Splunk Inc.

Shyam Mundhra

Steve Yu Zhang

Alexander Douglas James

Arun Ramani

Joseph Gabriel Echeverria

Poornima Devaraj

Venkata SreeKrishna Koganti

Ryan Konrad Yee

Xiangyu Wu

Hardik Shah

Thor Taylor

Manikandan Vellore Muneeswaran

Systems and methods are described herein for synthesizing traces from logs of a distributed computing system. A trace represents a single transaction, such as handling of a user request, on the distributed computing system. The transaction can include multiple underlying operations on the distributed computing system, which are represented as spans within the trace and may be hierarchically arranged within the trace. In instances where a distributed computing system does not provide for tracing natively, a trace can be synthesized from log entries of the distributed computing system. A streaming data processing system can ingest a data stream including log entries, and identify within the data stream those log entries relating to a given transaction. The streaming data processing system can further identify log entries that demark the beginnings and endings of operations for that transaction, and can utilize the identified log entries to build a trace for the transaction.

Streaming synthesis of distributed traces from machine logs

Systems and methods for rule-based data stream processing by data collection, indexing, and visualization systems. An example method includes: receiving, by the computer system, an input data stream comprising raw machine data; processing the raw machine data by a data processing pipeline that produces transformed machine data, wherein the data processing pipeline comprises an ordered plurality of pipeline stages, wherein a pipeline stage of the ordered plurality of pipeline stages applies a rule of a set of rules to an input of the pipeline stage, wherein the rule specifies an action to be performed on the input of the pipeline stage responsive to evaluating a conditional expression applied to the input of the pipeline stage, wherein the action generates an output of the pipeline stage, and wherein the rule is selected based on a source type associated with the input data stream; and supplying the transformed machine data to a data collection, indexing, and visualization system.

Rule-based data stream processing

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Pleasanton, CA, United States of America

Shyam Mundhra