Abstract: Techniques are disclosed relating to determining whether a set of database schemas are different. A computer system may receive a request to create a snapshot for a set of data stored in a database having a first database schema. In response to receiving the request, the computer system may create the snapshot for the set of data. As part of the creating, the computer system may generate, based on the first database schema, a first hierarchy of hash values that includes a first root hash value for the first database schema. The first hierarchy of hash values may be usable to determine whether the first database schema is different from a second database schema. The computer system may include the first hierarchy of hash values with the snapshot.

Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for facilitating the implementation of declarative transaction control. A database transaction control configuration associated with an element of a process flow can be obtained via a graphical user interface (GUI) and stored in association the element. The database transaction control configuration indicates whether a pending database transaction is to be committed to a database prior to executing a set of computer-readable instructions corresponding to the element. During execution of the process flow, the database transaction control configuration is accessed and it is determined whether a currently pending database transaction is to be committed to a database prior to executing a set of computer-readable instructions corresponding to the element.

Abstract: A method by one or more electronic devices to provision an infrastructure for a machine learning application in a multi-tenant on-demand serving infrastructure. The method includes storing a plurality of templates, wherein each of the plurality of templates indicates a scoring interface, a web server, a definition of a continuous integration pipeline, and a definition of a continuous deployment pipeline, receiving a request to provision the infrastructure for the machine learning application using a specified template from the plurality of templates, and provisioning the infrastructure for the machine learning application using the specified template to create a version control system repository, a continuous integration pipeline, and a continuous deployment pipeline.

Abstract: A method by a router component in a multi-tenant on-demand serving infrastructure to route scoring requests to scoring containers. The method includes receiving a scoring request, determining a machine learning application associated with the scoring request, determining whether a router instance for the machine learning application exists, and responsive to a determination that a router instance for the machine learning application does not exist, obtaining a configuration object for the machine learning application and instantiating the router instance for the machine learning application based on the configuration object for the machine learning application. The method further includes invoking the router instance for the machine learning application to route the scoring request associated with the machine learning application to a scoring container that provides scoring functionality for the machine learning application.

Abstract: A method of a base scorer in a scoring service container includes sending a model identifier to a model loader of an application specific scorer in the scoring service container, receiving a model object from the model loader in response to sending the model identifier, sending a request for a scoring from a client application to a scoring function of the application specific scorer, receiving the scoring from the application specific scorer, and returning the scoring to the client application.

Abstract: A method performs service discovery in a machine learning service. The method includes detecting initialization of at least one service container, identifying label information in the at least one service container, collecting the label information for the initializing at least one service container, and storing the label information in a routing information storage to enable routing of requests to the at least one service container.

Abstract: A method by one or more electronic devices for spinning up a scoring container on demand. The method includes receiving, from an orchestrator component via an application programming interface (API), a request to spin up the scoring container, wherein the scoring container is configured to provide scoring functionality, spinning up the scoring container responsive to receiving the request to spin up the scoring container, and providing, to the orchestrator component via the API, a response to the request to spin up the scoring container, wherein the response includes a uniform resource locator (URL) to use to submit scoring requests to the scoring container.

Abstract: A user device (e.g., a computing device, a smart device, a mobile device, a laptop, a tablet, a set-top box, a display device, etc.) may generate and/or display various pages (e.g., web pages, application pages, links and/or linked data, documentation, etc.) of a multipage user interface (e.g., website, application, data/content source, etc.). The user device may enable a user to avoid getting lost in circular navigation by tracking a sequence of navigation to pages of the multipage user interface and generating a breadcrumb path indicative of the sequence of navigation. The user device may generate a graphical representation of the sequence of navigation, represented as a circular path, that may be selectively displayed on a current page of the multipage user interface whenever circular navigation is detected.

Abstract: Techniques are disclosed relating to provisioning fault domain sets (FDS). In some embodiments, a computer server system implements an FDS for disseminating a storage service across a plurality of fault domains. To implement the FDS, in some embodiments, the computer server system access FDS data specifying a desired state of the FDS in which the storage service is disseminated across at least a particular number of fault domains. The computer server system may determine available resources of the plurality of fault domains and determine a current state of the FDS based on fault domains that have already been provisioned to the FDS. Based on at least the desired state of the FDS, the current state of the FDS, and the available resources, the computer server system provisions one or more additional fault domains to the FDS to reconcile the FDS's current state with the FDS's desired state.

