Abstract: A method, a system, and a computer program product for monitoring of software applications are disclosed. A request for data associated with a software application is received. Based on the received request, a monitoring agent is injected in a response data. The response data is responsive to the received request. Using the monitoring agent, at least one transaction implementing the response data is monitored. The transaction is executed by the software application. Data associated with execution of the transaction is collected based on the monitoring.

Abstract: A system includes reception of a first data record, identification of one or more component elements in the first data record, application of a cleansing operation to change a first component element of the one or more component elements to a first cleansed component element, the first cleansed component element being different from the first component element, automatic determination a change significance of the change, and storage an identifier of the first cleansed component element in association with an identifier of the change significance.

Abstract: Techniques and solutions are described for determining, evaluating, and selecting data retrieval pathways. A plurality of database objects, such as tables, can be retrieved, and relationships between them determined. The relationships are between various attributes of the database objects. A plurality of pathways are determined between at least two target database objects, where the path determination does not consider attribute-level relationship information. After a path is determined, the relationship-level information can be added. A summary of the path, and relationship information, can be displayed to a user. A user can select paths to remove from the display, and can indicate one or more database objects that are required for a valid path, one or more database objects that are prohibited from valid paths, or combinations thereof. A user can select a path, and a query language statement to implement the path can be generated and displayed to the user.

Abstract: Technologies are described for improving the performance of distributed database systems. The technologies provide suggested table distributions that can reduce the performance overhead associated with database operations that involve multiple nodes, and can provide more even distribution of computing resource use. In a particular example, a method includes minimizing a scoring function that includes a plurality of performance metrics, at least a portion of the metrics being associated with a weight. Candidate table distributions can be analyzed in an iterative manner to determine a lowest-score distribution. A final table distribution can be output, such as to a user.

Abstract: An improved system and process for machine-learning upgrade analysis and training thereof is provided herein. A request to analyze the time to upgrade a current system to a target system may be received. A change list having one or more changes for the target system may be read. Custom code for the current system may be compared to the change list to identify recommended changes to the custom code to upgrade the custom code to be compatible with the target system. The recommended changes may be classified into one or categories respectively via a trained first machine-learning algorithm. Time to upgrade the custom code for the respective classified changes may be estimated via a trained second machine-learning algorithm. The recommended changes, the classifications of the recommended changes, and the time estimates of the recommended changes may be provided.

Abstract: Search results are received from an initiated free text search of log data from one or more logs, where the free text is performed using search terms entered into a free text search graphical user interface. A set of at least one search result is selected from the search results containing an event desired to be identified in a completed enterprise threat detection (ETD) pattern. A forensic lab application is rendered to complete an ETD pattern. An event filter is added for an event type based on normalized log data to a path. A relative ETD pattern time range is set and an ETD pattern is completed based on the added event filter.

Abstract: An application object framework provides a software developer with an ability to configure protocol extensions to the application object framework. The software developer may be enabled to configure protocol extensions to the application object framework that enable network communications using protocols that were not originally designed for use by the application object framework, or that did not exist at a time of creation or purchase of the application object framework.

Abstract: A system, a method, and a computer program product for deployment of objects are disclosed. At least one configuration for deploying of at least one artifact during runtime of an application is defined. The configuration includes at least one dependency for the artifact. The configuration is applied to the artifact. The artifact is deployed based on the applied configuration during runtime of the application. The configuration can include at least one of the following: a default configuration for the artifact and an explicit configuration for the artifact.

Abstract: The present disclosure describes methods, systems, and computer program products for performing a frequency domain analysis of activity data for a computer system. One computer-implemented method receiving time domain activity data for a computer system, wherein the time domain activity data comprise activity records associated with the computer system in a time domain; computing, by a hardware processor, frequency domain activity data based on the time domain activity data; and displaying the frequency domain activity data.

Abstract: Code block and test script debugging suggestion is discussed herein. An embodiment operates by receiving, by at least one processor, a data backup request from a first data client; determining, by at least one processor, a second data client to store data from the first data client; and issuing, by at least one processor, a peer-to-peer initialization request to the first and second data clients, wherein the peer-to-peer initialization request is based on the data backup request; wherein the first and second data clients are configured to establish peer-to-peer communications between the first and second data clients in response to the peer-to-peer initialization request.

