Abstract: Technologies are provided for supporting tenant customizations in a cloud computing platform. A standard application programming interface (API) can be defined to support a generic set of parameters that allow tenant-specified custom data to be passed to and from the standard API. The generic set of parameters allow the standard API to process requests and responses that include a payload that comprises tenant-specified custom data. The payload allows the tenant-specified custom data to be passed to and from the standard API. When a request is received at the cloud computing platform, a request payload of the request, that includes tenant-specified custom data, can be processed at the standard API, and a response can be sent from the cloud computing platform that includes a response payload that includes the tenant-specified custom data.

Abstract: A system stores logs representing events that occur in the system based on executable instructions executed by the system, for example, by processes executing within the system or by applications. The system analyzes the logs to determine the root cause of the error or event that resulted in generation of the log. The system clusters logs to determine clusters of logs. The system analyzes logs of each cluster to determine a root cause of errors resulting in logs belonging to the cluster. For any new error log that is received, the system determines the cluster to which the error log belongs and takes action based on the root cause associated with the cluster, for example, sending an alert message or performing automatic remediation.

Abstract: Systems, methods, and computer-readable media for asynchronous (async) querying are described. In embodiments, a system may convert a user-issued query into a distributed execution instruction set (DEIS), and issue the DEIS to data stores that may have various database structures. The system may obtain database objects from the data stores, and store a result set indicating the obtained database objects in a location specified by the user-issued query. The system may also provide mechanisms to allow users to view progress of their async query jobs and/or cancel ongoing async query jobs. Other embodiments may be described and/or claimed.

Abstract: Systems and methods are described for migrating a workflow from a source system to a target system. The systems and methods receive metadata defining a workflow configured for processing by the source system. A set of rules associated with transforming the metadata for processing by the target system are identified. A first rule is applied to the metadata to execute a first transformation of an element of the metadata. A second rule is applied to the metadata to execute a second transformation of a position of an element of the metadata. The systems and methods generate a transformed workflow including the first transformation and the second transformation. The transformed workflow is displayed via the target system.

Abstract: A system may automatically generate a predictive machine learning model by automatically performing various processes based on an analysis of the data as well as metadata associated with the data. The system may accept a selection of data and a prediction field from the data. The system may automatically generate a set of features based on the data and may automatically remove certain features that cause inaccuracies in the model. The system may balance the data based on a representation rate of certain outcomes. The system may train and select a model based on several candidate models. The system may then perform the predictions based on the selected model and send an indication of the predictions to a user.

Abstract: Systems, devices, and techniques are disclosed for translation of tenant identifiers. A record may be received. A value of a tenant identifier for the record may be determined from a key for the record or a scan descriptor. The value of the tenant identifier in the key for the record may be replaced with a new value for the tenant identifier. A bitmap stored in a record header of the record may be used to identify columns of the record that stored an encoded value of the tenant identifier. An encoded new value of the tenant identifier may be stored in columns identified by the bitmap stored in the record header that include an attribute indicating that tenant identifier translation is enabled.

Abstract: Computer programming code may be executed via look ahead execution in a virtual machine. The computer programming code may include a first instruction to retrieve data stored in an on-demand computing services environment and a second instruction to transmit the data to a recipient. The first instruction, the second instruction, and the data may be evaluated to determine whether the execution of the computer programming code constitutes acceptable use of the on-demand computing services environment. When it is determined that the execution of the computer programming code does not constitute acceptable use of the on-demand computing services environment, further execution of the computer programming code may be halted.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for security verification of communications to tenants of an on-demand database service. These mechanisms and methods for security verification of communications to tenants of an on-demand database service can enable embodiments to allow tenants to selectively implement security measures with respect to inbound communications, etc. The ability of embodiments to provide such feature may allow tenants to efficiently and effectively implement security measures for in-bound emails.

