Abstract: A system and method for providing content for display form data sources on a client device are provided. The method includes receiving, by a distribution server, a report identifier associated with a report and a request for information, wherein the information is requested based on the report; determining by the distribution server at least a data source, the at least a data source storing at least a portion of the information; requesting access from the integration server to the at least a data source to retrieve the at least a portion of the information; and sending from the distribution server to the client device, the at least a portion of the information, wherein the at least a portion of information is utilized in the report. In an embodiment, the data sources are accessible by an integration server.

Abstract: The representative embodiments discussed in the present disclosure relate to techniques with which data packet loss, such as Transmission Control Protocol (TCP) packet loss, may be detected. More specifically, in some embodiments, by detecting a TCP packet with an enabled selective acknowledgement (SACK) signal, the loss (e.g., drop) of an additional TCP packet may be determined. Moreover, using information included in the detected TCP packet, an operational efficiency of a cloud computing system and/or a component of the cloud computing system may be determined.

Abstract: A specification of an information technology change is received via an information technology service management system. The specification of the information technology change is analyzed to determine features of the information technology change. Machine-generated data is analyzed to identify a phenomena detected in the machine-generated data. To a machine learning model, the features of the information technology change and features of the detected phenomena in the machine-generated data are provided to determine a correlation between the information technology change and the detected phenomena in the machine-generated data.

Abstract: A management system to facilitate improved software asset management includes a management server coupled to a client instance and certain databases. The client instance stores identifiers associated with software programs accessible to users through the client instance. To enable software asset management features, the management server receives the identifiers and determines, based on the certain databases, whether the identifiers are associated with software models of the software programs. Notably, in response to an identifier of a particular software program not being associated with a software model, the management server generates a software model for the particular software program, and further, stores entries or relationships within the certain databases.

Abstract: A document is received. The document is analyzed to discover text and structures of content included in the document. A result of the analysis is used to determine intermediate text representations of segments of the content included in the document, wherein at least one of the intermediate text representations includes an added text encoding the discovered structure of the corresponding content segment within a structural layout of the document. The intermediate text representations are used as an input to a machine learning model to extract information of interest in the document. One or more structured records of the extracted information of interest are created.

Abstract: A remote network management platform manages a managed network. The managed network may contain computing devices for executing applications. The remote network management platform may also include a database storing a graph that represents the computing devices, the applications, and relationships therebetween. A computing device may be configured to generate and provide a graphical user interface that includes: (i) a panel containing an active copy of the graph read from the database, (ii) a first selectable control that creates an editable, private copy of the graph and replaces the active copy of the graph in the panel with the editable, private copy of the graph, and (iii) a second selectable control that updates the active copy of the graph with the editable, private copy of the graph, saves the active copy of the graph as updated to the database, and displays the active copy of the graph as updated.

Abstract: An embodiment may involve a definition of a process, wherein the process is referenced by a parent entry, wherein the process includes a set of stages, wherein the stages in the set of stages are respectively associated with sets of activities, and wherein a process design application was used to define the process. The embodiment may also include one or more processors configured to: (i) receive a reference to the parent entry; (ii) identify a transformer class associated with the process design application, wherein the transformer class converts output in a first configuration related to the process design application to input in a second configuration; (iii) receive, from the transformer class, data related to the process in the second configuration; and (iv) generate a graphical user interface that displays the process and the set of stages in a hierarchical arrangement.

Abstract: Disclosed herein are enterprise applications and platforms that manage databases containing documents and may employ search systems that allow users to retrieve documents based on queries. The search systems may be configured to retrieve data from several different data sources and may be associated with many of the applications. Furthermore, the search systems may include a faceted interface based on database or document attributes for further search refinement. The faceted interface may be template-based and modular, allowing reconfiguration of the interfaces without substantial rewriting of the application code base.

Abstract: A source computational instance may be configured to operate a software application and store a first set of content related to the software application. A target computational instance may be configured to operate the software application and store a second set of content related to the software application. The software application operated by the target computational instance may apply transformation rules to received content before storing the received content in the second set of content. The source computational instance may be further configured to receive selected content chosen from the first set of content and an indication of the target computational instance, and transmit the selected content to the target computational instance. The target computational instance may be further configured to receive the selected content, apply the transformation rules to the selected content, and store the selected content within the second set of content.

Abstract: A server receives a first hypertext transfer protocol (HTTP) from a client device that requests first and second items of content associated with a webpage and applies a defer directive to the second item. The server retrieves, from a database, via a single worker thread, first data associated with the first item and transmits a first message comprising the first data associated with the first item. The server retrieves, from the database, via the worker thread, second data associated with the deferred item and transmits a second message comprising the second data associated with the second item.

