Splunk Inc.

Zhimin Liang

Blaine Wastell

Matthew Modestino

David Christopher Baldwin

Marc Andre Chéné

Denis Vergnes

Sanjeev Raghavendra Kulkarni

Boyang Peng

Dragoljub Profirovic

Systems and methods are disclosed for processing data associated with isolated execution environments. A chunk of data associated with an isolated execution environment can include log data and non-log data. At least a portion of the log data can include log data generated by the isolated execution environment. The system can parse the chunk of data to identify the log data and the non-log data and extract at least a portion of the log data from the chunk of data. The extracted data can be further processed to generate one or more events.

Log data extraction from data chunks of an isolated execution environment

Systems and methods are described for implementation by a streaming data processing system of a processing pipeline that obtains data items from one or more data sources. The one or more data sources may include multiple partitions of a topic or multiple topics. The one or more data sources are defined by a data pattern, a group of tenants, or a process. The implementation of the processing pipeline can include identifying the one or more data sources to obtain data items. The processing pipeline can include a plurality of processing tasks to obtain the data items. The streaming data processing system can utilize a workload coordinator to dynamically assign particular data sources to particular processing tasks. The implementation of the processing pipeline can further include executing the plurality of processing tasks to cause processing tasks to obtain data items from assigned data sources and process the data items.

Workload coordinator for providing state credentials to processing tasks of a data processing pipeline

This technology is directed to facilitating scalable and secure data collection. In particular, scalability of data collection is enabled in a secure manner by, among other things, abstracting a connector(s) to a pod(s) and/or container(s) that executes separate from other data-collecting functionality. For example, an execution manager can initiate deployment of a collect coordinator on a first pod associated with a first job and deployment of a first connector on a second pod associated with a second job separate from the first job of a container-managed platform. The collect coordinator can provide a data collection task to the first connector deployed on the second pod of the second job. The first connector can then obtain the set of data from the data source and provide the set of data to the collect coordinator for providing the set of data to a remote source.

Enhancing efficiency of data collection using a discover process

Efficient and secure scalable-two-stage data collection

Systems and methods are disclosed for processing location information associated with isolated execution environments and generating metadata for events based on the location information. A system can parse location information of a log file that includes chunks of data associated with an isolated execution environment to identify characteristics of the isolated execution environment. The system can generate events based on the chunks of data and associated the events with metadata generated based on the characteristics of the isolated execution environment.

Generating metadata for events based on parsed location information of data chunks of an isolated execution environment

Extracting machine data generated by an isolated execution environment from a chunk of data generated by an isolated execution environment manager

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Vancouver, Canada

Zhimin Liang