Crowdstrike, Inc.

Code 42 Software, Inc.

Christopher Gwinn

David Frederick Diehl

Thomas Johann Essebier

Matthew Edward Noonan

Nora Lillian Sandler

Peter John Lindquist

Brian Bispala

Matthew Dornquast

Justin Grammens

Samuel Schroeder

Thomas (Tony) Lindquist

A distributed security system can include instances of a compute engine that can execute either locally in security agents on client devices or as cloud instances in a security network. Event data can be processed by elements of the distributed security system according to centrally-defined ontological definitions and/or configurations. Bounding managers of local security agents can control how much event data is sent to the security network. A storage engine in the security network can store event data received from client devices, can route event data to other elements of the security network, including cloud instances of the compute engine. An experimentation engine of the security network can also at least temporarily adjust other elements of the distributed security system during experiments or tests.

Distributed digital security system

Disclosed in some examples are predictive storage techniques for use in a distributed data system. The predictive storage techniques may be used to manage locally stored elements of a shared data collection, such as the storage of files on nodes of the distributed data system that are limited in local storage space. The predictive storage techniques may achieve a balance between consumption of local resources and timely access of important elements in the shared data collection. For example, the predictive storage techniques may be used for keeping or pre-caching certain items of a collection that are determined as likely to be used in local storage for convenient access, and allowing access the remaining items on request over a network.

Shared file system predictive storage techniques

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Minneapolis, MN, United States of America

Christopher Gwinn