Abstract: A big data database may store information to be used to generate results of aggregation queries. An aggregation query platform may include an aggregation query broker that receives an aggregation query from a remote user interface associated with a user and evaluates the aggregation query to determine if the aggregation query qualifies to be designated as a live query. The aggregation query platform may also include a dynamic aggregation engine to, if the aggregation query is designated as a live query by the aggregation query broker, store an indication of the aggregation query and automatically update a local dynamic result of the aggregation query when information in the big data database associated with the live query is changed.

Abstract: The present disclosure involves systems, software, and computer implemented methods for database scaling for multi-tenant applications. One example method includes receiving an indication to migrate a tenant of an application from a default database to a scale database. The tenant is locked. At least one stateful component that includes state information for the tenant is identified. The state information is serialized. The identified stateful component(s) are shut down. Data for the tenant is copied from the default database to the scale database. The tenant is assigned to the scale database. The serialized state information is de-serialized to generate de-serialized state information, and the de-serialized state information is stored in the scale database. The stateful component(s) are restarted and the tenant is unlocked.

Abstract: The present disclosure involves systems, software, and computer implemented methods for calculating hashes of archive files and their file entries. In one example, a method may include receiving an archive file which includes at least one compressed file, storing the archive file by sending a first copy of the archive file stream to a first processing thread which stores the archive file in a local file system, and applying a hash function to the archive file and the at least one compressed file to create hash values corresponding to the archive file and the at least one compressed file by sending a second copy of the archive file stream to a second processing thread, which applies the hash function to the archive file and the at least one compressed file to create the hash values and is executed in parallel to the first processing thread.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program provides a first visualization that includes a first set of data from a first data model. The program further provides a second visualization that includes a second set of data from a second data model. The program also receives an association between a first attribute in the first data model and a second attribute in the second data model. The program further receives a filter on the first set of data from the first data model. The program also applies the filter on the first visualization. The program further propagates the filter to the second visualization based on the association.

Abstract: A data-brokerage service that facilitates data sharing between Internet-of-Things (IoT) platforms via peer-to-peer connections is described. In various embodiments, the data-brokerage service receives, from an IoT platform acting as data consumer, a selection of data fields included in a plurality of data streams provided from a plurality of respective IoT platforms acting as data producers. Responsive to the selection, the data-brokerage service causes the plurality of data-producer platforms to stream at least the selected data fields of the plurality of data streams to the data-consumer platform, and causes the data-consumer platform to combine the streamed data fields received from the plurality of data-producer platforms into a single target data stream.

Abstract: Methods, systems, and computer-readable storage media for detecting a source of a defect in microservice-based applications, implementations including receiving at least one error log, the at least one error log including event data associated with at least one microservice in a set of microservices hosted on a cloud infrastructure, determining, for each microservice in the set of microservices, and for each type of defect in a set of types of defects, a probability that a respective microservice has a respective type of defect, and executing at least one action based on a probability indicating that a microservice of the set of microservices has a type of defect.

Abstract: Disclosed herein are system, method, and computer program product embodiments for data anonymization in an in-memory database. An embodiment operates by identifying a textual attribute corresponding to data of an input table. A value corresponding to the textual attribute is determined for each of the plurality of records. A plurality of groups is generated based on the determined values. At least portion of the data as sorted into the plurality of groups is provided.

Abstract: In offline access of data in mobile devices, a request to access a document is received at a mobile server. The document is fetched from a BI platform to the mobile server. Plurality of requests is sent from the mobile server to the BI platform to retrieve data packages from the BI platform. The data packages is converted to a plurality relational database management tables at the mobile server. The plurality of relational database management tables is compressed to a compressed database. The compressed database is sent to the mobile device and stored. A new request is received at the mobile device for operations on the document. Based on the new request, operations are performed on the document based on the compressed database stored in the mobile device, when the mobile device is not connected to the mobile server.

Abstract: Overlay visualizations are implemented utilizing data of a data layer. A table comprises a measure and two or more different dimensions mapping to a same value range. For visualization, the measure for those dimensions may be plotted along a common axis in a same chart. Accordingly, a query executes a UNION of multiple subqueries. A first subquery aggregates the first dimension over the value range, injecting a constant formula field to identify the original first dimension. A second subquery aggregates the second dimension over the value range, again injecting the constant formula field to identify the original second dimension. UNION of these subquery results presents one larger dataset for input to the overlying visualization layer. The constant formula field may be relied upon to differentiate between the combined dimensions on the common axis, allowing association of the measure values with the original dimensions in the displayed plot (e.g., via coloring).