Splunk Inc.

Omprakaash Thoppai

Subramaniam Baskaran

Tristan Antonio Fletcher

Sakib Mehasanewala

Michael Margulis

Marc Andre Chene

Joel Schoenberg

Syam Bollu

Yogesh Sontakke

Esha Desai

Rehan Mulla

Satya Venkata Bharani Suresh Vasabhaktula

Anudeep Rentala

Systems and methods ingest machine data including logs, metadata, and cost and usage information from multiple heterogeneous cloud services. The machine data is saved as events. An application retrieves the metadata, events, metrics, and logs and causes an easy to understand visual representation of costs, resource usage, and non-compliance for each of a client's cloud services. Further, the data across the client's multiple heterogeneous cloud services is normalized to provide visual representations that compare the costs, resource usage, and non-compliance across the client's multiple heterogeneous cloud services. Further, machine learning aspects of the application can provide recommendations and trend analysis for cloud service asset usage.

Networked cloud service monitoring

Techniques are described for providing a cloud data collector (CDC) application for managing the generation of infrastructure templates. The CDC application provides graphical user interfaces that enable a user to provide inputs indicating configurations of data to be ingested by the data intake and query system, each configuration including one or more user accounts, in addition to data sources and regions associated with data sources. Using the configurations provided as input to the CDC application, the CDC application generates an infrastructure template that can be used to configure the service provider network to provide the requested security data to the data intake and query system.

Generating infrastructure templates for facilitating the transmission of user data into a data intake and query system

A computer implemented method includes establishing, by a data intake and query system, a network connection between the data intake and query system and an application and infrastructure monitoring platform. The data intake and query system receives a data stream from the application and infrastructure monitoring platform. The computer implemented method further includes transforming the data stream while receiving the data stream to obtain a transformed data stream. Further, the transformed data stream is analyzed while receiving the data stream to generate analysis results, which are presented.

Monitoring platform job integration in computer analytics system

An example method includes collecting, at a computing system of a data intake and query system, source data corresponding to an instance of a service hosted by a service provider, wherein the service provider hosts the service on a network of the service provider, identifying in the source data a set of metrics for the instance of the service, applying a machine learning model to the set of metrics to determine a classification for the set of metrics, generating, using the classification, a recommendation, wherein the recommendation relates to usage by the instance of the service of one or more physical resources of the service provider, and transmitting, for receipt by a client device, data comprising the recommendation, wherein the data enables display on the client device of a visualization comprising the recommendation.

Service provider instance recommendations using machine-learned classifications and reconciliation

Information technology networked cloud service monitoring

Workflows for configuring the ingestion of user data from a service provider network into a data intake and query system

Integration in computer analytics system

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San Jose, CA, United States of America

Omprakaash Thoppai