Splunk Inc.

Timothy Matthew Robin Williamson

Eric Wohlstadter

Gergely Danyi

Maxime Petazzoni

Sahinaz Safari Sanjani

Sakshi Garg

Charles Smith

Viet Quoc Nguyen

Umang Agarwal

Akila Balasubramanian

Vladimir Sor

Filip Slunecko

Bogdan Cristian Drutu

Donald Passey

Henry Maier

An observability system is disclosed that provides novel techniques for configuring indexable custom tags. The observability system enables customers and users to specify and create indexable custom tags in a flexible and user-friendly manner. The observability system includes a novel custom tag configuration system that enables users of the observability system to configure indexed custom tags. Using a set of user interfaces (e.g., graphical user interfaces (GUIs)), a user is guided through a workflow for configuring indexed custom tags.

Custom indexed tags

A method of computing real-time metrics for automated workflows includes aggregating a set of ingested spans into a set of traces. The method further includes executing a set of rules to determine a set of workflows associated with the set of traces, wherein each workflow of the set of workflows is associated with a respective trace of the set of traces, and wherein each workflow is operable to group together activity associated with a client process within a respective trace. The method also includes assigning a name to each workflow based on the rules and computing real-time metrics for each of the workflows.

Configuring automated workflows for application performance monitoring

Techniques may include receiving a plurality of spans of trace data at a computing system during a first time period. The techniques may include storing the plurality of spans in a span partition of a data store. The data store can contain a plurality of span partitions with spans that are grouped in the partition by trace identifier. The device may include generating a timestamp partition, with an index of timestamps by trace identifiers, for the first time period. The techniques may include storing the timestamp partition in the data store. Also, the techniques may include identifying at least two timestamp partitions that correspond to a second time period that preceded the first time period. The techniques may include generating and storing a primary compacted timestamp partition by combining the at least two timestamp partitions.

Techniques for processing trace data

A method of identifying a root cause of a failure for a trace within a microservices-based application includes determining if a root span of the trace is an error span resulting in an error experienced by a user at a front end of the microservices-based application. If the root span of the trace is an error span, the method analyzes a plurality of spans comprising the trace to determine if the trace comprises at least one leaf error span. If the trace comprises a single leaf error span, the method attributes the root cause of the failure in the trace to a service associated with the single leaf error span. If the trace comprises multiple leaf error spans the method attributes the root cause of the failure in the trace to a service associated with a leaf error span of the multiple leaf error spans comprising a latest starting timestamp.

Identifying the root cause of failure observed in connection to a workflow

Growing community of inventors

Santa Barbara, CA, United States of America

Timothy Matthew Robin Williamson