Abstract: A method of early warning and risk assessment of incidents in a multi-tenant cloud environment is provided. The method includes: capturing a plurality of data metrics; automatically generating derived features from the plurality of captured data metrics; automatically selecting risk assessment features from the derived features and the captured data metrics; and predicting the risk of an incident in the multi-tenant cloud environment within a specified time window in the future and one or more possible root causes of the incident by applying the newly selected risk assessment features to a trained risk assessment model. The trained risk assessment model has been trained using machine learning techniques to predict the risk of an incident in the multi-tenant cloud environment within a specified time window in the future, provide an explanation of possible root causes of the incident, and assign a strength level to each possible root cause.

Abstract: A data-driven approach to network performance diagnosis and root-cause analysis is presented. By collecting and aggregating data attribute values across multiple components of a content delivery system and comparing against baselines for points of inspection, network performance diagnosis and root-cause analysis may be prioritized based on impact on content delivery. Recommended courses of action may be determined and provided based on the tracked network performance analysis at diagnosis points.

Abstract: Systems and methods are provided for receiving at least a first query color, and searching an electronic catalog including a plurality of product images for the first query color to determine a similarity measure between the first query color and a product image of a plurality of product images. The similarity measure may be determined by determining a Euclidean distance between values in a three-dimensional color space for the first query color and a target color of the product image, and determining the similarity measure between the query color and the product image by determining a sum of the similarity measures from all target colors on the product image, weighted by the coverage of each target color. The search results may be transmitted based on the searching of the electronic catalog including the plurality of product images for the first query color.

Abstract: Disclosed herein are system, method and computer readable storage medium for detecting space suitable for overlaying media content onto an image. The system receives an image which may be an image or a video frame. The image is processed using a number of image processing techniques in order to automatically propose spaces for inserting media content onto the image. The proposed spaces may then be further analyzed using a heuristics-based approach to select bounding boxes for inserting media content. Subsequently, one or more media content items may be selected for insertion onto the bounding boxes on the image. The system may then cause a display of the image with the selected media content item overlaid onto the image within the selected bounding boxes.

Abstract: Systems and methods for unifying question answering and text classification via span extraction include a preprocessor for preparing a source text and an auxiliary text based on a task type of a natural language processing task, an encoder for receiving the source text and the auxiliary text from the preprocessor and generating an encoded representation of a combination of the source text and the auxiliary text, and a span-extractive decoder for receiving the encoded representation and identifying a span of text within the source text that is a result of the NLP task. The task type is one of entailment, classification, or regression. In some embodiments, the source text includes one or more of text received as input when the task type is entailment, a list of classifications when the task type is entailment or classification, or a list of similarity options when the task type is regression.

Abstract: Methods, systems, and devices for processing private data using a workflow action are described. A method may include identifying, at a user device that is authenticated to access a local system, an action of a workflow that is running on an external server that is external to the local system. The action may involve processing private data stored within the local system. The method may further include receiving, at the user device, a direct data query associated with the action, the direct data query including a set of encoded instructions that are self-extracting upon being executed by a browser of the user device. The method may further include executing, by the browser of the user device, the set of encoded instructions to directly access the private data and transmitting an indication of a result of the action based on directly accessing the private data.

Abstract: Methods, and apparatuses are provided for access limitations to a network in a session using a formatted web token. The method includes: formatting a web token by a schema to create a formatted web token for user access to the network; receiving a log-in request for the user access to the network server via an app hosted by a computing device remotely located to the network server; in response to receipt of a user access request, creating the session by the network server with network limitations for user access to data and resources of the network; passing the formatted web token to a client for enabling user access to the data and resources of the network; decoding payload data of the formatted web token at the client to authenticate the user access; and enabling the client with access limitations based on decoded payload data.

Abstract: Methods and systems are provided for automatically determining a need to invoke functionality of a feature of an application while using a primary application and for automatically invoking that functionality without user action. When input information is input into the primary application via a user interface of a user system, it can be received by an application server from a sender process at the user system, and a pre-fix that occurs before a text string can be identified. The text string that follows the pre-fix can be extracted by performing a matching analysis against a library of keywords and extracting a matching keyword. The text string comprises extracted text from the input information. The matching keyword can be matched to an entry that is mapped to a command that can be executed to generate an action that automatically invokes the functionality of the feature of the application without user action.