Abstract: An embodiment may involve: transmitting, by a non-production computational instance and to a central computational system, a configuration for a service provided by the central computational system, wherein the non-production computational instance is arranged to test the configuration; appending, to the configuration at the non-production computational instance, a synchronization identifier to indicate that the configuration has been synchronized with the central computational system; receiving, by a production computational instance and from the non-production computational instance, a copy of the configuration; reading, by the production computational instance, the synchronization identifier from the copy of the configuration; determining that the synchronization identifier is not reflected as part of a synchronization history maintained at the production computational instance; and, in response to determining that the synchronization identifier is not reflected in the synchronization history, transmitting

Abstract: At least service task data and application utilization data are collected. The collected data is analyzed to determine a utilization pattern. Based on the determined utilization pattern, a computer automation opportunity is automatically identified. An automatically generated recommendation of an automation solution among a plurality of automation solution candidates is provided for the identified computer automation opportunity.

Abstract: A request to perform a prediction using a machine learning model of a specific entity is received. A specific security key for the machine learning model of the specific entity is received. At least a portion of the machine learning model is obtained from a multi-tenant machine learning model storage. The machine learning model is unlocked using the specific security key and the requested prediction is performed. A result of the prediction is provided from a prediction server.

Abstract: An embodiment may involve a plurality of configuration items and an unmatched configuration item, wherein the unmatched configuration item is associated with a first set of attribute values and a first vulnerability, wherein the first vulnerability is associated with a first set of field values.

Abstract: A software architecture within a public cloud network may include units of: (i) a plurality of computational instances respectively related to managed networks, (ii) a plurality of servers configurable as load simulators, (iii) administrative components configured to deploy and update the software architecture, and (iv) shared infrastructure services, wherein the units of the software architecture are implemented on virtual machines of the public cloud network and are connected to but logically isolated from one another by way of different access controls or policies. A provider network, coupled to the software architecture by way of network gateways within the shared infrastructure services, may be configured to deliver the configuration, software packages, and database schema to the infrastructure-as-code platform.

Abstract: An embodiment involves persistent storage and one or more processors. The persistent storage may contain a plurality of hardware models specifying types of computing devices, wherein the hardware models include attributes representing manufacturer names, product names, and model numbers of the computing devices. The processors may be configured to: obtain, from the persistent storage, a hardware model; calculate a hash value over attributes of the hardware model; compare the hash value to hash values in a curated list, the curated list including normalized hardware models that map the hash values to normalized manufacturer names, normalized product names, or normalized model numbers; determine that the hash value matches a particular hash value for a normalized hardware model; and update, in the persistent storage, the hardware model to include at least one of a normalized manufacturer name, a normalized product name, or a normalized model number associated with the normalized hardware model.

Abstract: An embodiment may involve a database containing a first user profile that specifies a first preferred language of a first user and a second user profile that specifies a second preferred language of a second user. The embodiment may also involve one or more processors configured to: receive, from the first user and within a chat session, a first set of messages in the first preferred language; cause the first set of messages to be translated into the second preferred language; provide, to the second user and within the chat session, the first set of messages as translated; receive, from the second user and within the chat session, a second set of messages in the second preferred language; cause the second set of messages to be translated into the first preferred language; and provide, to the first user and within the chat session, the second set of messages as translated.

Abstract: A system includes persistent storage containing data used by software applications, and a server application configured to perform operations, including identifying a subset of the data, where the subset is used to generate a full offline payload for a particular software application and that includes user interface (UI) components selected for the particular software application based on the subset of the data. The operations also include monitoring the subset of the data to identify a modification to particular data and, based on identifying the modification, generating a partial offline payload based on the particular data as modified, where the partial offline payload includes a subset of the UI components, and where each UI component of the subset is updated based on the particular data as modified. The operations further include receiving a request for the partial offline payload and, based on receiving the request, transmitting the partial offline payload.

Abstract: An embodiment may involve persistent storage containing a machine learning trainer application configured to apply one or more learning algorithms. One or more processors may be configured to: obtain alert data from one or more computing systems; generate training vectors from the alert data, wherein elements within each of the training vectors include: results of a set of statistics applied to the alert data for a particular computing system of the one or more computing systems, and an indication of whether the particular computing system is expected to fail given its alert data; train, using the machine learning trainer application and the training vectors, a machine learning model, wherein the machine learning model is configured to predict failure of a further computing system based on operational alert data obtained from the further computing system; and deploy the machine learning model for production use.

Abstract: A computing system includes persistent storage configured to store representations of software applications installed on computing devices, and a software application configured to perform operations, including retrieving, from the persistent storage, a first plurality of representations of a first plurality of software applications installed on a particular computing device and a second plurality of representations of a second plurality of software applications installed on a reference computing device. The operations also include determining a device fingerprint of the particular computing device based on the first plurality of representations and a reference device fingerprint of the reference computing device based on the second plurality of representations, and comparing the device fingerprint to the reference device fingerprint.