Ansible Tower Upgrade – Quick Note on EC2 Sizing

by Matthew KimlerNo Comments
Last week I started on a personal project to get Ansible Tower upgraded in our lab. Our Tower deployment actually runs in AWS as an EC2 instance with some EBS backed storage. It's a simple and common setup for folks that are running Tower. There wasn't much excitement with this upgrade from 3.1 to 3.4 except for one minor hiccup. We typically run lean and mean in the lab, using only what we really need to use resource-wise. The AWS instance for Tower is a m3.medium which gives a single vCPU and 3.75 GB of RAM. Ansible Tower requires 2 GB RAM minimum but has a recommended size of 4 GB RAM. Thus, the m3.medium seems to the most ideal EC2 instance type of this type of testing workload. While the original 3.1 deployment had no issues with the m3.medium, the upgrade failed several times and quit reporting the following error: TASK [preflight : Preflight check - Fail if this machine lacks sufficient...
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Liliana and the Family

by Matthew Kimler Comment Closed
Again, another long delay in getting updates out about the family. I really need to get better at this. The big news was the birth of daughter Liliana. She's happy and healthy and as I write this, is now just over four months old. Recently, it's been about rolling over and trying to get some forward motion going. Overall though, it's more like barrel rolling. The only downside is that she hates being on her stomach at night sometimes, and that makes for horrible sleep for Mommy and Daddy. There's the little one at three months. Big eyes like her Dad. With some luck, she won't have my stare down eyes look. On the Jameson side of the house, he'll be starting Little Kickers. We just did our first trial and we think he really enjoyed it. It was quite fun to watch him engage with the class and do some of the exercises. I think it's still a bit of a...
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Getting Started with NVIDIA Containers and DIGITS

by Matthew KimlerNo Comments
For the GTC 2019 conference, IAS wanted to put together something to demonstrate the value of NVIDIA's DGX platform for artificial intelligence and machine learning. I've never actually done anything like this before and so I welcomed the opportunity to get my hands on the DGX Station and learning how to unleash the power of Tesla V100 cards. I'm far from building SkyNet, but it only took a few days to get the hang of everything and get something rolling. To help others on this journey, I'm going to outline the process I used to get the DGX Station running a DIGITS docker container, download the MNIST data set, and do the basic test of DIGITS with some image classification. This is not the only way to accomplish this and this way might be a little "dirty", but it worked and the results were there. Thus, take this as a guide and move on from there. In our lab, everything is...
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