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing a data model application programming interface (“API”) to customizable live applications in a cloud collaboration platform. The cloud collaboration platform provides data storage, a data model, and an API to embedded third-party live applications to allow the live applications to securely create, store, and access data within the cloud collaboration platform. The data model allows records stored in the cloud collaboration platform to sync independently, merge intelligently, and function offline.

Abstract: Described herein are systems, apparatus, methods and computer program products configured for componentized dashboards for data visualization. In certain embodiments, a component may be configured to be integrated within a dashboard. The component may receive data from one or more user database and provide one or more representations of the data. The component may be integrated within the dashboard as a separate component. That is, the component may provide the plurality of representations independent of the dashboard. The component may be maintained independent of the dashboard and, thus, may be updated independent of the dashboard.

Abstract: A method for managing a user's email subscriptions has been developed. The method provides a user interface (UI) to the user that allows the user to view and select multiple stand-alone components across multiple dashboard displays for an email subscription to an email address. The user's selections are received via the UI. A display of each of the subscribed stand-alone components is rendered periodically based on the user's preference. The rendered displays are combined into a single email message that is sent to the email address upon completion of the rendering of the displays.

Abstract: Verification of discriminative models includes receiving an input; receiving a prediction from a discriminative model for the input; encoding, using an encoder, a latent variable based on the input; decoding, using a decoder, a reconstructed input based on the prediction and the latent variable; and determining, using an anomaly detection module, whether the prediction is reliable based on the input, the reconstructed input, and the latent variable. The encoder and the decoder are jointly trained to maximize an evidence lower bound of the encoder and the decoder. In some embodiments, the encoder and the decoder are further trained using a disentanglement constraint between the prediction and the latent variable. In some embodiments, the encoder and the decoder are further trained without using inputs that are out of a distribution of inputs used to train the discriminative model or that are adversarial to the discriminative model.

Abstract: In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing a scheduler with preemptive termination of existing workloads to free resources for high priority items.

Abstract: A method and system uses a test cloud system for monitoring cloud to cloud performance. The method includes initiating a first trust relationship by the test cloud system with a first target cloud system, receiving a success indicator for the trust relationship, in response to the first target cloud verifying the test cloud system is whitelisted, generating a security token using a private key of the test cloud system, and invoking a function of an application programming interface of the first target cloud using the security token to validate functionality of the function of the application programming interface of the first target cloud.

Abstract: Databases that reside on a private network behind a firewall may be difficult to access from a cloud platform on the Internet. Techniques disclosed herein allow an Internet system to communicate with multiple different databases behind multiple different firewalls, however. A client-side private computer system, from behind a firewall, transmits a series of database request status inquires to a server system (not behind the firewall). These status inquiries may be sent as HTTP long poll messages. When the server wishes to query a database on the private network, it responds to one of the database request status inquiries. Because the client-side computer initiated communication, the server response is allowed to pass through the firewall when it might otherwise be blocked. Employing such techniques in parallel allows a server to interact with multiple firewalled databases without the difficulties and inconvenience of attempting a VPN connection.

Abstract: Snippets of content associated with a communication platform are described. In an example, based at least in part on a determination, by the communication platform, that a user of the communication platform is permitted to access one or more snippets of content provided by one or more other users of the communication platform, causing one or more user interface elements associated with the one or more snippets of content to be presented via a user interface of a user computing device of the user. The communication platform can receive, from the user computing device, a request to view a snippet of content of the one or more snippets of content and can cause the snippet of content to be presented by the user computing device via the user interface associated with the communication platform.

Abstract: A system performs conversations with users using chatbots customized for performing a set of tasks. The system may be a multi-tenant system that allows customization of the chatbots for each tenant. The system receives a task configuration that maps tasks to entity types and an entity configuration that specifies methods for determining entities of a particular entity type. The system receives a user utterance and determines the intent of the user using an intent detection model, for example, a neural network. The intent represents a task that the user is requesting. The system determines one or more entities corresponding to the task. The system performs tasks based on the determined intent and the entities and performs conversations with users based on the tasks.

