Abstract: A computer-implemented method, system and computer program product for improving accuracy and efficiency of auditing databases. A table, list or index of a database is analyzed to identify metadata, which includes time series data, user data, an Internet Protocol address and operation data. The identified metadata is associated with the corresponding record or row of the table, list or index from which the metadata was extracted. A determination is then made as to whether to record a raw data image associated with the record or row of the analyzed table, list or index based on the corresponding data operation. The identified metadata as well as the recorded data images, if any, are stored in a structured audit log. Auditing information is then obtained from a structured audit log based on matching the record or row identifier (RID) associated with the query with the RID associated with the structured audit log.

Abstract: A computer-implemented method, a system, and a computer program product for service delivery are disclosed. In the method, a static analysis can be performed on a plurality of services to be deployed in an environment comprising a plurality of nodes, to determine dependency relationships among the plurality of services. The plurality of services can be deployed in the environment based on the dependency relationships, a predefined priority for each of the plurality of services, and deployment time for each of the plurality of services. Also, the plurality of services can be scheduled into corresponding nodes in the environment.

Abstract: Embodiments of the present disclosure relate to a method, system, and computer program product for comparison of database data. According to the method, a first tree structure corresponding to first data segments of first database data and a second tree structure corresponding to second data segments of second database data are at least partially obtained. Each node of the first or second tree structure indicating a characteristic value of at least one of the first or second data segments, and nodes of the first or second tree structure are divided into a first or second plurality of branches from a first or second root node based on update frequencies of the first or second data segments. A difference between the first data segments and the second data segments is determined by at least comparing characteristic values indicated by nodes in the obtained parts of the first and second tree structures.

Abstract: A set of tasks is extracted from workflow data of a system. A set of keywords is extracted from a task in the set of tasks. The set of keywords is expanded into an expanded set of keywords, the expanded set of keywords comprising a new keyword with a semantic relationship to a keyword in the set of keywords. A new task is generated using the expanded set of keywords. Based on a result of execution of the new task, a model of the system is adjusted, the model comprising the workflow data, the set of tasks, and the expanded set of keywords.

Abstract: Processing within a computing environment is facilitated by using a machine learning implicit-anomaly model to determine a possibility of an implicit anomaly within a system based on system metrics data obtained during running of one or more test cases on the system. The process further includes determining, using artificial intelligence, occurrence of an incident within the system associated with running of the one or more test cases. Determining the occurrence of the incident uses the determined possibility of the implicit anomaly within the system based on the system metrics data, and the process further includes initiating an action based on the occurrence of the incident within the system with running of the one or more test cases.

Abstract: Aspects of the invention include determining an event associated with a computing system, the event occurring at a first time, obtaining system data associated with the computing system, determining a system state of the computing system at the first time based on the system data, determining, based on the system state, two or more system data clusters comprising clustered system data associated with the system state of the computing system, determining, via an interpolation algorithm, an interpolated data value for the first time based on the system data, and adjusting the interpolated data value based on a determination that the interpolate data value is outside the two or more system data clusters.

Abstract: Disclosed are a computer-implemented method, a system and a computer program product for record management in a time series database (TSDB). In the computer-implemented method for record management in a TSDB, time series records can be obtained from distributed sources by one or more processing units. The records can be divided into different record groups based on a timestamp of each of the records by one or more processing units. The records in each of the record groups can be normalized into normalized records by one or more processing units. The normalized records can be stored in the TSDB by one or more processing units.

Abstract: A computer-implemented method includes receiving, by a processing unit, from a first tenant, a query to retrieve data from a nonrelational database system. The method further includes determining, by the processing unit, that an index associated with the query is cached in a shared index cache, wherein the shared index cache stores indexes for a plurality of tenants. The method further includes retrieving, by the processing unit, a result of the query based on the index in the shared index cache. The method further includes outputting, by the processing unit, the result of the query.

Abstract: Mechanisms are provided for scheduling a workload in a cloud computing system. A cloud affinity factor (CAF) computer model is trained, via a machine learning process based on a training dataset comprising static characteristics of a workload binary for a workload, and dynamic characteristics corresponding to historical performance data for the workload, such that the trained CAF computer model predicts a performance classification for a given workload binary. The trained CAF computer model processes a new workload to generate a performance classification for the new workload. Cloud affinity factor(s) are generated based on the performance classification for the new workload. Node affinity and dispatch rule(s) are applied to the cloud affinity factor(s) to select one or more nodes of the cloud computing system to which to dispatch the workload. The workload is then scheduled on the selected one or more nodes.