Abstract: Embodiments of the present invention include a method of processing time series metrics (TSM) data. The method includes receiving a TSM data point for a metric, the TSM data point indicating an identifier (ID) of the metric, getting a persistence policy associated with the metric, selecting a first resolution database according to the persistence policy, storing the TSM data point in the first resolution database, selecting a second resolution database according to the persistence policy; and when the second resolution database is defined, storing the TSM data point in a staging file for the second resolution database.

Abstract: A system for testing a software procedure is provided. The system is configured to: provide a user interface for configuring a test procedure; inject test data into a program execution flow for a target procedure; initiate test execution of the target procedure; evaluate test results based on data flow within actions of the target procedure to determine the success or failure of the actions during the test execution; and providing a GUI for reviewing the data flow within the actions of the target procedure during the test execution; wherein the GUI provides a test scenario graphical element for each of one or more test scenarios and a view chart graphical element for each test scenario, wherein selection of a view chart graphical element results in the display of a Gantt chart that describes the performance of each action in the target procedure during the test execution.

Abstract: Techniques are disclosed for classifying a user search query for a database system. In disclosed techniques, a computing system receives a user search query for the database system and determines, based on the user search query, a database query that is compatible with an interface of the database system to implement the user search query. In some embodiments, the computing system causes a query remediation interface to be presented to a user that entered the user search query. In some embodiments, the interface includes: a classification of the user search query that specifies attributes of the database query, and one or more elements selectable to alter the database query. The computing system receives, from the user via the query remediation interface, input for altering the database query and determines an updated database query based on the input. The computing system may access the database system using the updated database query.

Abstract: An attentional neural machine translation model is provided for the task of machine translation that, according to some embodiments, leverages the hierarchical structure of language to perform natural language processing without a priori annotation. Other features are also provided.

Abstract: A system to control navigation of graphical user interface (GUI) panels on a web page includes a processor and a storage medium that stores instructions that are configurable to cause the processor to perform a method of navigating the GUI panels. The method controls display of a web page having GUI panels, and receives input associated with a command to change focus away from a first GUI panel. The input is generated in response to selection of an assigned keyboard key, selection of an assigned combination of keyboard keys, or selection of an assigned sequence of keyboard keys by a user. In response to receiving the input, a second GUI panel is identified, and focus is switched from the first GUI panel to the second GUI panel.

Abstract: A machine learning serving infrastructure implementing a method of receiving or detecting an update of container metrics including resource usage and serviced requests per model or per container, processing the container metrics per model or per container to determine recent resource usage and serviced requests per model or per container, and rebalancing distribution of models to a plurality of containers to decrease a detected load imbalance between containers or a stressed container in the plurality of containers.

Abstract: A plurality of permissions associated with the on-demand computing services environment may be identified. Each of the permissions may identify a respective one or more actions permitted to be performed within the on-demand computing services environment. Each of the permissions may be granted to a respective one or more user accounts within the on-demand computing services environment. A degree of overlap between a first group of the user accounts granted a first one of the permissions and a second group of the user accounts granted a second one of the permissions may be determined. When the degree of overlap exceeds a designated threshold, a designated permission set that includes the first permission and the second permission may be created.

Abstract: Systems, methods, and devices facilitate synchronization of content between instances of data records. Servers may be configured to generate a data record comprising a dynamic synchronization data object, receive an input associated with the data record, and determine a plurality of synchronization parameters including a plurality of expansion parameters and a plurality of permission parameters associated with the dynamic synchronization data object. The servers may be configured to determine a plurality of update parameters based on the synchronization parameters, the update parameters identifying if a modification included in the input should be applied to contents of the dynamic synchronization data object. The servers may also be configured to update the data record and the contents of the dynamic synchronization data object based, at least in part, on the determined update parameters, the updating including pushing the updated contents to at least one of the plurality of target data records.

Abstract: Machine learning version management method for a prediction service includes receiving a prediction request, determining application metadata for the request that defines routing logic and a machine learning framework version, determining model metadata for the request that defines at least one model and at least one model version, forwarding the prediction request to the at least one model with the at least one model version, and returning a prediction from the at least one model to a requestor.

Abstract: Systems and methods provide a simple and flexible data access layer for an application. The systems and methods receive, at a data access layer associated with an application, a request for accessing data in memory; identify a pattern of the data of the request; determine whether the data access layer includes a table having a structure of one of key/value pair, sorted set, map, or event that is suitable for accessing the data of the request based on the identified pattern. If the data access layer includes a table with suitable structure, using that table for accessing the data of the request. If the data access layer does not include a table with suitable structure, generating a table having the structure of one of key/value pair, sorted set, map, or event; and using the generated table for accessing the data of the request.