公开(公告)号：US11886451B2

公开(公告)日：2024-01-30

申请号：US17515140

申请日：2021-10-29

Applicant: SPLUNK Inc.

Inventor： Sunil Kittinakere Nagesh Koundinya ,  Ramakrishnan Hariharan Chandrasekharapuram ,  Paul Ingram ,  Joseph Ari Ross

IPC: G06F16/2458

CPC classification number: G06F16/2462 ,  G06F16/2474 ,  G06F16/2477

Abstract: Described are systems, methods, and techniques for collecting, analyzing, processing, and storing time series data and for evaluating and determining whether and how to include late or delayed data points for inclusion when publishing or storing the time series data. Maximum delay values can identify a duration for waiting for late or delayed data, such as prior to publication. In some examples, maximum delay values can be dynamically adjustable based on a statistical evaluation process. For late or delayed data points that are received after the maximum delay elapses, some data points can be included in the stored time series data, such as if they are received in the same order that they are generated.

公开(公告)号：US11775501B2

公开(公告)日：2023-10-03

申请号：US16757354

申请日：2019-10-28

Applicant: Splunk Inc.

Inventor： Joseph Ari Ross ,  Matthew William Pound

IPC: G06F16/23 ,  G06F11/36

CPC classification number: G06F16/2365 ,  G06F11/3636

Abstract: Embodiments of the present disclosure provide for trace and span sampling and analysis for instrumented software. Each span may be annotated with one or more tags that provide context about an executed task, such as a user instrumenting the software, a document involved in a request, an infrastructure element used in servicing a request, etc. A sampler may perform tail-based sampling of traces comprising spans. The sampler may select a portion of the traces having selected features and send them to an analyzer. The analyzer may receive the selected traces and determine whether the selected traces are indicative of configuration problems for the instrumented software. An alert may be generated based on identified configuration problems.

公开(公告)号：US11663109B1

公开(公告)日：2023-05-30

申请号：US17384491

申请日：2021-07-23

Applicant: SPLUNK INC.

Inventor： William Deaderick ,  Tanner Gilligan ,  Joseph Ari Ross

IPC: G06F11/34 ,  G06F16/245 ,  G06F11/30

CPC classification number: G06F11/3452 ,  G06F11/3006 ,  G06F16/245

Abstract: Embodiments are directed to facilitating identifying seasonal frequencies. In particular, a set of candidate seasonal frequencies associated with a time series data set are determined based on ACF peaks identified in association with a representation of the time series data set. Thereafter, the filters are applied to analyze the candidate seasonal frequencies and update the candidate seasonal frequencies by removing any candidate seasonal frequencies that fail a filter. An example filter can include comparing ACF peaks with peaks associated with SDF peaks. Thereafter, a candidate seasonal frequency of the updated candidate seasonal frequencies can be identified as a seasonal frequency for the time series data set, and such a seasonal frequency can be provided (e.g., to a user or another process) for use in performing data analysis.

公开(公告)号：US20230136216A1

公开(公告)日：2023-05-04

申请号：US17515140

申请日：2021-10-29

Applicant: SPLUNK Inc.

Inventor： Sunil Kittinakere Nagesh Koundinya ,  Ramakrishnan Hariharan Chandrasekharapuram ,  Paul Ingram ,  Joseph Ari Ross

IPC: G06F16/2458

Abstract: Described are systems, methods, and techniques for collecting, analyzing, processing, and storing time series data and for evaluating and determining whether and how to include late or delayed data points for inclusion when publishing or storing the time series data. Maximum delay values can identify a duration for waiting for late or delayed data, such as prior to publication. In some examples, maximum delay values can be dynamically adjustable based on a statistical evaluation process. For late or delayed data points that are received after the maximum delay elapses, some data points can be included in the stored time series data, such as if they are received in the same order that they are generated.

公开(公告)号：US11379475B2

公开(公告)日：2022-07-05

申请号：US16858477

申请日：2020-04-24

Applicant: Splunk Inc.

Inventor： Gergely Danyi ,  Steven Flanders ,  Joseph Ari Ross ,  Justin Smith ,  Eric Wohlstadter ,  Chengyu Yang

IPC: G06F16/245 ,  G06F11/34 ,  G06F11/30

Abstract: A computer-implemented method for analyzing spans and traces associated with a microservices-based application executing in a distributed computing environment comprises aggregating a plurality of ingested spans associated with one or more applications executing in the distributed computing environment into a plurality of traces, wherein each of the plurality of ingested spans is associated with a plurality of tags. The method further comprises comparing durations of a set of related traces of the plurality of traces to determine patterns for the plurality of tags and generating a histogram that represents a distribution of the durations of the set of related traces. The method also comprises providing alerts for one or more tags from the plurality of tags associated with traces having a duration above a threshold based on the distribution of the durations.

公开(公告)号：US11281565B1

公开(公告)日：2022-03-22

申请号：US17030270

申请日：2020-09-23

Applicant: Splunk Inc.

Inventor： Joseph Ari Ross

IPC: G06F11/36 ,  G06F11/34 ,  G06F17/18 ,  G06F17/11

Abstract: An analysis system receives a time series. The data values of the time series correspond to a metric describing a characteristic of the computing system that changes over time. The analysis system stores a statistic value that represents the stationarity of the time series. In response to receiving a most recent value, the analysis system assigns the most recent value as the leading value in a window before retrieving the trailing value of the window. The analysis system updates the statistic value to add an influence of the most recent value and remove an influence of the trailing value. If the statistic value is less than a threshold, the analysis system determines that the time series is stationary. In response to determining the time series is stationary, the analysis system assigns an alert to the metric. The analysis system detects an anomaly in the metric based on the assigned alert.