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Lucas Caballero, 474870 Meredith Way, Boulder, CO 80303

Lucas Caballero Phones & Addresses

4870 Meredith Way, Boulder, CO 80303    303-9888708   

7852 Mansfield Ave, Lakewood, CO 80235    303-9888708   

3481 Fenton St, Denver, CO 80227    303-9888708   

Arvada, CO   

5250 Huron St, Littleton, CO 80120    720-2837812   

Mentions for Lucas Caballero

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Lucas Caballero Photo 1

Platform Engineer

3195 Sterling Cir, Boulder, CO 80301
Information Technology And Services
Wall Street On Demand - Boulder, Colorado since Mar 2008
Web Developer, Sr Web Developer, Library Architect, Web Capabilities Coordinator
Indigio 2008 - 2009
Web Developer
Metropolitan State College of Denver 2002 - 2008
Jquery, Integration, Cms, Javascript, Ajax, C#, Web Development, Css, Json, Web Applications, Blogging, User Interface, Git, Distributed Systems, Xml, Cascading Style Sheets, Node, Express, Coffeescript, Npm, Zmq, Tmux, Zsh, Unix, Intellij, Emacs, Html5, Java, Agile Methodologies, Software Development, Go, Elasticsearch, Html, Node.js, Linux
Lucas Caballero Photo 2

Lucas Caballero

Lucas Caballero Photo 3

Lucas Caballero


Us Patents

Systems, Methods, Computing Platforms, And Storage Media For Administering A Distributed Edge Computing System Utilizing An Adaptive Edge Engine

US Patent:
2021029, Sep 23, 2021
Mar 19, 2021
Appl. No.:
- Boulder CO, US
Kurt Rinehart - Boulder CO, US
Matthew Wickman - Arvada CO, US
Gary Ritzer - Longmont CO, US
Lucas Caballero - Broomfield CO, US
Glenn Slaven - Berridale, AU
Jason Stangroome - Wamberal, AU
Pavel Nikolov - Homebush West, AU
Ivan Hamilton - Cumberland Reach, AU
Calvin John Brewer - Centennial CO, US
International Classification:
H04L 12/803
H04L 12/853
H04L 12/801
H04L 12/815
Systems, methods, computing platforms, and storage media for administering a distributed edge computing system utilizing an adaptive edge engine based on a finite state machine behavioral model are disclosed. Exemplary implementations may: select a first workload from one or more workloads; access, for the selected workload, one or more location optimization strategies from a plurality of location optimization strategies; and optimize an objective function across a portion of the one or more endpoints; select one or more endpoints; deploy the workload on at least one selected endpoint; monitor the health of the endpoint-workload deployment; and direct network traffic to the appropriate endpoint.

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