Abstract: An enhanced resource reconciliation process is disclosed to examine the metadata hierarchy of unidentified instances of configuration objects within a particular “data partition” (sometimes called a dataset) of an enterprise configuration management database (CMDB) and perform reconciliation against a target dataset, such as a golden, i.e., production, dataset. The enhanced reconciliation process could identify against instances in the production dataset that are of the same class as the unidentified instance—as well as instances that come from any “candidate” classes. Candidate classes could consist of, e.g., classes upstream or downstream from the unidentified instance in the metadata hierarchy.

Abstract: A method of administering a computing system, including a plurality of computing devices. The method includes selecting an application for download to a computing device, prior to downloading the application, decompiling the application, searching for string patterns in the decompiled application, replacing the string patterns in the decompiled application with another string pattern, the another string pattern being configured to intercept at least one of a system event or an Application Programming Interface (API) call, and associating logic with the application. The logic is configured to interact with the application via the at least one system event or API call, the logic is configured to provide additional functions to the application, the logic is configured to be shared between the application and at least one other application, and the logic is stored separate from the application.

Abstract: A method includes displaying, in a single story-mode presentation on a user interface, information on events occurring in and/or related to a business process managed by a business process management application. The single story-mode presentation includes a time map navigation section that displays a time map of events relevant to a first business task or object of the business process along a first time line, and an event details section that contains information corresponding to the events displayed in the time map navigation section.

Abstract: A plurality of virtual machines executing on physical machines may be monitored, and performance data characterizing consumption of physical resources of the physical machines by the plurality of virtual machines during the observation time may be extracted. Each of the plurality of virtual machines may be classified as active or idle during each time division of a plurality of time divisions of the observation time, based on the performance data and on idleness criteria, to thereby generate an active-idle series for each of the plurality of virtual machines. For each active-idle series of each virtual machine of the plurality of virtual machines, at least one periodicity of recurring idle times within the observation time may be determined. Then, for each virtual machine with the at least one periodicity, an on-off schedule may be determined, and each of the virtual machines may be transitioned with the at least one periodicity between an on state and an off state in accordance with the on-off schedule.

Abstract: In a general aspect, a system can include a user interface with at least one input field for receiving input associated with an information technology (IT) customer service issue and a response area for displaying results in response to the input. The system can further include a context generation engine that receives the input associated with the IT customer service issue from the user interface and determines, based on the input, a multi-factor context. The system can also include a relevance-based search engine configured to search, based on the multi-factor context, a plurality of resources; assign, based on the multi-factor context, a respective relevancy score to each of the plurality of resources; and provide, to the user interface for display in the results area, a ranked list of a subset of the plurality of resources that is ordered based on the respective relevancy scores of the subset of the resources.

Abstract: A mainframe computing system includes a central processor complex, a plurality of billing entities, each billing entity having a respective capacity limit, and a workload manager that schedules work requested by the plurality of billing entities on the central processor complex and tracks, by billing entity, a rolling average of millions of service units. The mainframe also includes a dynamic capping policy that identifies a maximum MSU limit, a maximum cost limit, a subset of the plurality of billing entities, and, for each billing entity in the subset, information from which to determine a MSU entitlement value and cost entitlement value. The mainframe also includes a dynamic capping master that adjusts the respective capacity limits of the subset of the plurality of billing entities at scheduled intervals based on the dynamic capping policy to favor billing entities having high-importance workload within the maximum MSU limit and maximum cost limit.

Abstract: A method on mainframe computing system includes determining a current phase of an ordered list of phases, the current phase being one of a plurality of phases in the ordered list of phases and setting a target phase based on the current phase, the ordered list of phases, and a parameter phase when the parameter phase is provided. The method also includes using the target phase and a resource assignment structure to start and stop a plurality of resources that run on the mainframe computing system. At least some of the plurality of resources have an assigned phase in the resource assignment structure. The method also includes repeating the determining, setting, and using, responsive to receiving a phase command.

