for the web service, a test developer can interact with a test service through a web browser and provide the service an API specification. The test service then can automatically rank identified endpoints according to a ranking system as well as automate health checks by automatically preparing the health check code according to each identified endpoint.

Automated discovery of API endpoints for health check and automated health check generation

Disclosed herein are system, method, and computer program product embodiments for facilitating access to and incorporation of APIs within an application during development, while ensuring that the API satisfies quality constraints. These quality constraints are controlled by the application of rules, which result in a maturity score for the API, in accordance with embodiments. These rules may be provided by a variety of sources for use in scoring the API at various stages. For example, a developer group may control access to developers within the group by applying a ruleset that restricts APIs for applications written by the developer group to a threshold score. This threshold score can limit or restrict APIs that are offered to a developer by an API exchange. Additionally, a ruleset may be applied to enforce a minimum score for submission of an API for inclusion within an API exchange.

Rule-based scoring for APIs

Disclosed herein are system, method, and computer program product embodiments for providing anomaly feedback monitoring and detection. An embodiment operates by determining a first set of data corresponding to an anomaly indicating an undesirable data state for a first application. A subset of data from a second set of data corresponding to the undesirable data state is identified, wherein the second set of data is associated with communications between the first application and a second application. A notification identifying the anomaly is provided. Feedback associated with the anomaly is received. Data corresponding to the anomaly is updated based on the feedback.

Anomaly feedback monitoring and detection system

Disclosed herein are system, method, and device embodiments for implementing log tokenization in an integration platform system. An integration platform may provide a declaratively-configurable logger asset for deployment in an integration-application design tool, and package the declaratively configurable logger asset in an integration application at least partially built via the integration-application design tool. In addition, the integration application may identify sensitive information in original log data of the integration application, and generate modified log data based on tokenization of the sensitive information. Further, the integration application may log the modified log data into a log file.

Log tokenization in an integration platform

Disclosed herein are system, method, and device embodiments for implementing flow analysis in an integration platform system. An integration platform may provide a declaratively-configurable asset within an integration-application design tool, configure the declaratively-configurable asset based on declarative configuration information via the integration-application design tool, and package the declaratively-configurable asset into an integration application. Further, the integration platform may calculate a statistic associated with the declaratively-configurable asset based on the declarative configuration information during an execution of the integration application, and cause display of a graphic representation of the declaratively-configurable asset and the statistic in a monitoring tool.

Flow analysis in an integration platform

A system may include a mocking server and one or more tenants served by the mocking server. A tenant may test an application programming interface (API) using a mocking service. For example, the mocking server may run a mock implementation of an API based on an API specification, and the server may expose an endpoint of the mock implementation for API testing. In some cases, the API specification may use an additional service. The mocking server may need an implementation for this additional service in order to test the API. For improved efficiency and reliability of the mocking service, the mocking server may store pre-configured mock implementations for various service or complementary APIs, which can be publicly accessed and shared across multiple different tenants. The pre-configured mock implementations may enable a user to test an API without providing a mock implementation for each additional service indicated in the API specification.

Default mock implementations at a server

Growing community of inventors

Buenos Aires, Argentina

Ignacio Agustin Manzano