About Adam Young

Once upon a time I was an Army Officer, but that was long ago. Now I work as a Software Engineer. I climb rocks, play saxophone, and spend way too much time in front of a computer.

Converting a RHEL Workstation to a Server

My laptop is my Demo machine.  I need to be able to run the Red Hat cloud Suite of software on it.  I want to install this software the same way a customer would.  However, much of this software is server side software, and my machine was registered as a workstation. This means the Red Hat Content network won’t show me the server yum repositories.  Here is how I converted my machine to be a server.

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Networking Acronyms

My new role has me paying attention to the Network side of cloud a lot more than I had to in the past. One thing I’ve noticed about Networking is that it has a lot of acronyms, and people that work in it tend to throw them out in context and move on. This is my collection of recent acronyms and their meanings.

I will continue to update this one as I come across additional relevant terms and acronyms.
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Using an Ansible Tower Inventory from Command Line Ansible

In an earlier post, I wrote about using the OpenStack Ansible inventory helper when calling and Ansible command line tools. However, When developing an playbook, often there is more information pulled from the inventory than just the set of hosts. Often, the inventory also collects variables that are used in common across multiple playbooks. For this reason, and many more, I want to be able to call an Ansible playbook or Ad-Hoc command from the command line, but use the inventory as defined by an Ansible Tower instance. It turns out this is fairly simple to do, using the REST API.

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Optimizing R: Replace data.frame with parallel vectors

“First make it work, then make it faster” — Brian Kerningham

However, if the program takes too long to run, it might not be possible to make it correct. Iterative development breaks down when each iteration takes several hours. Some R code I was working with was supposed to run for a 1000 iterations, but with each iteration taking 75 seconds to run, we couldn’t take the time to let it run to completion. The problem was the continued appending of rows to a data.frame object.  Referred to as the Second Circle here. That in turn points to this larger article about problems R programmers find themselves facing. . How does one extricate oneself? Here were my steps.
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