GENERATING A HIERARCHICAL DATA STRUCTURE THAT REPRESENTS A LOG

    公开(公告)号:US20230409351A1

    公开(公告)日:2023-12-21

    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.

    COLLABORATIVE ANALYSIS SYSTEM FOR ANALYZING LOGS

    公开(公告)号:US20230325207A1

    公开(公告)日:2023-10-12

    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.

    DATA STRUCTURE GENERATION SYSTEM FOR ANALYZING LOGS

    公开(公告)号:US20230306007A1

    公开(公告)日:2023-09-28

    申请号:US17703269

    申请日:2022-03-24

    CPC classification number: G06F16/2246

    Abstract: New data structures for analyzing a log are generated. A hierarchical data structure includes a plurality of hierarchical nodes. Each node is associated with data and metadata. Each node may also be associated with analysis data. Information (data, metadata, and/or analysis data) of an ancestor node is imputed to a descendant node; a descendant node inherits the information of an ancestor node. When determining analysis data for a particular hierarchical node, information from any ancestor node to the particular hierarchical node may be used; however, information from non-ancestor nodes is not necessarily used. A timeline data structure includes a reference to a hierarchical node within a hierarchical data structure and a reference to an event type. The timeline data structure is thereby associated with the information of the referenced hierarchical node and information of any ancestor nodes to the referenced hierarchical node.

    Proactive performance supervision of multitenant cloud DB using hierarchical triage and comparative approach maintaining the data privacy and isolation

    公开(公告)号:US12282410B2

    公开(公告)日:2025-04-22

    申请号:US18471521

    申请日:2023-09-21

    Abstract: Herein are hierarchical and non-intrusive techniques to detect and diagnose incidental contention between database tenants. In an embodiment, a computer hosts a database server that operates a container database. The database server monitors level one performance metrics that characterize the performance of at least a first pluggable database (PDB) in the container database. The database server detects, in the level one performance metrics, a performance degradation of the first PDB. Responsively, the database server dynamically configures collection of level two performance metrics that characterize the performance of at least the first PDB and a second PDB in the container database. The database server detects, in the level two performance metrics, that the performance degradation is caused by the second PDB. The database server generates an alert that identifies the second PDB. The alert contains a particular metric of the level two performance metrics, and the particular metric characterizes the performance of the second PDB.

    PROACTIVE PERFORMANCE SUPERVISION OF MULTITENANT CLOUD DB USING HIERARCHICAL TRIAGE & COMPARATIVE APPROACH MAINTAINING THE DATA PRIVACY AND ISOLATION

    公开(公告)号:US20250103460A1

    公开(公告)日:2025-03-27

    申请号:US18471521

    申请日:2023-09-21

    Abstract: Herein are hierarchical and non-intrusive techniques to detect and diagnose incidental contention between database tenants. In an embodiment, a computer hosts a database server that operates a container database. The database server monitors level one performance metrics that characterize the performance of at least a first pluggable database (PDB) in the container database. The database server detects, in the level one performance metrics, a performance degradation of the first PDB. Responsively, the database server dynamically configures collection of level two performance metrics that characterize the performance of at least the first PDB and a second PDB in the container database. The database server detects, in the level two performance metrics, that the performance degradation is caused by the second PDB. The database server generates an alert that identifies the second PDB. The alert contains a particular metric of the level two performance metrics, and the particular metric characterizes the performance of the second PDB.

    CARDINAL METHOD FOR HIERARCHICAL PHASED SECURE ACCESS TO SYSTEM ENTITIES IN ISOLATED MULTI-TENANT DATABASE FOR AUTONOMOUS CLOUD ENVIRONMENTS

    公开(公告)号:US20230289459A1

    公开(公告)日:2023-09-14

    申请号:US17692709

    申请日:2022-03-11

    CPC classification number: G06F21/6218

    Abstract: Herein are multitenant database security techniques for fine-grained and dynamic access control of protected resources according to phases and roles. In an embodiment, a computer associates a process with a particular pluggable database of many pluggable databases in a container database in a database management system (DBMS). From the process, a request is received to access a protected resource that the particular pluggable database does not contain. Based on the protected resource and the particular pluggable database, the DBMS dynamically decides, in response to receiving the request, whether to permit access to the protected resource. Based on authorization by the DBMS, the protected resource is accessed to fulfil the request. In an embodiment, centrally managed policy decisions for restricted access are dynamically employed across a fleet of databases through a global policy manager.

    Fine grained memory and heap management for sharable entities across coordinating participants in database environment

    公开(公告)号:US11030123B2

    公开(公告)日:2021-06-08

    申请号:US16001335

    申请日:2018-06-06

    Abstract: Many computer applications comprise multiple threads of executions. Some client application requests are fulfilled by multiple cooperating processes. Techniques are disclosed for creating and managing memory namespaces that may be shared among a group of cooperating processes in which the memory namespaces are not accessible to processes outside of the group. The processes sharing the memory each have a handle that references the namespace. A process having the handle may invite another process to share the memory by providing the handle. A process sharing the private memory may change the private memory or the processes sharing the private memory according to a set of access rights assigned to the process. The private shared memory may be further protected from non-sharing processes by tagging memory segments allocated to the shared memory with protection key and/or an encryption key used to encrypt/decrypt data stored in the memory segments.

    Collaborative analysis system for analyzing logs

    公开(公告)号:US12106123B2

    公开(公告)日:2024-10-01

    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.

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