Abstract: Content-sensitive computer applications are run on computer hosts in a computer cluster. A computer application running history including but not limited to computer host scores is recorded for the computer cluster. A request to start a container for a content-sensitive computer application type in the computer cluster is received. In response, available computer hosts in the computer cluster are identified. A specific computer host is selected from among the available computer hosts to run the container for the content-sensitive computer application type.

Abstract: Embedding functionality of a communication platform into a third-party application is described. The communication platform can receive, from the third-party application, a request to connect to the communication platform, wherein the third-party application and the communication platform are associated with a user account. In response to receiving the request, causing an embedded user interface associated with the communication platform to be presented via a user interface of the third-party application. In an example, data input in the embedded user interface can be presented via a group-based communication user interface of the communication platform.

Abstract: Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products that enable performing dynamic user integration in a group-based communication system.

Abstract: Techniques are disclosed relating to caching techniques for processing a database change stream. A computer system may receive change records from a change stream that includes a plurality of records indicating changes to a database table. The change stream may include change records for multiple shards and be accessible by providing one or more position indicators for one or more of the multiple shards to request one or more change records and an updated position indicator. The system may store, for changes to a set of one or more shards, one or more cache entries that include respective groups of change records. The system may request a portion of the change stream by providing a received position indicator. The system may provide one or more cached change records from a cache entry that matches the provided position indicator.

Abstract: Disclosed herein are systems, methods, and devices that configure components of applications. A computing platform implemented using a server system may be configurable to cause determining an initial configuration of an application component that is configured to enable interactions with a user. The initial configuration is determined based on configuration parameters stored in the computing platform. The computing platform may also cause including a first instance of the application component in a webpage, the first instance being generated based on the initial configuration. The computing platform may also cause receiving a function call from the webpage, the function call being generated based on a user interaction with the webpage. The computing platform may also cause implementing a new instance of the application component responsive to the function call, the new instance comprising at least one change implemented based, at least in part, on the function call.

Abstract: Provided is a computing device of a group based communication system configured to securely validate a client device associated with a group-based communication interface user. An example computing device is configured to identify a validating request transmitted from the client device. If a validating request is identified, the example computing device will transmit a temporary device code to the client device associated with the group-based communication interface user and an e-mail code to an e-mail address associated with a user profile associated with the group-based communication interface user. The example computing device also stores the codes transmitted. The example computing device then receives a confirmation exchange from the client device and determines whether the confirmation exchange satisfies client device validation parameters.

Abstract: An online system stores objects representing potential transactions of an enterprise. The online system uses predictor models to determine an aggregate score based on values of the objects associated with a time interval, for example, a month. Each object is configured to take one of a plurality of states. The online system stores historical data describing activities associated with potential transaction objects and uses the stored data for generating the predictor models. The online system categorizes the objects into bins based on states of the objects. The online system may generate different predictions for each category. The online system may use machine learning based models as predictor models. The online system extracts features describing potential transaction objects and provides these as input to the predictor model.

Abstract: An online system performs predictions for real-time tasks and near real-time tasks that need to be performed by a deadline. A client device receives a real-time machine learning based model associated with a measure of accuracy. If the client device determines that a task can be performed using predictions having less than the specified measure of accuracy, the client device uses the real-time machine learning based model. If the client device determines that a higher level of accuracy of results is required, the client device sends a request to an online system. The online system provides a prediction along with a string representing a rationale for the prediction.

Abstract: Database systems and methods are provided for data migration between source and target computing systems using a configurable transformation service. The configurable transformation service obtains transformation configuration metadata associated with the particular combination of source and target computing systems, obtains a subset of source data in accordance with the transformation configuration metadata and transforms the subset of source data from a format associated with the source computing system to an intermediate, platform-independent format. The service transforms the subset of source data from the intermediate format to a destination format associated with the target computing system in accordance with the transformation configuration metadata and maintains the transformed subset of source data in the destination format in association with the target computing system.

