Abstract: A common backup and recovery solution is provided for diverse cloud-based services in a productivity suite. The common backup and recovery solution can be configured to interface with an API platform that is associated with the productivity suite to thereby retrieve text-based data that identifies content of the diverse cloud-based services. The common backup and recovery solution can create a backup of the content by storing the text-based data. The common backup and recovery solution can also employ the text-based data to identify and obtain files that form part of the content and then store the files as part of the backup with the text-based data. To perform a recovery, the common backup and recovery solution can employ the text-based data of the backup and content of the files in the backup to send requests to the API platform that will cause the content to be restored.

Abstract: JDBC-X, which is distributed database driver middleware, can extend the JDBC API to facilitate integrating an application with a distributed database. JDBC-X functions as an intermediary between the JDBC API and the JDBC drivers and provides a number of components that adapt JDBC SQL queries and corresponding result sets in a manner that is substantially transparent to the application. In this way, an application that was originally designed to access a relational database can be seamlessly converted to accessing a distributed database. Similarly, JDBC-X allows an application to employ a distributed database that is dynamically provisioned without needing to be aware of the current structure of the database.

Abstract: In one embodiment, a method includes receiving logfile data, parsing the logfile data into parsed data elements and acquiring at least one contextual data element in relation to the parsed data elements. The method further includes structuring the parsed data elements and the at least one contextual data element as instances of a multirepresentational time-series log entry. In addition, the method includes publishing real-time time-series performance data and determining a user viewing context. Furthermore, the method includes automatically correlating the user viewing context to at least one dimension. Additionally, the method includes filtering the log-entry instances by the at least one dimension to yield filtered log-entry instances. Also, the method includes pivoting the filtered log-entry instances on one or more dimensions, the pivoting yielding pivoted data. In addition, the method includes publishing the pivoted data to a user interface.

Abstract: A full-text index can be created for each mailbox of an EDB to facilitate the performance of complex queries to quickly search for email data. In this way, relevant email data can be identified and retrieved quickly and efficiently from the full-text index rather than from the EDB. To create such indexes, each email in a mailbox can be retrieved and processed to convert the email from its native format into textual name/value pairs which can then be submitted for indexing. This use of name/value pairs to index each email enables the emails across all mailboxes to be efficiently queried using any possible combination of values.

Abstract: In one embodiment, a method is performed by a computer system. The method includes receiving base attribute values of a registrant device. The method further includes determining similarities of the base attribute values to a reference string to yield base similarity values. The method also includes registering the registrant device for policy enforcement using the base similarity values. Furthermore, the method includes, responsive to a trigger, determining target attribute values of a target device. Also, the method includes determining similarities of the target attribute values to the reference string to yield target similarity values. Moreover, the method includes, responsive to the target similarity values satisfying a similarity threshold in relation to the base similarity values, configuring policy enforcement such that the target device is treated as the registrant device.

Abstract: Simulation data can be generated using a linear curve simplification and reverse simplification technique. The linear curve simplification and reverse simplification technique can facilitate the generation of simulation data from existing data where the simulation data will exhibit the same curve pattern as the existing data but with a degree of variation. In this way, varying sets of simulation data for a particular environment can be easily generated.

Abstract: In one embodiment, a method includes identifying a plurality of period combinations for a metric of interest. Each period combination comprises one or more time periods and each of the one or more time periods comprises one or more segments. The method further includes, for each period combination of the plurality of period combinations and each historical value of a plurality of historical values of the metric of interest, incrementally inserting the historical value into corresponding segments of the one or more time periods. Moreover, the method includes ranking the plurality of period combinations based on comparisons of the plurality of historical values to sets of corresponding predicted values. The method also includes selecting a highest-ranked period combination as best characterizing the metric of interest.

Abstract: In one embodiment, a method includes extracting a cross-platform data-collection schema based, at least in part, on information available via heterogeneous interfaces of a plurality of source platforms. The cross-platform data-collection schema identifies a plurality of collectable data points in relation to particular source platforms. The method further includes configuring a cross-platform data-collection schedule for the plurality of source platforms. The cross-platform data-collection schedule indicates a collected subset of the plurality of collectable data points in relation to collection frequencies. The method also includes causing data values for the collected subset to be collected on an ongoing basis as dictated by the cross-platform data-collection schedule. Furthermore, the method includes processing a proposed change to at least one of the collected subset and the collection frequencies.

Abstract: In an embodiment, a method is performed by a computer system. The method includes automatically receiving, from an agent on a client device that is physically distinct from the computer system, a cookie corresponding to an active user session on a website. The active user session is previously established on the website in response to the website receiving valid user credentials from the client device. The method also includes storing the cookie in memory. In addition, the method includes, via the cookie, collecting information from the website over the active user session, thereby reusing the active user session. Further, the method includes periodically sending a dummy request comprising the cookie to the website, thereby preserving the active user session.

Abstract: Data loss prevention (“DLP”) rules can be automatically applied to items during a migration. When a migration is performed, a migration engine may be configured with migration configuration settings which define the items to be migrated from the source system to the target system. The migration engine may also be configured with DLP configuration settings which define the type of items on which DLP should be performed. When the DLP configuration settings indicate that DLP should be applied to an item to be migrated, the migration engine routes the item to a DLP engine rather than directly migrating the item to the target system. After the DLP engine has processed the item, the DLP engine can return the processed item to the migration engine which in turn can migrate the processed item to the appropriate location in the target system.

