Microsoft will launch a raft of new features for its Azure Stream Analytics platform in preview next week, though you’ll have to wait at least a few weeks for general availability.

Microsoft pitches Azure Stream Analytics as a platform for quickly developing and deploying complex serverless analytics on data streams.

Top of the list of new features is online scaling, which means users no longer have to stop and restart a Stream Analytics job to change the number of Streaming Units allocated to a job. Streaming units represent the amount of compute resources allocated to a job.

As Microsoft puts it, “This builds on the customer promise of long-running mission-critical pipelines that Stream Analytics offers today.”

Also new is the ability to implement custom deserializers in C#, “which can then be used to de-serialize events received by Azure Stream Analytics.” At the same time, developers can now create Stream Analytics modules that write or reuse custom C# functions and invoke them right in the query through User Defined Functions. Both of these changes will give developers more to play with when dealing with IoT or other edge applications.

Other new features include the ability to debug query steps in Visual Studio, and to carry out local testing on live data in Visual Studio code, and the option of of managed identity authentication via PowerBI.

The public preview of all these features will open on November 4, with general availability coming some weeks later.

Looking a little further ahead, Microsoft has pencilled in a public preview of the ability to analyze ingress data from Event Hubs or IoT Hub on Azure Stack, and egress the results to a blob storage or SQL database  in January 2020. 

And if you like playing secret squirrel, you might like to know the company is soliciting signups for a Private Preview for real time scoring courtesy of Azure Machine Learning. The service will be based on custom pre-trained models managed by Azure Machine Learning, and hosted in either Azure Kubernetes Service or Azure Container Instances. Models can be built with a range of Python libraries, including Scikit-learn, PyTorch, TensorFlow, and trained on platforms, including Azure Databricks, Azure Machine Learning Compute, and HD Insight.

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A new 44-part video series called ‘Python for Beginners’ is being offered on YouTube by Microsoft. The Python series, consisting of three to four minute lessons. are taught by two staff members who love programming and teaching.

But this series of free lessons isn’t really for total beginners. Microsoft assumes that people who sign up have previously done some programming in JavaScript or may have used a visual programing language targeted for kids called ‘Scratch’ which was developed by MIT.

The purpose of this free training is to help infuse ambitions in beginners to build their own machine-learning apps, or applications or even build automated processes on a desktop computer.

To assist students in their training on ‘Pythons for Beginners,’ Microsoft has also provided additional resources which include slides and code samples on a page called GitHub.

Microsoft staff members who are teaching the ‘Python for Beginners’ series are Christopher Harrison, who is a senior program manager at Microsoft, and Susan Ibach, who is one of Microsoft’s AI Gaming unit’s business development manager.

Microsoft has several reasons why it wants more people to know Python which is already very popular and easy to learn. Python has a lot of libraries which assist and allow app developers to interface with Google-developed TensorFlow as well as Microsoft’s Cognitive Toolkit (CNTK) which are both machine-learning frameworks.

Developers can also use VS Code on their local PC in order to edit code stored on other remote machines, or containers, and Windows Subsystem for Linux (WSL) operating systems because Microsoft has built better support for Python in its Visual Studio Code (VS Code) editor.

In Microsoft’s marketplace for developers, the most popular extension is its own Python extension for VS Code and the VS code in itself has become hugely poplar among developers everywhere. Through the company’s distribution

of its popular Anaconda Python, it has made the VS Code available as part of its focus on AI.

Microsoft’s main benefit though for offering free training for Python is to expand  the number of Python developers who would be using Azure in order to build AI apps. Azure Machine Learning Studio already has built-in support for Python and recently last August of this year, Microsoft announced complete Azure Machine Learning support for its PyTorch 1.2  which is a machine-learning framework for Python within Facebook’s AI research team.

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