Splunk Inc.

Cribl, Inc.

Nicholas Robert Romito

Ledion Bitincka

Alexandros Batsakis

Paul J Lucas

Dritan Bitincka

Sourav Pal

Steve Yu Zhang

Christopher Madden Pride

Alexander Douglas James

David Marquardt

Clint Sharp

Arun Ramani

Karthikeyan Sabhanatarajan

Manu Jose

Ankit Jain

Igor Braylovskiy

Sophia Rui Zhu

Data payloads from an external data storage system are processed in an observability pipeline system. In some aspects, the observability pipeline system defines a leader role and worker roles. The leader role generates a data discovery task based on configuration information for a data collection task. A worker role executes the data discovery task, which includes communicating with an external data storage system to identify a data payload that is stored on the external data storage system and contains event data that meet event filter criteria. The leader role generates data collection tasks based on the data payload. Worker roles execute the data collection tasks. Executing a data collection task includes: communicating with the external data storage system to obtain a subset of filtered event data from the data payload; and streaming the subset of filtered event data to an observability pipeline process.

Processing data payloads from external data storage systems in an observability pipeline system

Embodiments are disclosed for performing cache aware searching. In response to a search query, a first bucket and a second bucket in remote storage for processing the search query. A determination is made that a first file in the first bucket is present in a cache when the search query is received. In response to the search query, a search is performed using the first file based on the determination that the first file is present in the cache when the search query is received, and the search is performed using a second file from the second bucket once the second file is stored in the cache.

Cache aware searching based on files of buckets

Load balancing processes are performed in an observability pipeline system comprising a plurality of computing resources. In some aspects, the observability pipeline system defines a leader role and worker roles. A plurality of computing jobs each include computing tasks associated with event data. The leader role dispatches the computing tasks to the worker roles according to a least in-flight task dispatch criteria, which includes iteratively: identifying an available worker role; identifying one or more incomplete computing jobs; selecting, from the one or more incomplete computing jobs, a computing job that has the least number of in-flight computing tasks currently being executed in the observability pipeline system; identifying a next computing task from the selected computing job; and dispatching the next computing task to the available worker role. The worker roles execute the computing tasks by applying an observability pipeline process to the event data associated with the respective computing task.

Load balancing computing resources in an observability pipeline system

In a general aspect, an observability pipeline system includes a pack data processing engine. In some aspects, an observability pipeline system includes data processing engines that are configured according to system default configuration settings and system local configuration settings. A pack file received from a remote computer system contains routes, pipelines, and pack default configuration settings. A pack data processing engine includes the routes and pipelines from the pack file. Pack local configuration settings, defined for the pack data processing engine, inherit at least one of the system default configuration settings and at least one of the pack default configuration settings. The pack local configuration settings are isolated from the system local configuration settings. When pipeline data is processed in the observability pipeline system on the computer system, the pack data processing engine is applied to the pipeline data.

Pack framework in an observability pipeline system

Embodiments of the present disclosure provide techniques for performing searches of event records by leveraging reference values in an inverted index. A method of searching comprises accessing a query associated with a first set of event records in a field searchable data store, each event record comprising a time-stamped portion of raw machine data. The method further comprises evaluating the query and generating results for the query by accessing an inverted index, wherein each entry in the inverted index comprises at least one field, a corresponding at least one field value and a reference value that identifies a location in the field searchable data store where an associated event record is stored. The method further comprises performing a search to filter out a second set of event records and retrieving the second set of event records from the field searchable data store using reference values in the inverted index.

Retrieving event records from a field searchable data store using references values in inverted indexes

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system parses the query and uses a metadata catalog to dynamically identify configuration parameters of datasets and/or rules associated with the query. The identified configuration parameters are communicated to a query processing component of the data intake and query system for use in executing the query.

Identifying configuration parameters for a query using a metadata catalog

Cache aware searching based on one or more files in remote storage

Embodiments of the present disclosure provide techniques for emitting structured and dynamic fields from an accelerated data model. The method comprises evaluating a query to search a data model, wherein the data model is defined by a set of events and at least one structured field from fields associated with the set of events. Each event comprises a time-stamped portion of raw machine data and is stored in a field searchable data store. A summarization table is associated with the data model and comprises a plurality of entries comprising reference values, wherein a respective summarization table entry comprises: the at least one structured field; a respective field value; and a reference value. The method further comprises accessing the set of events from the field searchable data store using the reference values in the summarization table and annotating the set of events with the at least one structured field and with at least one dynamic field from the fields associated with the set of events, wherein the at least one dynamic field is not defined in the data model.

Optimizing search of an accelerated data model by enabling emitting of structured and unstructured fields from the data model

Leveraging references values in inverted indexes to retrieve associated event records comprising raw machine data

Cache aware searching based on one or more files in one or more buckets in remote storage

Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives a first query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system parses the first query and uses a dataset association records of a metadata catalog to dynamically identify one or more datasets associated with the query and generate a second query. The data intake and query system executes the second query.

Query generation using a dataset association record of a metadata catalog

Embodiments are disclosed for a prefetching method that may include copying, in response to a search query, a first bucket from a remote storage to a cache. The first bucket may include first data associated with the search query. The method may further include identifying a first file type associated with a first file in the first bucket. The first file may be associated with a usage status. The method may further include accessing, based on the search query, a second bucket from the remote storage. The second bucket may include second data associated with the search query. The method may further include identifying a second file in the second bucket having the first file type, and copying, in response to the usage status indicating that the first file was used in processing the search query, the second file from the remote storage to the cache.

Growing community of inventors

San Francisco, CA, United States of America

Nicholas Robert Romito