Abstract: In one embodiment, a method includes selecting a set of logged user-initiated events of a user. The method further includes determining timing information, device-identification information, and user-location information for the set of logged user-initiated events. In addition, the method includes correlating the set of logged user-initiated events to recurring time intervals of a time map. Also, the method includes determining an overall density, a location-specific density, and a device-specific density of the set of logged user-initiated events for at least some recurring time intervals of the time map. Furthermore, the method includes generating a time-based activity pattern of the user, the time-based activity pattern comprising, for the at least some recurring time intervals of the time map, information related to the overall density, the location-specific density, and the device-specific density. In addition, the method includes publishing the time-based activity pattern to a scheduling interface.

Abstract: In an embodiment, a method includes receiving time-series data related to individual utilization rates of a plurality of central processing unit (CPU) cores. The method also includes, responsive to a trigger, transforming at least a portion of the individual utilization rates into a compressed value format, the transforming comprising: determining, from at least a portion of the time-series data, CPU-core utilization values of the plurality of CPU cores for a time constraint; evaluating the CPU-core utilization values against a preconfigured set of non-overlapping value ranges; responsive to the evaluating, determining a quantity of the CPU-core utilization values that correspond to each non-overlapping value range of the preconfigured set of non-overlapping value ranges; and generating a CPU-core utilization snapshot comprising the determined quantity of each non-overlapping value range of the preconfigured set of non-overlapping value ranges.

Abstract: In one embodiment, a method includes executing at least one application. The method further includes collecting, at periodic intervals as the least one application executes, an application load of each of the at least one application. In addition, the method includes generating, based at least in part on the collecting, an application-behavior baseline for each of the at least one application. The application-behavior baseline includes a plurality of projected application loads over a future period of time. The application-behavior baseline has a configurable time resolution. The method also includes automatically determining, for a subperiod of the future period, a quantity of compute resources required to manage the at least one application in satisfaction of at least one performance criterion. Moreover, the method includes causing the determined quantity of compute resources to be proactively provisioned to the at least one application in advance of a start of the subperiod.

Abstract: A secure communication channel can be established between a recovery console and a recovery agent during an Active Directory disaster recovery. This secure channel can be established without employing the Kerberos or NT LAN Manager (NTLM) authentication protocols. Therefore, the recovery console and recovery agent will be able to establish a secure channel even when the domain controller is in Directory Services Restore Mode (DSRM) and NTLM is disabled. A secure channel can be established between the recovery console and the recovery agent based on the Microsoft Secure Channel (Schanel) Security Support Provider (SSP). The Schannel implementation can be modified in a manner that allows the client to be authenticated within the Schannel architecture.

Abstract: Systems and methods for using a synchronization mechanism to dynamically update instrumentation during program execution are described herein. Using the synchronization mechanism, a decision tree structure of instruments can be avoided, saving processing resources. The synchronization mechanism can be a field or the like that is declared using a synchronization primitive. For example, the synchronization primitive can be a volatile or synchronized keyword in some programming languages. The field can refer to a currently-selected instrument implementation, thereby avoiding using a decision-tree structure to find a desired instrument implementation.

Abstract: Systems and methods are described for identifying, tracking, and customizing dependencies between components of a computing environment. By providing greater insight and transparency into dependencies, the systems and methods can facilitate modeling the underlying architecture of applications and computer hardware. As a result, IT personnel can better track relationships between components. Custom filtering tools can also provide IT personnel with tools to switch from different types of dependency views that focus on application-oriented views, hardware-oriented views, or other custom views. Model annotation tools can also enable IT personnel to customize a dependency model to reflect real-world application and hardware monitoring conditions.

Abstract: In one embodiment, a method is performed by a computer system. The method includes receiving a request to authenticate a user of an enterprise computing system. The method further includes, responsive to the request, selecting a set of previous user-initiated events of the user on the enterprise computing platform. Further, the method includes accessing user-specific event information related to the selected set of previous user-initiated events. In addition, the method includes generating, from at least a portion of the user-specific event information, a user-specific authentication sequence comprising a plurality of event-information requests. Additionally, the method includes administering the user-specific authentication sequence to the user, the administering comprising requiring the user to provide a valid response to each of the event-information requests as a precondition to successful authentication.

Abstract: In one embodiment, a method includes registering as a listener for availability notifications from at least one low-availability device. The method further includes determining a data-collection schedule of the at least one low-availability device. In addition, the method includes maintaining a prioritized queue comprising required data items needed from the at least one low-availability device. Also, the method includes preparing, in advance of the at least one low-availability device becoming available, a request for at least one required data item. The at least one required data item includes a highest-priority data item in the prioritized queue. The method additionally includes, responsive to a notification that the at least one low-availability device is available, transmitting the request to the at least one low-availability device.

Abstract: In one embodiment, a method includes identifying at least one transaction-path node as a problem node based, at least in part, on an analysis of end-to-end response times for a group of transactions. The method further includes determining one or more event types for the at least one transaction-path node. Also, the method includes, for each of the one or more event types, inferring a first event-relevance weight from an abstract model. The method also includes, for each of the one or more event types, inferring a second event-relevance weight from a concrete model. Furthermore, the method includes, for each of the one or more event types, determining an event relevance based, at least in part, on the first event-relevance weight and the second event-relevance weight. Additionally, the method includes identifying most-relevant events among a set of active events based, at least in part, on the determined event relevance.

Abstract: In one embodiment, a method includes determining a particular microservice to connect to an instance of a first container to provide a service. The method further includes identifying, from container metadata, one or more inputs of the first container. The method also includes searching the container metadata for containers that provide the particular microservice and whose outputs satisfy the one or more inputs of the first container. In addition, the method includes selecting a second container based on the searching, the second container comprising one or more outputs. Also, the method includes creating an instance of the second container. Furthermore, the method includes connecting the instance of the second container to the instance of the first container using the one or more outputs of the second container and the one or more inputs of the first container.