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公开(公告)号:US20200372007A1
公开(公告)日:2020-11-26
申请号:US16757354
申请日:2019-10-28
Applicant: Splunk Inc.
Inventor: Joseph Ari Ross , Matthew William Pound
IPC: G06F16/23
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.
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公开(公告)号:US12222840B1
公开(公告)日:2025-02-11
申请号:US17974262
申请日:2022-10-26
Applicant: SPLUNK Inc.
Inventor: Steven Karis , Maxime Petazzoni , Matthew William Pound , Joseph Ari Ross , Charles Smith , Scott Stewart
IPC: G06F11/36 , G06F9/54 , G06F16/24 , G06F16/2455
Abstract: A method of generating metrics data associated with a microservices-based application comprises ingesting a plurality of spans and mapping an ingested span of the plurality of spans to a span identity, wherein the span identity comprises a tuple of information identifying a type of span associated with the span identity, wherein the tuple of information comprises user-configured dimensions. The method further comprises grouping the ingested span by the span identity, wherein the ingested span is grouped with other spans from the plurality of spans comprising a same span identity. The method also comprises computing metrics associated with the span identity and using the metrics to generate a stream of metric data associated with the span identity.
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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
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.
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公开(公告)号:US11620164B1
公开(公告)日:2023-04-04
申请号:US17033253
申请日:2020-09-25
Applicant: Splunk Inc.
Inventor: Steven Karis , Maxime Petazzoni , Matthew William Pound , Charles Smith , Chengyu Yang
Abstract: According to embodiments, a method for virtual partitioning of data includes receiving a data stream comprising a plurality of traces, each trace comprising a plurality of spans from a plurality of users. The method also includes assigning the plurality of traces of the data stream to a plurality of virtual partitions based on each user of the plurality of users, each virtual partition of the plurality of virtual partitions comprising data of a user of the plurality of users. The method also includes scheduling at least a subset of the plurality of virtual partitions to at least one user partition of a shared topic, the at least one user partition comprising data from at least one virtual partition of at least one user of the plurality of users. The method also includes indexing each user partition of the shared topic based on each user and each virtual partition.
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公开(公告)号:US11816511B1
公开(公告)日:2023-11-14
申请号:US18176381
申请日:2023-02-28
Applicant: Splunk Inc.
Inventor: Steven Karis , Maxime Petazzoni , Matthew William Pound , Charles Smith , Chengyu Yang
CPC classification number: G06F9/5077 , G06F9/4881 , G06F9/505 , G06F9/5083 , G06F9/542 , G06F11/3466 , G06F11/34 , G06F11/364 , G06F11/3636 , G06F16/24568
Abstract: According to embodiments, a method for virtual partitioning of data includes receiving a data stream comprising a plurality of traces, each trace comprising a plurality of spans from a plurality of users. The method also includes assigning the plurality of traces of the data stream to a plurality of virtual partitions based on each user of the plurality of users, each virtual partition of the plurality of virtual partitions comprising data of a user of the plurality of users. The method also includes scheduling at least a subset of the plurality of virtual partitions to at least one user partition of a shared topic, the at least one user partition comprising data from at least one virtual partition of at least one user of the plurality of users. The method also includes indexing each user partition of the shared topic based on each user and each virtual partition.
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公开(公告)号:US11526425B1
公开(公告)日:2022-12-13
申请号:US16835179
申请日:2020-03-30
Applicant: SPLUNK INC.
Inventor: Steven Karis , Maxime Petazzoni , Matthew William Pound , Joseph Ari Ross , Charles Smith , Scott Stewart
IPC: G06F11/36 , G06F9/54 , G06F16/2455
Abstract: A method of generating metrics data associated with a microservices-based application comprises ingesting a plurality of spans and mapping an ingested span of the plurality of spans to a span identity, wherein the span identity comprises a tuple of information identifying a type of span associated with the span identity, wherein the tuple of information comprises user-configured dimensions. The method further comprises grouping the ingested span by the span identity, wherein the ingested span is grouped with other spans from the plurality of spans comprising a same span identity. The method also comprises computing metrics associated with the span identity and using the metrics to generate a stream of metric data associated with the span identity.
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