Real-time reporting based on instrumentation of software

    公开(公告)号:US11010278B2

    公开(公告)日:2021-05-18

    申请号:US16542318

    申请日:2019-08-16

    Applicant: Splunk Inc.

    Abstract: A data analysis system processes data generated by instrumented software. The data analysis system receives data streams generated by instances of instrumented software executing on systems. The data analysis system also receives metadata describing data streams. The data analysis system receives an expression based on the metadata. The data analysis system receives data of data streams for each time interval and computes the result of the expression based on the received data values. The data analysis system repeats these steps for each time interval. The data analysis system may quantize data values of data streams for each time interval by generating an aggregate value for the time interval based on data received for each data stream for that time interval. The data analysis system evaluates the expression using the quantized data for the time interval.

    Tracking error propagation across microservices based applications using distributed error stacks

    公开(公告)号:US11010235B1

    公开(公告)日:2021-05-18

    申请号:US16672174

    申请日:2019-11-01

    Applicant: SPLUNK INC.

    Abstract: A method of performing error analysis in a system comprising microservices comprises identifying a root cause error span from among a plurality of error spans for a trace associated with a user-request, wherein an error span is a span that returns an error to a microservice initiating a call resulting in the span, and wherein a root cause error span is an error span associated with an error originating microservice. The method further comprises determining a call path associated with the root cause error span, where the call path comprises a chain of spans starting at the root cause error span, and where each subsequent span in the chain is a parent span of a prior span. Subsequently the method comprises mapping each span in the chain to a span error frame to create an error stack and rendering an image of the error stack.

    TRACKING ERROR PROPAGATION ACROSS MICROSERVICES BASED APPLICATIONS USING DISTRIBUTED ERROR STACKS

    公开(公告)号:US20210133014A1

    公开(公告)日:2021-05-06

    申请号:US16672174

    申请日:2019-11-01

    Applicant: SPLUNK INC.

    Abstract: A method of performing error analysis in a system comprising microservices comprises identifying a root cause error span from among a plurality of error spans for a trace associated with a user-request, wherein an error span is a span that returns an error to a microservice initiating a call resulting in the span, and wherein a root cause error span is an error span associated with an error originating microservice. The method further comprises determining a call path associated with the root cause error span, where the call path comprises a chain of spans starting at the root cause error span, and where each subsequent span in the chain is a parent span of a prior span. Subsequently the method comprises mapping each span in the chain to a span error frame to create an error stack and rendering an image of the error stack.

    Data source correlation user interface

    公开(公告)号:US10997192B2

    公开(公告)日:2021-05-04

    申请号:US16264562

    申请日:2019-01-31

    Applicant: Splunk Inc.

    Abstract: Systems and methods are disclosed for implementing a data stream correlation user interface. The data stream correlation user interface provides workflows for selecting individual data sources from a matrix of data sources, identifying individual data fields of the data sources, establishing criteria for determining correlations between them, and reviewing and enabling user verification of correlated data sources. Correlations may be established based on the values of data fields in individual records of the data sources, and may be determined based on correspondences or associations between the values, lookup tables, formulas, user-specified criteria, or other relationships.

    MANAGEMENT OF DISTRIBUTED COMPUTING FRAMEWORK COMPONENTS IN A DATA FABRIC SERVICE SYSTEM

    公开(公告)号:US20210117425A1

    公开(公告)日:2021-04-22

    申请号:US16657899

    申请日:2019-10-18

    Applicant: Splunk Inc.

    Abstract: Systems and methods are described for establishing and managing components of a distributed computing framework implemented in a data intake and query system. The distributed computing framework may include a master and a plurality of worker nodes. The master may selectively operate on a search head captain that is chosen from the search heads of the data intake and query system. The search head captain may distribute configuration information for the master and the distributed computing framework to the other search heads, which in turn, may distribute that configuration information to indexers of the data intake and query system. Worker nodes may be selectively activated for operation on the indexers based on the configuration information, and the worker nodes may additionally use the configuration information to contact the master and join the distributed computing framework. This approach may provide numerous benefits, including improved security, flexibility in the selection of worker nodes, and redundancy for failures of physical components of the data intake and query system.

    ANOMALY DETECTION IN DATA INGESTED TO A DATA INTAKE AND QUERY SYSTEM

    公开(公告)号:US20210117416A1

    公开(公告)日:2021-04-22

    申请号:US16779479

    申请日:2020-01-31

    Applicant: Splunk Inc.

    Abstract: Systems and methods are described for processing ingested data in an asynchronous manner as the data is being ingested to detect potential anomalies. For example, one or more streaming data processors can convert data as the data is ingested into a comparable data structure, determine whether the comparable data structure should be assigned to an existing data pattern or a new data pattern, and optionally update a characteristic of the data pattern to which the comparable data structure is assigned. The streaming data processor(s) can perform these operations automatically in real-time or in periodic batches. Once one or more comparable data structures have been assigned to one or more data patterns, the streaming data processor(s) can analyze the comparable data structures assigned to a particular data pattern to determine whether any of the comparable data structures appear to be anomalous.

    ANOMALY AND OUTLIER EXPLANATION GENERATION FOR DATA INGESTED TO A DATA INTAKE AND QUERY SYSTEM

    公开(公告)号:US20210117415A1

    公开(公告)日:2021-04-22

    申请号:US16779460

    申请日:2020-01-31

    Applicant: Splunk Inc.

    Inventor: Ram Sriharsha

    Abstract: Systems and methods are described for processing ingested data, detecting anomalies in the ingested data, and providing explanations of a possible cause of the detected anomalies as the data is being ingested. For example, a token or field in the ingested data may have an anomalous value. Tokens or fields from another portion of the ingested data can be extracted and analyzed to determine whether there is any correlation between the values of the extracted tokens or fields and the anomalous token or field having an anomalous value. If a correlation is detected, this information can be surfaced to a user.

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