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Samuel Thurston, Software Engineer

Samuel Thurston, Software Engineer
Samuel Thurston is a Software Engineer and Cloud Practice Lead for ISE, architecting and implementing cloud solutions for enterprise clients. He enjoys running, yoga, and cooking, and is frequently found on the disc golf course.

Recent Posts

FaaS: Function as a Service

Sep 28, 2018 | by Samuel Thurston, Software Engineer | Tags: Cloud

Serverless has been a buzzing topic in the cloud community for quite some time now, and with good reason:  serverless is great for managing cloud costs and utilization, deploying quickly, and scaling on-demand.  While I’ve touched on some serverless elements before, today we’re going to talk about the backbone of serverless computing: Function as a Service or FaaS.

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Networking is Hard

Aug 23, 2018 | by Samuel Thurston, Software Engineer | Tags: Cloud

It’s back to school season, and for me that meant helping my eldest daughter move into her first apartment with roommates and … cable internet.  Few industries garner as much universal hatred as residential Internet service providers (ISPs).  The previous residents, in their well-earned distrust of the local provider, told her that it would be much cheaper to purchase her own modem and router than to lease.  And so, she bought reasonably-priced (translation: the cheapest) models from Amazon.  

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Observability in Distributed Systems

Jul 19, 2018 | by Samuel Thurston, Software Engineer | Tags: Cloud

Whether you’re working with a single-instance application or a complex deployment of dozens of orchestrated microservices, it is important to know that the code is working the way it should, and how people and outside systems are interacting with it. I’ve written before about instrumentation of applications and even showed a toy example using amazon X-Ray, but I thought I should devote some space to observability and why it is important.

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Hands-On With Amazon AWS DeepLens

Jun 21, 2018 | by Samuel Thurston, Software Engineer | Tags: Cloud

I recently received my AWS DeepLens device.  I’m by no means a machine learning expert.  However, Andy Jassy’s announcement of the device at 2017’s AWS re:Invent implied that the DeepLens would put Machine Learning and Computer Vision in the hands of non-experts and make it easy.  So, let’s try out one of AWS’s pre-trained samples to see just how easy this device is to use.

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