International Business Machines Corporation

Piotr Kania

Michal S Paluch

Tomasz Andrzej Stopa

Pawel K Gocek

Konrad K Skibski

Piotr P Godowski

Bartlomiej Tomasz Malecki

Pawel Tadeusz Januszek

Umit Bektas

Marek Peszt

Piotr Padkowski

Wlodzimierz Martowicz

Tomasz L Prudzic

Patryk M Walawender

Szymon M Brandys

Pawel Slowikowski

Artur Zezula

Slawomir T Mezyk

Marcin D Gierlak

Grzegorz Poniewozik

Krystian N Chmiel

Monika Grabska

Marcin Labenski

Krzysztof Pienkowski

Embodiments of the present invention include a method for running a virtual manager scheduler for scheduling activities for virtual machines. The method may include: defining a schedule for one or more activities to be executed for a virtual machine; applying an adjustment to the schedule in accordance with feedback information received via a virtual machine client aggregating the feedback information from a plurality of virtual machine clients, each being related to a virtual machine, per scheduled activity type; and determining of a group adjustment for a determined group of the virtual machine clients based on a function of the feedback information of the plurality of virtual machine clients.

Feedback analysis for virtual machines manager scheduling

An exclusion database is maintained for software discovery scans where directories within a file system are excluded according to discovered software artifacts, scan time parameters, and pre-defined exclusion definitions associated with software applications. A file system tree having directory-specific attributes for causing software discovery scans to limit scanning within the file system.

Software discovery using exclusion

An approach for optimizing single-row operations in a data warehouse. Single-row operations are determined based on receiving database operations. Extends identifiers are received based on the single-row operations. Single-row usage statistics are maintained for extends identifiers based on single-row operations. A logical sequence of the extends identifiers in extends lists stores are sorted based on single-row usage statistics and the logical sequence is maintained based on determining further single-row operations.

Data warehouse single-row operation optimization

Identification of unmatched registry entries may be provided by scanning a file system, discovering software, collecting first attribute values of the discovered software, and receiving a plurality of filtering rules including a method and an attribute. The attribute may comprise a software-specific condition. The method may further comprise collecting native registry entries comprising second attribute values indicated by said attributes of at least one of said rule, and comparing said first attribute values of said discovered software with related ones of said second attribute values of said collected native registry entries. Then, the native registry entries may be grouped into two groups. The first group represents matched registry entries and the second group represents unmatched registry entries. The unmatched registry entries may be identified as unequivocal entries for further software discovery. Finally, the filtering rules may be applied against said collected registry entries based on said filtering method.

Enhanceable cross-domain rules engine for unmatched registry entries filtering

In an approach for providing adaptive software inventory scan frequencies and schedules, a processor receives information from an initial scan of a set of software inventory scans, wherein the information includes at least one of: running processes, file system entries, registry entries, and software catalog evaluations. A processor analyzes the information from the initial scan. A processor predicts an outcome for future software inventory scans based on the analysis of the information, wherein the prediction includes a scanning frequency and a scanning schedule.

Dynamic scheduling for a scan

One or more processors determine that one or more memory locations in a client computing device contain one or more software artifacts that provide a match to a first software signature. One or more processors send instructions not to scan the one or more memory locations against a second software signature.

One or more processors scan a first software container template for one or more identities of software present on a first software container associated with the first software container template. One or more processors generate a map of the one or more identities of software present on the first software container. The one or more identities of software present on the first software container are mapped with one or both of: an identifier of the first software container template and an identifier of the first software container associated with the first software container template.

Determining the identity of software in software containers

A method for software discovery may be provided. The method may comprise scanning an shared resource mounted to an endpoint device for identifying installed software on the shared resource for the endpoint device, monitoring a read access to such identified installed software by the endpoint device using a monitoring agent, and marking the installed software as used on the shared resource by the endpoint device using a software asset management unit. Additionally, the method may comprise recording a last time use of the installed software by the endpoint device, and marking the installed software as uninstalled on the endpoint device after a predetermined time after the last time use.

Software discovery for software on shared file systems

A method and a related system for identifying unmatched registry entries may be provided. The method may comprise scanning a file system and discovering software based on a file signature, collecting first attributes of the discovered software, collecting native registry entries, and comparing the first attributes against second attributes of the collected registry entries based on a filtering rule. Thereby, the registry entries may be grouped into two groups. One group may represent matched registry entries and the other group may represent unmatched registry entries. The unmatched registry entries may be identified as unequivocal entries for further software discovery.

Identifying unmatched registry entries

An approach for optimizing single-row operations in a data warehouse. Single-row operations are determined based on receiving database operations. Extends identifiers are received based on the single-row operations. Single-row usage statistics are stored in extends lists stores where single-row usage statistics include at least one of a hit count and a last hit date. Single-row usage statistics are maintained for extends identifiers based on single-row operations. A logical sequence of the extends identifiers in extends lists stores are sorted based on single-row usage statistics and the logical sequence is maintained based on determining a further single-row operations.

Identification of unmatched registry entries may be provided, by scanning a file system, discovering software, collecting first attribute values of the discovered software, receiving a plurality of filtering rules including a method and an attribute. The attribute may comprise a software-specific condition. The method may further comprise collecting native registry entries comprising second attribute values indicated by said attributes of at least one of said rule, and comparing said first attribute values of said discovered software with related ones of said second attribute values of said collected native registry entries. Then, the native registry entries may be grouped into two groups. The first group represents matched registry entries and the second group represents unmatched registry entries. The unmatched registry entries may be identified as unequivocal entries for further software discovery. Finally, the filtering rules may be applied against said collected registry entries based on said filtering method.

Installation information of a software component is received. The software component is software. The installation information includes an installation state for the software component, an identifier for the software component, a vendor of the software component, and a calendar date of the installation. The installation information is stored in a pseudo-permanent database. The record of the installation information in the pseudo-permanent database will survive the uninstallation of the software component. An update to the installation information is received in response to the installation state of the software component changing. The update includes modified installation information and a calendar date of when the installation information changed. The updated installation information is stored in the pseudo-permanent database.

Storing computing component installation information

A method for collecting monitoring data on a set of monitored computers. The method comprises providing definitions for collection methods for a set of monitoring data, wherein the monitoring data is collected from agents running at monitoring computers, wherein each item of monitoring data has at least one respective collection method. The method further comprises determining a subset of monitoring data to be updated. The method further comprises identifying collection methods corresponding to the subset of monitoring data and triggering the agents running at the monitoring computers to collect monitoring data using the identified collection methods.

Query driven data collection on parallel processing architecture for license metrics software

A first computing entity receives a respective set of software discovery rules from each of a plurality of other computing entities. Based on each of the sets of software discovery rules, a set of software discovery rules associated with the first computing entity is modified. The modified set of software discovery rules is communicated to each of the plurality of other computing entities.

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Cracow, Poland

Piotr Kania