Abstract: Described herein are systems, apparatus, methods and computer program products configured for image detection/recognition of products. The disclosed systems and techniques utilize video data to provide the necessary number of images and view angles needed to train a machine learning product detection/recognition system to recognize a specific product within later provided images. In various embodiments, a user may provide video data and the video data may be transformed in a manner that may aid in training of the machine learning system.

Abstract: A method for providing interoperability between a plurality of security services and target applications by an interoperability service. The method includes receiving a request from one of the plurality of security services to perform a task on a target application, preparing a unified data model for interaction with the target application, determining and organizing data connections to perform the task on the target application, generating a set of requests using the unified data model based on the task and utilizing business logic of the interoperability service for the data connections with the target application, transforming the set of requests into commands and data structures specific to the target application, and sending the set of requests on respective data connections with the target application.

Abstract: Methods, systems, and devices for analyzing communication messages (e.g., emails or activities) to determine relationship strength using a distributed graph are described. In some systems, a user may be associated with a specific tenant. A database server of the system may receive communication messages associated with the user and a target user. The server may perform a natural language processing (NLP) analysis on the communication messages to extract metadata, and may generate or update a distributed graph indicating connections between users based on the extracted metadata. Using the connections of the graph, the server may calculate a closeness score between the user and the target user. Additionally, the server may calculate closeness scores between the target and other users associated with the tenant, and may determine the users with the greatest closeness scores. The server may send a suggestion for the determined users to initiate communication with the target.

Abstract: Embodiments for training a neural network using sequential tasks are provided. A plurality of sequential tasks are received. For each task in the plurality of tasks a copy of the neural network that includes a plurality of layers is generated. From the copy of the neural network a task specific neural network is generated by performing an architectural search on the plurality of layers in the copy of the neural network. The architectural search identifies a plurality of candidate choices in the layers of the task specific neural network. Parameters in the task specific neural network that correspond to the plurality of candidate choices and that maximize architectural weights at each layer are identified. The parameters are retrained and merged with the neural network. The neural network trained on the plurality of sequential tasks is a trained neural network.

Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for implementing a software development tool that enables a set of computer-readable instructions to be requested and obtained in association with an element of a process flow represented in a layout. A set of specifications can be submitted in association with a request, where the set of specifications includes input-output value pairs. In response, the system can automatically generate a first set of computer-readable instructions according to the set of specifications, where the first set of computer-readable instructions implements a mapping between the input-output value pairs. In addition, the system can obtain a second set of computer-readable instructions according to the set of specifications, either from pre-existing software code or from individual(s) (e.g., software developer(s)) to whom the system has sent a request for computer-readable instructions.

Abstract: A method is provided for processing a query. In some embodiments, the method includes creating a historical schema defining an ordered set of fields based on a current schema of an object and a field modification of the current schema. The method includes inserting, based on the field modification, a new field at an end of the historical schema and archiving records into a second storage device. The method includes receiving a query, which includes a command specifying a subset of fields and which indicates a non-current field. The method includes searching in the second storage device for archive records having a second schema including the subset of fields and the non-current field. The first and second schemas follow the field order in accordance with the historical schema. The method further includes accessing the subset of fields and the non-current field in accordance with the command.

Abstract: Embodiments described herein provide systems and methods for an Explicit Memory Tracker (EMT) that tracks each rule sentence to perform decision making and to generate follow-up clarifying questions. Specifically, the EMT first segments the regulation text into several rule sentences and allocates the segmented rule sentences into memory modules, and then feeds information regarding the user scenario and dialogue history into the EMT sequentially to update each memory module separately. At each dialogue turn, the EMT makes a decision among based on current memory status of the memory modules whether further clarification is needed to come up with an answer to a user question. The EMT determines that further clarification is needed by identifying an underspecified rule sentence span by modulating token-level span distributions with sentence-level selection scores. The EMT extracts the underspecified rule sentence span and rephrases the underspecified rule sentence span to generate a follow-up question.