Abstract: A method to reconcile multiple instances of a single computer resource identified by resource discovery operations includes: (1) accessing information describing one or more resources; (2) identifying, via the accessed information, at least one resource that has been detected or discovered by at least two of the discovery operations; and (3) merging attributes associated with the identified resource from each of the at least two discovery operations into a single, reconciled resource object. Illustrative “resources” include, but are not limited to, computer systems, components of computer systems, data storage systems, switches, routers, memory, software applications (e.g., accounting and database applications), operating systems and business services (e.g., order entry or change management and tracking services).

Abstract: A method includes receiving a floor map indicating a layout of a location, displaying at least a portion of the floor map, capturing signal strength data representing a signal field for at least one position on the floor map, identifying an asset within the layout of the location, determining at least one property that identifies the asset using one of a discovery process using a wireless protocol and an image processing application programming interface (API) configured to classify an image and detect individual within the image, updating the floor map with the asset and the at least one property, and communicating the asset and the at least one property to the remote computing device.

Abstract: Described is a method for auction based decentralized ticket allotment. The method includes receiving a ticket indicating a system problem, generating an auction for the ticket, receiving at least one bid, based on the auction, to resolve the system problem from at least one agent, the at least one bid including one of a time to resolution, a hold and a no bid, and allotting the ticket to an agent based on the at least one bid.

Abstract: A method includes receiving a map indicating a layout of a location, receiving a point-of-interest (POI) data structure representing a POI, and POI metadata associated with the POI, generating an annotated floor map, based on the map, the annotated floor map including a POI indicator placed on the map at the location of the POI, the POI indicator indicating the type of the POI and the status of the POI, displaying at least a portion of the annotated floor map, in response to the client computing device moving within the location or out of the location, transmitting location information to a map selector and receiving one or more maps selected by the map selector, the one or more maps include or bound by the location information.

Abstract: An example system may include one or more collectors and an analyzer. The one or more collectors receive a plurality of data streams that include operational data for a plurality of application nodes. The plurality of data streams are captured and provided by a plurality of meters deployed on at least one cloud computing platform to respectively meter the plurality of application nodes. The analyzer processes the plurality of data streams to generate real-time performance data for a first application of a plurality of applications and generates, based on the real-time performance data for the application instances, statistics for data flows between components of the first application. The analyzer generates comparative statistics on the performance of the first application relative to the performance of the plurality of applications hosted, and reallocated, based on the comparative statistics, resources for the performance of the first application.

Abstract: Disclosed are methods and systems to provide coordinated identification of data items across a plurality of distributed data storage repositories (datastores). In one disclosed embodiment, a single configuration management database (CMDB) controls identification rights for all CIs as they are first identified in a master/slave relationship with all other CMDBs in the distributed environment. In a second embodiment, a plurality of CMDBs divide identification rights based upon coordination identification rules where certain CMDBs are assigned authoritative identification rights for CIs matching the rules of a particular CMDB in the distributed environment. In a third embodiment, one or more of the plurality of CMDBs may also have advisory identification rights for CIs which do not already have an identifiable unique identity and can coordinate with an authoritative CMDB to establish an identity for CIs.

Abstract: Systems and methods provide automatic discovery of cluster membership based on transaction processing. An example method includes, at a source node of a first tier of nodes, generating a service identifier for a transaction that requests a service hosted by a second tier, the service identifier being based on a logical identifier for the second tier. The method also includes sending the transaction, including the service identifier, from the source node to the service hosted by the second tier. The method includes, at a destination node in the second tier, obtaining the service identifier from the transaction and reporting the service identifier with a destination node identifier to a visibility server as cluster information. The method also includes, at the visibility server, receiving cluster information from a plurality of destination nodes and assigning each of the plurality of destination nodes to a cluster based on the service identifiers.

