Splunk Inc.

Vmware, Inc.

Nicira, Inc.

Facebook, Inc.

Mayank Agarwal

Justin Pearson Smith

Steven Flanders

Steven Karis

Gergely Danyi

Shashwat Sehgal

Jonathan Dillman

John Branson Bley

Angel Colberg

Maxime Petazzoni

John Bennett Wundes

Scott Stewart

Nicholas Kushmerick

Joshua Walters

Jeremy Olmsted-Thompson

Eric Wohlstadter

Rashmi Kalyani Vasudevan

Rahul Gidwani

David Tagatac

Dmitrii Anoshin

Eyal Maderer

Jayant Jain

Anirban Sengupta

Raju Koganty

Chidambareswaran Raman

Dahlia Malkhi

Srinivas Nimmagadda

Darren Brown

Junyuan Lin

Eric Schkufza

Ramsés V Morales

Dhrubajyoti Borthakur

Haobo Xu

Deep P Desai

Ramses V Morales

Jon Herlocker

Nagavamsi Ponnekanti

Nishant Jain

Udi Wieder

A method of rendering a service graph illustrating dependencies between a frontend and a backend of an application comprises generating a plurality of frontend traces from a plurality of frontend spans and generating a plurality of backend traces from a plurality of backend spans ingested from the application. The method also comprises aggregating frontend metrics data using the plurality of frontend traces and backend metrics data using the plurality of backend traces. The method further comprises determining connection information between one or more frontend traces of the plurality of frontend traces and corresponding backend traces of the plurality of backend traces. The method also comprises rendering the service graph using the connection information and the aggregated frontend and backend metrics data.

Rendering a service graph to illustrate page provider dependencies at an aggregate level

A method of aggregating metrics associated with a user interaction during a real user session comprises identifying a span comprising a tag associated with a workflow from ingested spans associated with the real user session, where the workflow comprises spans generated in response to the user interaction. The method also comprises identifying other spans associated with the workflow from the ingested spans. The method further comprises grouping the other spans associated with the workflow with the tagged span and aggregating metrics for the workflow over a duration of time.

Aggregating metrics for workflows associated with a real user session

A method of persisting and querying Real User Monitoring (RUM) data comprises grouping together spans associated with a user-interaction with a webpage or application that are ingested during a given time duration. The method also comprises generating one or more data sets each associated with an analysis modality using the grouped spans, wherein each analysis modality extracts a different level of detail from the spans. Further, the method comprises selecting, based on a first user query, a first analysis modality for generating a response to the first user query and accessing a data set that is associated with the first analysis modality. The method also comprises generating the response to the first user query using the data set associated with the first analysis modality, wherein the first user query requests information pertaining to a performance of the application in response to the user-interaction.

Multiple modalities of data collection and analysis for real-time monitoring (RUM) in a microservices-based architecture

A method of tracking errors in a system comprising microservices comprises ingesting a plurality of spans generated by the microservices during a given duration of time. The method further comprises consolidating the plurality of spans associated with the given duration of time into a plurality of traces, wherein each trace comprises a subset of the plurality of spans that comprise a common trace identifier. For each trace, the method comprises: a) mapping a respective trace to one or more error stacks computed for the respective trace and to one or more attributes determined for the respective trace; and b) emitting each error stack computed from the respective trace with an associated pair of attributes. The method then comprises reducing duplicate pairs of error stack and associated attributes and maintaining a count for each pair of error stack and associated attributes.

In a microservices-based application, tracking errors by mapping traces to error stacks

Monitoring and troubleshooting tools provide the capability to visualize different levels of a client's application that is deployed as a suite of independent but cooperating services (e.g., an application that includes a monolithic application and a microservices-based application), collect values of monitored or tracked metrics at those different levels, and visualize values of the metrics at those levels. For example, metrics values can be generated for components of the monolithic application and/or for components of a microservice of the microservice-based application.

Generating metrics values at component levels of a monolithic application and of a microservice of a microservices-based architecture

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, wherein an error span is a span that returns an error to a microservice that generates 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.

Displaying error stacks in a graphical user interface (GUI) to track error propagation across microservices-based applications

A method of analyzing a performance of a microservices-based application comprises generating a plurality of traces from a plurality of spans associated with the microservices-based application. The method also comprises generating a plurality of data sets each associated with a respective analysis mode of a plurality of analysis modes using the plurality of traces, wherein each analysis mode extracts a different level of detail for analyzing the performance of the services in the application from the plurality of spans. Further, the method comprises selecting, based on a first user query, a first analysis mode from the plurality of analysis modes for generating a response to the first user query. The method also comprises accessing a data set of the plurality of data sets that is associated with the first analysis mode and generating the response to the first user query using the data set associated with the first analysis mode.

Multiple modes of storing and querying trace data in a microservices-based architecture

A method of rendering a graphical user interface (GUI) comprising an application topology graph for a microservice architecture comprises generating a plurality of traces from a first plurality of spans generated by instrumented services in the architecture and generating generate a second plurality of spans for uninstrumented services using information extracted from the first plurality of spans. The method further comprises grouping the second plurality of spans with the plurality of traces. Subsequently, the method comprises traversing the traces and collecting a plurality of span pairs from the plurality of traces, wherein each pair of the span pairs is associated with a call between two services. The method also comprises aggregating information across the plurality of span pairs to reduce duplicative information associated with multiple occurrences of a same span pair from the plurality of span pairs. Finally, the method comprises rendering the application topology graph using the aggregated information.

Application topology graph for representing uninstrumented objects in a microservices-based architecture

Monitoring and troubleshooting tools provide the capability to visualize different levels of a client's application that is deployed as a suite of independent but cooperating services (e.g., as microservices of a microservices-based architecture), collect values of monitored or tracked metrics at those different levels, and visualize values of the metrics at those levels. For example, metrics values can be generated for teams of the microservices.

Generating metrics values for teams of microservices of a microservices-based architecture

A method of identifying exemplary spans associated with a real user session comprises aggregating ingested spans associated with user interaction with an application during the user session. The method also comprises segmenting the user session into chunks and storing each chunk with an identifier indicating a location of a respective chunk. Further, responsive to user-specified parameters included in a query, the method comprises accessing a chunk using a respective identifier and applying the user-specified parameters to spans in the chunk. Additionally, the method comprises rendering a waterfall visualization comprising exemplary spans associated with the user session, wherein the exemplary spans surface in response to the applying the user-specified parameters to the plurality of spans in the chunk.

Surfacing and displaying exemplary spans from a real user session in response to a query

A method of rendering a service graph responsive to a query comprises generating a plurality of frontend traces and a plurality of backend traces associated with an application or website. The method also comprises determining connection information between one or more frontend traces of the plurality of frontend traces and corresponding backend traces of the plurality of backend traces. Further, the method comprises consolidating the one or more frontend traces with the corresponding backend traces to form one or more end-to-end traces using the connection information. Responsive to the query, the method comprises retrieving a set of exemplary end-to-end traces from the one or more end-to-end traces and rendering a service graph in accordance with constraints applied in the query using the set of exemplary end-to-end traces and the connection information.

Rendering a service graph to illustrate page provider dependencies

Application topology graph for representing instrumented and uninstrumented objects in a microservices-based architecture

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Kirkland, WA, United States of America

Mayank Agarwal