In January this year, we launched Applied Cloud Stories initiative - a call for new content created by independent community members, focusing on practical stories about scenarios and workloads that can run on Azure.
Over the last couple of months, we were fortunate to receive a number of outstanding community stories. Many of them shared lessons learned, trade-offs, tips and tricks, and valuable experience. We are grateful for every single story we received from you!
We are absolutely delighted to share the winners of Applied Cloud Stories initiative!
"Over the last few years IoT devices and ML/AI have become very popular, and now a lot of companies are moving forward to use them in production. All cloud providers, including Microsoft Azure, provides services how to deploy developed machine learning algorithms to the edge device. The main concern of some industries (automotive, agriculture, etc.) is that in production the cost for data transfer, out of the total cost of ownership, will be huge."
"Let's take a look at how Azure ML IoT works and when reducing the data transfer matters."
The reviewers highlighted that the author does a superb work with using different technologies on Azure and applying them to solve a real technical challenge and a business problem. The fact that he demonstrates how to reduce the size for the Docker image layers, which need to be transferred to the IoT device is very unique and has a visible business impact: the cost of the update of the model in production decreases exponentially and other developers and data scientists can leverage this lesson to operationalize their IoT solutions while maintaining costs low.
"How to find an automated and easy way to create a non-production environment?"
"In most cases, the ongoing situation is that developers are sharing VMs with the needed applications, or they use their own workstation. While this works, it is far from ideal. I found a solution, using PowerShell, ARM Templates and Azure Serverless services. In this post I want to talk about how to deploy a test environment with a calendar appointment."
Our reviewers found the idea and the concept described in the article to be interesting and original! They appreciated that the author technically shows how to use "unexpected" APIs integrations to trigger various cloud actions.
"CloudSkew's infrastructure has been built on top of various Azure services - snapped together like lego blocks."
"Deep-dive on CloudSkew's building blocks discussing the lessons learnt, key decisions & trade offs made."
The reviewers noted the wide spectrum of topics and technologies covered in this amazing article. Incredible covering of monitoring and incident management, things like manual approvals, and many more. The author also focused on technology choices and tradeoffs, such as PaaS vs Kubernetes.
"This story shows how we used Azure Notebooks for providing an interactive learning experience in class."
The reviewers agreed the story is a nice use case for academic audiences. It shows how easy is it to use Azure to teach students.
Congratulations to authors of the winning stories!
Over the next days, we will be reaching out to the winners and to authors of submission that Applied Cloud Stories Committee chose to feature.
We look forward to publishing winning and featured stories on Microsoft content properties and sharing with you very soon! We are incredibly grateful for hearing all the amazing community stories.