Collaborative Analysis System For Analyzing Logs

    公开(公告)号:US20240053994A1

    公开(公告)日:2024-02-15

    申请号:US18495095

    申请日:2023-10-26

    CPC classification number: G06F9/44526

    Abstract: Plugins that are independently written are executed in a collaborative manner to analysis a log. A plugin executing with respect to a particular node of a hierarchical data structure determines values for a set of keys based on information of the particular node and/or any ancestor nodes, and information stored in a shared repository. The plugin stores the values for the keys as additional information of the particular hierarchical node and/or into the shared repository. The plugin does not access information of non-ancestor nodes when executing with respect to the particular hierarchical node. Each plugin writes into and retrieves from the shared repository using the shared naming convention, thereby sharing information. The sequence of execution of the plugins is not dependent on dependencies amongst the plugins. If a dependent plugin requiring an output from a requisite plugin is first executed, the dependent plugin is flagged as pending and subsequently re-executed.

    GENERATING LOG TIMELINE DATA STRUCTURES BASED ON THE HIERARCHICAL DATA STRUCTURE

    公开(公告)号:US20230409350A1

    公开(公告)日:2023-12-21

    申请号:US18459282

    申请日:2023-08-31

    CPC classification number: G06F9/44526

    Abstract: Plugins that are independently written are executed in a collaborative manner to analysis a log. A plugin executing with respect to a particular node of a hierarchical data structure determines values for a set of keys based on information of the particular node and/or any ancestor nodes, and information stored in a shared repository. The plugin stores the values for the keys as additional information of the particular hierarchical node and/or into the shared repository. The plugin does not access information of non-ancestor nodes when executing with respect to the particular hierarchical node. Each plugin writes into and retrieves from the shared repository using the shared naming convention, thereby sharing information. The sequence of execution of the plugins is not dependent on dependencies amongst the plugins. If a dependent plugin requiring an output from a requisite plugin is first executed, the dependent plugin is flagged as pending and subsequently re-executed.

    VIRTUAL MACHINE CLUSTER PLACEMENT IN A CLOUD ENVIRONMENT

    公开(公告)号:US20230350733A1

    公开(公告)日:2023-11-02

    申请号:US17730883

    申请日:2022-04-27

    CPC classification number: G06F9/5077 G06F9/5044 G06F15/17331 G06F11/3409

    Abstract: Techniques are described herein for automatically determining optimal placement for VM clusters in multi-device infrastructure. Potential combinations of host nodes for a VM cluster are selected based on applicable constraints on host nodes for the cluster. Further, applicable optimization criteria (OC) for the VM cluster and/or the infrastructure are formally defined and modeled for automatic performance. Application of this placement model to the potential combinations of host nodes results in one or more OC metrics that may be directly compared so that alternate potential host node combinations may be ranked based on the determined OC metrics. The highest-ranked node combination is identified as the optimal VM cluster placement. The placement model can be used to implement initial, incremental, shuffling, or scaling placements of VM clusters. Further, hierarchical decisions may be made based on the determined OC metrics, allowing for application of the placement model to large and complex infrastructures.

    Generating a hierarchical data structure that represents a log

    公开(公告)号:US12106122B2

    公开(公告)日:2024-10-01

    申请号:US18459287

    申请日:2023-08-31

    CPC classification number: G06F9/44526

    Abstract: Plugins that are independently written are executed in a collaborative manner to analysis a log. A plugin executing with respect to a particular node of a hierarchical data structure determines values for a set of keys based on information of the particular node and/or any ancestor nodes, and information stored in a shared repository. The plugin stores the values for the keys as additional information of the particular hierarchical node and/or into the shared repository. The plugin does not access information of non-ancestor nodes when executing with respect to the particular hierarchical node. Each plugin writes into and retrieves from the shared repository using the shared naming convention, thereby sharing information. The sequence of execution of the plugins is not dependent on dependencies amongst the plugins. If a dependent plugin requiring an output from a requisite plugin is first executed, the dependent plugin is flagged as pending and subsequently re-executed.

    Declarative method of grouping, migrating and executing units of work for autonomous hierarchical database systems

    公开(公告)号:US11983197B2

    公开(公告)日:2024-05-14

    申请号:US17699740

    申请日:2022-03-21

    CPC classification number: G06F16/282 G06F16/21

    Abstract: Herein is database administration workflow automation with source annotations and intelligent scheduling techniques for applying a hierarchy of interdependent administrative tasks to distributed and/or nested databases. In an embodiment, a source language compiler analyzes annotations to identify a hierarchy of administrative tasks that administers pluggable databases in container databases. From the annotations, a runtime codebase is generated that implements and invokes the administrative task hierarchy. At runtime, a container database management system (CDBMS) autonomously identifies and instantiates the administrative tasks, including identifying a dependency of a first administrative task on a second administrative task and a lack of dependency of a third administrative task on the second administrative task. The CDBMS contains an intelligent scheduler that concurrently executes the second and third administrative tasks and defers execution of the first administrative task until after completion of the second administrative task. For example, the administrative tasks may be distributed to different databases for parallelism or instead sequenced for phased execution based on dependencies between administrative tasks or phases.

    Collaborative analysis system for analyzing logs

    公开(公告)号:US11822939B2

    公开(公告)日:2023-11-21

    申请号:US17703301

    申请日:2022-03-24

    CPC classification number: G06F9/44526

    Abstract: Plugins that are independently written are executed in a collaborative manner to analysis a log. A plugin executing with respect to a particular node of a hierarchical data structure determines values for a set of keys based on information of the particular node and/or any ancestor nodes, and information stored in a shared repository. The plugin stores the values for the keys as additional information of the particular hierarchical node and/or into the shared repository. The plugin does not access information of non-ancestor nodes when executing with respect to the particular hierarchical node. Each plugin writes into and retrieves from the shared repository using the shared naming convention, thereby sharing information. The sequence of execution of the plugins is not dependent on dependencies amongst the plugins. If a dependent plugin requiring an output from a requisite plugin is first executed, the dependent plugin is flagged as pending and subsequently re-executed.

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