Steve Michelotti and I presented a session on AzureGov last week at Microsoft Ignite 2017 in Orlando. It focused on demonstrating the innovative capabilities in AzureGov that are specifically designed to help government agencies with their mission. We dedicated about 80% of the session to live demos.

Steve started out with a brief description of AzureGov and how to get started…along with some recent news announcements, including API Management and Key Vault. Steve then quickly transitioned into demos related to Cognitive Services, Azure IOT and Power BI. I conducted two demos related to Cosmos DB Graph database and the CNTK deep learning algorithm on an N Series GPU machine.

Please watch the video below and let us know if you have any questions.

The rapid growth of the Internet of Things (IoT) is certainly exciting for government agencies, but it also brings many challenges (namely security and devising a clear strategy for integrating a still-evolving technology).

Last night’s #AzureGov meetup was a great evening of networking, demos, use cases and best practices for government agencies looking to quickly and securely deploy IoT.

Last night featured two speakers from Docker Public SectorChris Cyrus, vice president, and Andrew Weiss, lead engineer  –  who joined the Microsoft Azure Government team to discuss how containers are changing the way software is built and procured in government. They presented demos of Docker Containers deploying IoT in the cloud and gave insights into best practices and customer use cases for government IoT.

In case you missed it, @aisteam was there and livestreamed the event. (Videos below.) Read More…

When you read about the Internet of Things, you often hear about connected cars, connected kitchen appliances, small devices that let you order things quickly, or other consumer-grade applications. In this post, I will quickly describe a recent IoT project I worked on where the devices are not small consumer-grade sensors…they are large industrial manufacturing machines.

In this case, machines arranged on a shop floor are responsible for cutting metal into various shapes. These machines must be both very powerful and very precise, and they have robotic arms that are programmed to grip specialized tools for this activity. These machines use the MT Connect protocol as the language for communicating their operational status and the results of any action taken. On collection, the data is streamed to a collection point for analysis. In older machines, adapters are installed to stream the machine’s data using the common language.

Our work on this project helped the engineers identify optimal cut times by analyzing the machine activity data. First, we needed to enhance the collection process so that all data was readily available, then apply the appropriate business rules to identify cut time, and finally provide quick, actionable feedback on the outcome. Read More…