Coming to Azure: Plug-and-Play IoT, Edge Database, Improved AI and Blockchain Support

This week ahead of its Build 2019 developer conference Microsoft announced a number of improvements to its Azure platform that are designed to give developers increased capabilities for Internet of Things (IoT) solutions as well as artificial intelligence (AI), and blockchain projects, via both cloud and edge architectures.

To start, Azure is no longer stopping at the cloud: Microsoft will be releasing Azure SQL Database Edge, which it says will support "the spectrum of edge compute needs...with built-in AI [and] in-database machine learning." An official release date for this (and the rest of the changes in the article) has yet to be announced; more details are expected to be revealed at Build

Another new product will be IoT Plug and Play, an IoT modeling language designed to "seamlessly connect IoT devices to the cloud."

"Previously, software had to be written specifically for the connected device it supported, limiting the scale of IoT deployments," Microsoft explained in an announcement of the new product.

"IoT Plug and Play will offer customers a large ecosystem of partner-certified devices that can connect quickly."

A product Web site for IoT Plug and Play had not yet been launched when this article was published.

Azure's AI and Machine Learning Improvements
Some of the most significant changes AI-related changes are coming to Azure Machine Learning, a cloud-based platform that offers a drag-and-drop interface for prepping, training and deploying machine learning models. According to Microsoft, the machine learning service is being designed to serve three different groups: developers, who want a "code-first" model; business experts, who may prefer a "no-code" model; and IT pros or other nondeveloper techies, who want to use the "drag-and-drop" model. All three models feed into the same back end.

To help improve the interoperability of Azure Machine Learning, next week at its 2019 Microsoft Build conference in Seattle, Wash., the company said it will officially announce the platform's support for the Open Neural Network Exchange, an open cross-platform "ecosystem" for AI models also supported by Amazon Web Services (AWS) and Facebook. The platform also supports ONNX Runtime, which Microsoft made open source in December 2018.

Other improvements announced for Azure Machine Learning include improved Azure DevOps integration, user interface improvements and low-latency improvements, plus support for Nvidia TensorRT and Intel nGraph for programming those manufacturers' high-performance deep learning chipsets.

Microsoft also announced that Azure Search is getting the AI treatment with new "cognitive search" capabilities. The company explained that customers will soon be able to apply Azure Cognitive Services algorithms directly to Azure Search, adding greatly improved business intelligence (BI) and analytics capabilities.

And speaking of Azure Cognitive Services, the company's collection of SDKs, APIs and other tools to help developers without a data science background apply AI solutions in the enterprise, the company also announced this service will get a new category called "decision" (to add to the existing vision, knowledge, language, speech, search and anomaly detection categories). Within decision, developers and data scientists will find (not unsurprisingly) tools for creating applications with better decision-making capabilities, including a "content moderator" and a personalization tool.

Supporting the Blockchain, Plus New Ledgers
Building on the existing Azure Blockchain Workbench, released last year, Microsoft is announcing Azure Blockchain Service (not to be confused with the old Azure Blockchain as a Service product), which it describes as a "fully managed" blockchain service that enterprises can use to support all types of blockchain applications.

"Azure Blockchain Service deploys a fully managed consortium network and offers built-in governance for common management tasks, such as adding new members, setting permissions and authenticating user applications," the company said.

"J.P. Morgan's Ethereum platform, Quorum, is the first ledger available in Azure Blockchain Service, giving Microsoft and J.P. Morgan customers the ability to deploy and manage scalable blockchain networks in the cloud," it continued.

Here's how it will work using Azure DevOps and VS Code:

The ledger is just the foundation for new applications. After configuring the underlying blockchain network with Azure Blockchain Service, you need to codify your business logic using smart contracts. Until now, this has been cumbersome, requiring multiple command-line tools and limited developer IDE integration. Today we are releasing an extension for VS Code to address these issues. This extension allows you to create and compile Ethereum smart contracts, deploy them to either the public chain or a consortium network in Azure Blockchain Service, and manage their code using Azure DevOps.

Once your network is created and smart contract state machines are deployed, you must build an application in order for consortium participants to share business logic and data represented by the smart contracts. A key challenge has been integrating these applications with smart contracts so they either respond to smart contract updates or execute smart contract transactions, connecting business processes managed in other systems (such as databases, CRM, and ERP systems) with the ledger. Our new Azure Blockchain Dev Kit makes this easier than ever with connectors and templates for Logic Apps and Flow as well as integrations with serverless tools like Azure Functions.

Azure's blockchain dev kit is available here, and a preview version of Azure Blockchain Service is expected to be released momentarily.

More information on all of the above announcements is expected next week at Microsoft's Build 2019 developer conference.

About the Author

Becky Nagel is the former editorial director and director of Web for 1105 Media's Converge 360 group, and she now serves as vice president of AI for company, specializing in developing media, events and training for companies around AI and generative AI technology. She's the author of "ChatGPT Prompt 101 Guide for Business Users" and other popular AI resources with a real-world business perspective. She regularly speaks, writes and develops content around AI, generative AI and other business tech. Find her on X/Twitter @beckynagel.