Abstract: Disclosed are some implementations of systems, apparatus, methods, and computer program products for facilitating web site navigation using a search-based navigation interface of a web-based application or browser service. A plurality of sources can be searched to identify a set of items based, at least in part, on user input received via a search input interface element of the search-based navigation interface. Each item of the set of items can correspond to an object of one of a plurality of object types. A user interface object including user-selectable options can be provided for display in proximity to the search input interface element, where each item of the set of items corresponds to a different one of the user-selectable options. In response to a user selection of one of the user-selectable options corresponding to an item of the set of items, access to the corresponding object can be provided.

Abstract: Systems and methods are described for applying a plurality of data points of a time series data set representing values of a metric measuring performance of a cloud computing service to a machine learning model to predict a forecast of a most likely value of the metric at a selected future time. The method includes determining whether the plurality of data points of the time series data set are anomalies according to the machine learning model and the forecast and generating a collective anomaly from the anomalies when the plurality of data points is determined to be anomalies. The method further includes determining whether the collective anomaly does not meet one or more cloud computing service level objective (SLO) threshold requirements and sending an alert when the collective anomaly does not meet one or more cloud computing SLO threshold requirements.

Abstract: Systems and methods are provided for near-zero-cost (NZC) query framework or approach for differentially private deep learning. To protect the privacy of training data during learning, the near-zero-cost query framework transfers knowledge from an ensemble of teacher models trained on partitions of the data to a student model. Privacy guarantees may be understood intuitively and expressed rigorously in terms of differential privacy. Other features are also provided.

Abstract: Methods and systems are provided for generating an interactive simulation representing one or more assets based on one or more asset records. Based on information from asset records stored at a database system of a cloud-based computing system, an asset simulator module, executed at a cloud-based computing system, can generate one or more simulated representations of the assets. A simulator application executed at the cloud-based computing system can augment the simulated representations of the assets with (at least) additional information from the asset records stored in the database system, and generate a user interface that presents an interactive simulation of the assets. The user interface can include the simulated representations of the assets with the additional information from the asset records stored in the database system.

Abstract: A self-healing build pipeline architecture for a software application build job across a distributed computer platform comprises a public API that receives configuration data describing the build job, stores the configuration data in a decentralized database, serves requests to/from a pipeline tracker API, and stores states of build pipelines during the build job. The decentralized database stores the configuration data and a project identifier for the build, and metadata regarding states of the build pipelines collected across the distributed computer platform. The pipeline tracker API runs local to the build environment in the distributed computer platform and sends a build status to public API for updating the decentralized database. For any failures in any of the build pipelines, the state is retrieved from the decentralize database and a new build pipeline is triggered locally that resumes from the failed state to provide a self-healing build pipeline architecture.

Abstract: System and methods are described for automated recovery from errors occurring during replication of a database. The method includes getting text from one or more log files generated during database replication processing in a cloud computing environment, transforming the text into a structured language form represented by vectors, and identifying patterns in the vectors. The method further includes classifying one or more errors based on the identified patterns using supervised learning as either a recoverable error or an unrecoverable error, analyzing the one or more errors to determine one or more recovery jobs associated with database replication processing in the cloud computing environment for each of the recoverable errors, and invoking the one or more recovery jobs.

Abstract: An application programming interface (API) platform accesses cloud-based software services in a cloud computing system. API requests used in the API platform include a tenant specific endpoint (TSE) that uses a unique tenant identifier and an API endpoint as a URL domain. The unique tenant identifier identifies a tenant associated with the API request and the API endpoint identifies one of the cloud-based software services. The combination of the unique tenant identifier and the API endpoint in the domain of the TSE maps to an IP address for a specific software service in a specific one of the data centers in the cloud computing system assigned to the tenant. This allows API requests to be routed directly to the tenant specific data centers without first being routed through a central routing service.