Year: 2018 4 posts
Attaching Kubernetes clusters with NVIDIA V100 GPUs to Azure Machine Learning Service
Azure Machine Learning Service allows you to easily deploy compute for training and inference via a machine learning workspace. Although one of the compute types is Kubernetes, the workspace is a bit picky about the node VM sizes. I wanted to use two Standard_NC6s_v3 instances with NVIDIA Tesla V100 GPUs but that was not allowed.…
Deploying Azure Cognitive Services Containers with IoT Edge
Introduction Azure Cognitive Services is a collection of APIs that make your applications smarter. Some of those APIs are listed below: Vision: image classification, face detection (including emotions), OCR Language: text analytics (e.g. key phrase or sentiment analysis), language detection and translation To use one of the APIs you need to provision it in an…
Deploying Azure resources using webhookd
In the previous blog post, I discussed adding SSL to webhookd. In this post, I will briefly show how to use this solution to deploy Azure resources. To run webhookd, I deployed a small Standard_B1s machine (1GB RAM, 1 vCPU) with a system assigned managed identity. After deployment, information about the managed identity is available…
Using certmagic to add SSL to webhookd
A while ago, I stumbled upon https://github.com/ncarlier/webhookd. It is a simple webhook server, written in Go, that can execute shell scripts. To use it, simply install it on a Linux box and execute it. By default, the executable looks at the ./scripts folder and maps each shell script to a URL you can call. It…