Abstract: According to one general aspect, a method may include receiving a data query request that includes one or more search parameters to be searched for within a plurality of files that are stored according to a hierarchical organizational structure, wherein each file includes at least one data record. The method may include scanning a plurality of files to determine if one or more files match a sub portion of the search parameters. The method may further include parsing the candidate files to determine which, if any, records included by the respective candidate files meet the search parameters. The method may include generating, by one or more result analyzers, query results from the resultant data. The method may also include streaming, to the user device, the query results as at least one query result becomes available and to start streaming before the query requests have been fully generated.

Abstract: A computer system for classifying one or more servers by server type in a networked computing system to institute server-type based monitoring and or maintenance of the networked computing system. The computer system includes a processor, a memory, a data receiver, a server signature generator, and a server-type tagging service. The data receiver collects server performance data for a first server over a time interval. The server signature generator determines a signature of the first server based on the collected server performance data. The server-type tagging service compares the signature of the first server to a signature of a second server of known server type, determines a similarity of the signature of the first server to the signature of the second server, and, based on the similarity, classifies the first server as being of the same server type as the second server.

Abstract: Data is often populated into Configuration Management Databases (CMDBs) from different sources. Because the data can come from a variety of sources, it may have inconsistencies—and may even be incomplete. A Normalization Engine (NE) may be able to automatically clean up the incoming data based on certain rules and knowledge. In one embodiment, the NE takes each Configuration Item (CI) or group of CIs that are to be normalized and applies a rule or a set of rules to see if the data may be cleaned up, and, if so, updates the CI or group of CIs accordingly. In particular, one embodiment may allow for the CI's data to be normalized by doing a look up against a Product Catalog and/or an Alias Catalog. In another embodiment, the NE architecture could be fully extensible, allowing for the creation of custom, rules-based plug-ins by users and/or third parties.

Abstract: Methods, devices and systems to make compressed backup copies of in-use compressed database indices are described. In general, an “oldest” time at which index pages in working memory had been updated is identified. Compressed index pages may be directly copied without the need to bring them into working memory or uncompressing them. The identified “oldest” time is then associated with the compressed backup copy. In some embodiments, an entire compressed backup copy may be associated with a single point in time (e.g., the identified “oldest” time). In other embodiments, a compressed backup copy may be associated with multiple points in time (e.g., one time for each portion of the compressed index that is being backed-up). Compressed indices copied in accordance with the invention may be used during restore operations to reconstruct database indices using the identified “oldest” time and database log files.

Abstract: Disclosed are methods and systems to automatically integrate work requests from multiple Spoke systems at a centralized Hub system. In one embodiment, a Hub system receives a portion of a work request from a problem tracking system executing in the region (e.g., geographic area or network subnet) of an associated Spoke system. The request comprises enough information for the Hub system to prioritize this work request against other work requests already received from this same Spoke system, other Spoke systems in the same region, or even other Spoke systems from other regions. A Hub user can then be presented with an integrated work queue of requests to service after they have been properly prioritized. The Hub user may be supporting multiple clients in an outsourcing style Information Technology (IT) support model or a call center model. Supported clients can execute on different data center platforms, at the same time.

Abstract: Overlay datasets provide an efficient, flexible and scalable mechanism to represent the logical replication of one or more prior defined datasets. Only changes made to an entity in an overlay dataset's underlying dataset are replicated into the overlay dataset (such changes do not affect the underlying dataset). Read operations directed to the overlay dataset will find entities in the overlay dataset if they exist and in the underlying dataset(s) if no overlay-specific entity exists. Accordingly, overlay datasets provide an efficient mechanism for making changes to an existing dataset without suffering the high processing time and storage overhead associated with prior art copying and versioning techniques. Overlay datasets also provide a natural mechanism to keep two or more datasets in synchronization because changes to a base or underlying dataset's entities are “visible” in its associated overlay dataset (unless the entity has been modified in the overlay dataset).