Personal blog of Yzmir Ramirez

Microsoft didn’t rush to bring blockchain technology to its Azure cloud computing platform, but over the course of the last year, it started to pick up the pace with the launch of its blockchain development kit and the Azure Blockchain Workbench. Today, ahead of its Build developer conference, it is going a step further by launching Azure Blockchain Services, a fully managed service that allows for the formation, management and governance of consortium blockchain networks.

We’re not talking cryptocurrencies here, though. This is an enterprise service that is meant to help businesses build applications on top of blockchain technology. It is integrated with Azure Active Directory and offers tools for adding new members, setting permissions and monitoring network health and activity.

The first support ledger is J.P. Morgan’s Quorum. “Because it’s built on the popular Ethereum protocol, which has the world’s largest blockchain developer community, Quorum is a natural choice,” Azure CTO Mark Russinovich writes in today’s announcement. “It integrates with a rich set of open-source tools while also supporting confidential transactions—something our enterprise customers require.” To launch this integration, Microsoft partnered closely with J.P. Morgan.

The managed service is only one part of this package, though. Microsoft also today launched an extension to Visual Studio Code to help developers create smart contracts. The extension allows Visual Studio Code users to create and compiled Etherium smart contracts and deploy them other on the public chain or on a consortium network in Azure Blockchain Service. The code is then managed by Azure DevOps.

Building applications for these smart contracts is also going to get easier thanks to integrations with Logic Apps and Flow, Microsoft’s two workflow integration services, as well as Azure Functions for event-driven development.

Microsoft, of course, isn’t the first of the big companies to get into this game. IBM, especially, made a big push for blockchain adoption in recent years and AWS, too, is now getting into the game after mostly ignoring this technology before. Indeed, AWS opened up its own managed blockchain service only two days ago.

Microsoft today announced three new services that all aim to simplify the process of machine learning. These range from a new interface for a tool that completely automates the process of creating models, to a new no-code visual interface for building, training and deploying models, all the way to hosted Jupyter-style notebooks for advanced users.

Getting started with machine learning is hard. Even to run the most basic of experiments take a good amount of expertise. All of these new tools great simplify this process by hiding away the code or giving those who want to write their own code a pre-configured platform for doing so.

The new interface for Azure’s automated machine learning tool makes creating a model as easy importing a data set and then telling the service which value to predict. Users don’t need to write a single line of code, while in the backend, this updated version now supports a number of new algorithms and optimizations that should result in more accurate models. While most of this is automated, Microsoft stresses that the service provides “complete transparency into algorithms, so developers and data scientists can manually override and control the process.”

For those who want a bit more control from the get-go, Microsoft also today launched a visual interface for its Azure Machine Learning service into preview that will allow developers to build, train and deploy machine learning models without having to touch any code.

This tool, the Azure Machine Learning visual interface looks suspiciously like the existing Azure ML Studio, Microsoft’s first stab at building a visual machine learning tool. Indeed, the two services look identical. The company never really pushed this service, though, and almost seemed to have forgotten about it despite that fact that it always seemed like a really useful tool for getting started with machine learning.

Microsoft says that this new version combines the best of Azure ML Studio with the Azure Machine Learning service. In practice, this means that while the interface is almost identical, the Azure Machine Learning visual interface extends what was possible with ML Studio by running on top of the Azure Machine Learning service and adding that services’ security, deployment and lifecycle management capabilities.

The service provides an easy interface for cleaning up your data, training models with the help of different algorithms, evaluating them and, finally, putting them into production.

While these first two services clearly target novices, the new hosted notebooks in Azure Machine Learning are clearly geared toward the more experiences machine learning practitioner. The notebooks come pre-packaged with support for the Azure Machine Learning Python SDK and run in what the company describes as a “secure, enterprise-ready environment.” While using these notebooks isn’t trivial either, this new feature allows developers to quickly get started without the hassle of setting up a new development environment with all the necessary cloud resources.