Virtual Machine Firewall
    61.
    发明申请

    公开(公告)号:US20250077255A1

    公开(公告)日:2025-03-06

    申请号:US18456632

    申请日:2023-08-28

    Abstract: Embodiments are directed to a firewall for a virtual machine (“VM”) application. Embodiments initiate event monitoring of the VM application. Embodiments receive an event and compare the event to a plurality of events stored in a baseline profile of the VM application. When the event differs from any of the plurality of events, embodiments automatically generate an alert and/or perform an action corresponding to the VM application.

    Hardware optimized string table for accelerated relational database queries

    公开(公告)号:US12242481B1

    公开(公告)日:2025-03-04

    申请号:US18423196

    申请日:2024-01-25

    Abstract: Data structures and methods are described to enable a hardware optimized dynamic string table for accelerating relational database queries. A method comprises retrieving a lookup key for a query against a dynamic string table, the lookup key associated with a key length and a key hash. The method further comprises configuring a formatted lookup key as in-line or out-of-line based on whether the key length exceeds a maximum inline key size. The method further comprises replicating, into a first plurality of single instruction, multiple data (SIMD) lanes, the formatted lookup key. The method further comprises writing a candidate bucket, selected from the dynamic string table based on the key hash, into a second plurality of SIMD lanes. The method further comprises performing a SIMD compare of the first plurality of SIMD lanes and the second plurality of SIMD lanes, and returning an associated code when the lookup key is matched.

    Change data capture on no-master data stores

    公开(公告)号:US12242456B2

    公开(公告)日:2025-03-04

    申请号:US17959049

    申请日:2022-10-03

    Abstract: The present embodiments relate to implementing change data on no-master NoSQL data stores. An optimized node can be identified from a plurality of NoSQL data storage nodes and a specialized node can be connected (e.g., collocated) to the optimized node. The specialized node can maintain change data capture (CDC) data provided by client nodes in a hash map that can be used as a point of truth for coordinating CDC data across the plurality of NoSQL data storage nodes. The plurality of NoSQL data storage nodes can identify and coordinate all read/write data obtained from multiple client devices in a geographically separated large-scale (e.g., planet scale) system to identify change data in a distributed data store. The specialized data can provide read data to devices in the large-scale system to reconcile inconsistencies in change data across nodes in the large-scale system.

    Method for intelligent, dynamic, realtime, online relocation of pluggable databases across nodes based on system resource pressure

    公开(公告)号:US12242438B1

    公开(公告)日:2025-03-04

    申请号:US18494597

    申请日:2023-10-25

    Abstract: Techniques are provided for implementing a pluggable database monitoring system that groups running processes for the pluggable database into a grouping and monitors resource usage for the grouping to determine whether to migrate the pluggable database to another container. A system identifies a set of running processes associated with a pluggable database. The pluggable database is hosted on a container DBMS, which is hosted on a virtual machine. The system generates a first grouping that contains the set of running processes. The system monitors, in real-time, aggregated resource usage of the first grouping to determine if the aggregated resource usage exceeds a first threshold. In response to the aggregated resource usage of the first grouping exceeding the first threshold, the system migrates the first pluggable database to a second container DBMS.

    Transitioning between thread-confined memory segment views and shared memory segment views

    公开(公告)号:US12242394B2

    公开(公告)日:2025-03-04

    申请号:US18472511

    申请日:2023-09-22

    Abstract: Techniques for transitioning between memory segment views include: instantiating a first memory segment view that confines access to a memory segment to a first thread; receiving a request to transition ownership of the memory segment to a second thread; responsive to receiving the request to transition ownership of the memory segment to the second thread: instantiating a second memory segment view that permits access to the memory segment by the second thread; copying metadata from the first memory segment view to the second memory segment view; terminating the first memory segment view, to prevent access to the memory segment via the first memory segment view.

    Identifying root cause anomalies in time series

    公开(公告)号:US12242332B2

    公开(公告)日:2025-03-04

    申请号:US17962869

    申请日:2022-10-10

    Abstract: Techniques are described for identifying root cause anomalies in time series. Information to be used for root cause analysis (RCA) is obtained from a graph neural network (GNN) and is used to construct a dependency graph having nodes corresponding to each time series and directed edges corresponding to dependencies between the time series. Nodes corresponding to time series that do not contain anomalies may be removed from this dependency graph, as well as edges connected to these nodes. This edge and node removal may result in the creation of one or more sub-graphs from the dependency graph. A root cause analysis algorithm may be run on these one or more sub-graphs to create a root cause graph for each sub-graph. These root cause graphs may then be used to identify root cause anomalies within the multiple time series, as well as sequences of anomalies within the multiple time series.

    Associating capabilities and alarms

    公开(公告)号:US12242330B2

    公开(公告)日:2025-03-04

    申请号:US18164283

    申请日:2023-02-03

    Abstract: Techniques are described for monitoring the health of services in a computing environment such as a data center. More particularly, the present disclosure describes techniques for monitoring the health and availability of capabilities in a computing environment such as a data center by enabling alarms to be associated with the capabilities. A capability refers to a set of resources in a data center. By providing the ability to associate an alarm with a capability, the health or availability of the associated capability can be monitored or ascertained by tracking the state of the alarm associated with the capability. For example, if the alarm associated with a particular capability is triggered, it may indicate that the particular capability and the one or more resources corresponding to the particular capability are not in a healthy state. Accordingly, by monitoring alarms associated with capabilities, the health of the associated capabilities can be ascertained.

    Predicting Product Demand with Cluster-Based Product Cross-Elasticity Estimates

    公开(公告)号:US20250069104A1

    公开(公告)日:2025-02-27

    申请号:US18454697

    申请日:2023-08-23

    Abstract: Techniques for generating a retail forecasting model from product-cluster-based estimated elasticity values to forecast the effects of price changes on the demand for a set of products are disclosed. A system generates cluster-based price-elasticity values for a set of products by applying a set of regressive elasticity-estimation algorithms to a set of product data and clustering products based on product descriptions and estimated price-elasticity values. The system uses the cluster-based price-elasticity values for the products to generate the retail forecasting model.

    Enforcing Fairness on Unlabeled Data to Improve Modeling Performance

    公开(公告)号:US20250068979A1

    公开(公告)日:2025-02-27

    申请号:US18942116

    申请日:2024-11-08

    Abstract: Fairness of a trained classifier may be ensured by generating a data set for training, the data set generated using input data points of a feature space including multiple dimensions and according to different parameters including an amount of label bias, a control for discrepancy between rarity of features, and an amount of selection bias. Unlabeled data points of the input data comprising unobserved ground truths are labeled according to the amount of label bias and the input data sampled according to the amount of selection bias and the control for the discrepancy between the rarity of features. The classifier is then trained using the sampled and labeled data points as well as additional 10 unlabeled data points. The trained classifier is then usable to determine unbiased classifications of one or more labels for one or more other data sets.

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