Abstract: Disclosed are a computer-implemented method, a system and a computer program product for record management in a time series database (TSDB). In the computer-implemented method for record management in a TSDB, time series records can be obtained from distributed sources by one or more processing units. The records can be divided into different record groups based on a timestamp of each of the records by one or more processing units. The records in each of the record groups can be normalized into normalized records by one or more processing units. The normalized records can be stored in the TSDB by one or more processing units.

Abstract: A method, computer system, and a computer program for monitoring synchronization and aggregation are provided. The method may include receiving a plurality of metrics and identifying a plurality of metadata associated with the plurality of metrics. The method may further include calculating a hash value of the plurality of metadata based on the plurality of metrics. The method may further include detecting at least one modification to the plurality of metadata based on the hash value and updating the plurality of metrics based on the at least one modification in which the plurality of metrics are displayed in a self-adapting metric diagram.

Abstract: Aspects of the invention include includes detecting a change in a code section of a source code in relation to a reference code section. An incremental section is created in object code, the incremental section includes an object code section describing the change in the code section and a symbol section describing a change to a symbol associated with the changed code section. The incremental section is attached to a software update. The software update to a target computer system.

Abstract: A computer-implemented method, system and computer program product for improving accuracy and efficiency of auditing databases. A table, list or index of a database is analyzed to identify metadata, which includes time series data, user data, an Internet Protocol address and operation data. The identified metadata is associated with the corresponding record or row of the table, list or index from which the metadata was extracted. A determination is then made as to whether to record a raw data image associated with the record or row of the analyzed table, list or index based on the corresponding data operation. The identified metadata as well as the recorded data images, if any, are stored in a structured audit log. Auditing information is then obtained from a structured audit log based on matching the record or row identifier (RID) associated with the query with the RID associated with the structured audit log.

Abstract: A method includes receiving, by a computing device, a first transaction from a user device for a first version of a database record; generating, by the computing device, a bit for the database record; receiving, by the computing device, a second transaction from a second user device for a second version of the database record; locking, by the computing device, the database record; determining, by the computing device, a modification between the first version of the database record and the second version of the database record; and updating, by the computing device, the bit in response to the modification.

Abstract: A computer-implemented method includes receiving, by a computing system, an update for a computer program executing on the computing system. The method further includes determining, by the computing system, a data structure that is affected by the update by checking a structure change information included in the update. The method further includes checking, by the computing system, instance-count of the data structure, the instance-count representing a number of instances of the data structure in a memory of the computing system. The method further includes based on a determination that the instance-count is zero, applying, by the computing system, the update to the computer program.

Abstract: Software for proximity positioning that performs the following operations: (i) receiving at least one parameter via an advertising channel of a first protocol, wherein the at least one parameter is encoded in an advertising packet of the first protocol, and wherein the first protocol supports a first proximity positioning technology; (ii) extracting the encoded at least one parameter from the advertising packet; and (iii) performing, by a second proximity positioning technology different from the first proximity positioning technology, a measurement of distance based, at least in part, on the at least one parameter.

Abstract: Aspects of the invention include includes detecting a change in a code section of a source code in relation to a reference code section. An incremental section is created in object code, the incremental section includes an object code section describing the change in the code section and a symbol section describing a change to a symbol associated with the changed code section. The incremental section is attached to a software update. The software update to a target computer system.

Abstract: A computer-implemented method for determining influence of applications on system performance includes collecting, by a processor, for several applications that are executing on a computing system, respective instrumentation data during multiple time-segments. The method further includes determining, for each of the applications, a performance value and a robustness value for each of the time-segments based on the respective instrumentation data. Further, using the performance value and robustness value for each time-segment, multiple health-waveforms are generated, where a health-waveform is generated for each respective application. The method further includes determining, by the processor, an influence-factor of a first application on a second application, the first application and the second application are executing on the computing system.

Abstract: Aspects of the invention include determining an event associated with a computing system, the event occurring at a first time, obtaining system data associated with the computing system, determining a system state of the computing system at the first time based on the system data, determining, based on the system state, two or more system data clusters comprising clustered system data associated with the system state of the computing system, determining, via an interpolation algorithm, an interpolated data value for the first time based on the system data, and adjusting the interpolated data value based on a determination that the interpolate data value is outside the two or more system data clusters.

Abstract: A computer-implemented method includes receiving, by a computing system, an update for a computer program executing on the computing system. The method further includes determining, by the computing system, a data structure that is affected by the update by checking a structure change information included in the update. The method further includes checking, by the computing system, instance-count of the data structure, the instance-count representing a number of instances of the data structure in a memory of the computing system. The method further includes based on a determination that the instance-count is zero, applying, by the computing system, the update to the computer program.