LOG-BASED SYSTEM MAINTENANCE AND MANAGEMENT
    81.
    发明申请

    公开(公告)号:US20190095313A1

    公开(公告)日:2019-03-28

    申请号:US16037354

    申请日:2018-07-17

    Abstract: Methods and systems for system maintenance include identifying patterns in heterogeneous logs. Predictive features are extracted from a set of input logs based on the identified patterns. It is determined that the predictive features indicate a future system failure using a first model. A second model is trained, based on a target sample from the predictive features and based on weights associated with a distance between the target sample and a set of samples from the predictive features, to identify one or more parameters of the second model associated with the future system failure. A system maintenance action is performed in accordance with the identified one or more parameters.

    AUTOMATED EVENT ID FIELD ANALYSIS ON HETEROGENEOUS LOGS

    公开(公告)号:US20170279840A1

    公开(公告)日:2017-09-28

    申请号:US15429849

    申请日:2017-02-10

    CPC classification number: H04L63/1425

    Abstract: A system, program, and method for anomaly detection in heterogeneous logs. The system having a processor configured to identify pattern fields comprised of a plurality of event identifiers. The processor is further configured to generate an automata model by profiling event behaviors of the plurality of event sequences, the plurality of event sequences grouped in the automata model by combinations of one or more pattern fields and one or more event identifiers from among the plurality of event identifiers, wherein for a given combination, the one or more event identifiers therein must be respectively comprised in a same one of the one or more pattern fields with which it is combined. The processor is additionally configured to detect an anomaly in one of the plurality of event sequences using the automata model. The processor is also configured to control an anomaly-initiating one of the network devices based on the anomaly.

    Early Warning Prediction System
    85.
    发明申请

    公开(公告)号:US20170278007A1

    公开(公告)日:2017-09-28

    申请号:US15375291

    申请日:2016-12-12

    CPC classification number: G06N7/005 G06F11/30 G06N20/00

    Abstract: A computer-implemented method provides an early warning of an impending failure in a monitored system. The method includes performing, by a processor, an offline model learning process that generates a model of expected log rates in the monitored system from historical log data. The model represents a normal behavior of the monitored system. The method further includes performing an online detection process that detects the impending failure in the monitored system prior to an actual occurrence thereof based on (i) the model of expected log rates and (ii) observed log rates. The method also includes displaying, by a display device based on (i) the model of expected log rates and (ii) observed log rates in the monitored system, information relating to the impending failure prior to the actual occurrence of the impending failure. The online detection process identifies short term and long term failures and long term failures.

    Automated Anomaly Detection Service on Heterogeneous Log Streams

    公开(公告)号:US20170139806A1

    公开(公告)日:2017-05-18

    申请号:US15352546

    申请日:2016-11-15

    CPC classification number: G06F11/3612 G06F11/0706 G06F11/0766 G06F11/3636

    Abstract: Systems and methods are disclosed for handling log data from one or more applications, sensors or instruments by receiving heterogeneous logs from arbitrary/unknown systems or applications; generating regular expression patterns from the heterogeneous log sources using machine learning and extracting a log pattern therefrom; generating models and profiles from training logs based on different conditions and updating a global model database storing all models generated over time; tokenizing raw log messages from one or more applications, sensors or instruments running a production system; transforming incoming tokenized streams are into data-objects for anomaly detection and forwarding of log messages to various anomaly detectors; and generating an anomaly alert from the one or more applications, sensors or instruments running a production system.

    Path selection in hybrid networks
    89.
    发明授权
    Path selection in hybrid networks 有权
    混合网络中的路径选择

    公开(公告)号:US09413646B2

    公开(公告)日:2016-08-09

    申请号:US14831570

    申请日:2015-08-20

    Abstract: Systems and methods for controlling legacy switch routing in one or more hybrid networks of interconnected computers and switches, including generating a network underlay for the one or more hybrid networks by generating a minimum spanning tree (MST) and a forwarding graph (FWG) over a physical network topology of the one or more hybrid networks, determining an optimal path between hosts on the FWG by optimizing an initial path with a minimum cost mapping, and adjusting the initial path to enforce the optimal path by generating and installing special packets in one or more programmable switches to trigger installation of forwarding rules for one or more legacy switches.

    Abstract translation: 用于控制互连计算机和交换机的一个或多个混合网络中的传统交换机路由的系统和方法,包括通过在一个或多个混合网络上生成最小生成树(MST)和转发图(FWG)来生成用于所述一个或多个混合网络的网络底层 一个或多个混合网络的物理网络拓扑,通过利用最小成本映射优化初始路径来确定FWG上的主机之间的最佳路径,以及通过在一个或多个混合网络中生成和安装专用分组来调整初始路径以实施最佳路径 更多的可编程开关来触发一个或多个传统交换机的转发规则的安装。

    Transparent performance inference of whole software layers and context-sensitive performance debugging
    90.
    发明授权
    Transparent performance inference of whole software layers and context-sensitive performance debugging 有权
    整个软件层的透明性能推断和上下文敏感的性能调试

    公开(公告)号:US09367428B2

    公开(公告)日:2016-06-14

    申请号:US14512653

    申请日:2014-10-13

    CPC classification number: G06F11/3636 G06F11/3419

    Abstract: Methods and systems for performance inference include inferring an internal application status based on a unified call stack trace that includes both user and kernel information by inferring user function instances. A calling context encoding is generated that includes information regarding function calling paths. Application performance is analyzed based on the encoded calling contexts. The analysis includes performing a top-down latency breakdown and ranking calling contexts according to how costly each function calling path is.

    Abstract translation: 用于性能推理的方法和系统包括通过推断用户功能实例来推断基于包括用户和内核信息的统一调用堆栈跟踪的内部应用程序状态。 生成包含有关函数调用路径的信息的调用上下文编码。 基于编码的呼叫上下文来分析应用性能。 分析包括根据每个功能调用路径的代价昂贵地执行自上而下的延迟故障和排序呼叫上下文。

Patent Agency Ranking