UPDATED 20:30 EDT / MAY 28 2021

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Microsoft empowers developer productivity with new tools and services

While developers have always played a pivotal role in business innovation, this position came to prominence recently when they drove companies’ response to the pandemic – whether it was developing solutions from a medical standpoint, supporting call centers and online retail, or improving systems to enable working-from-home and homeschooling.

Creating tools and services that facilitate the work of developers and boost their productivity in the container environment, which is increasingly being adopted by DevOps, is one of the main goals of Microsoft’s collaboration with Docker Inc. and GitHub Inc., according to to  Amanda Silver (pictured), corporate vice president of developer tools at Microsoft.

“What we want to do is make sure that we’re empowering developers that we’re focused on their productivity and that we’re delivering value to them so they can do their job better, so that they can help others,” she said. “[In] the developer division specifically, we really try to make sure that we’re improving the state of the art for modern developers.”

Silver spoke with John Furrier, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during DockerCon. They discussed Microsoft’s initiatives to simplify containers for developers, the challenges around microservice programmability, and the role of machine learning in this landscape. (* Disclosure below.)

Enabling microservice programmability

Containers have brought incredible productivity in terms of repeatable environments for developers and, of course, production and testing, but they have also posed some challenges. One is that it came with the microservice architecture, according to Silver.

“What happens when you start to have many microservices working together in a SaaS or in some kind of aggregate service environment or kind of application environment is it starts to get unwieldy,” she explained. “It’s really hard to make it so that one microservice can actually address another microservice and they could pass information back and forth.”

What used to be easier if you were just building a client-server application – because within the server all of the code was basically contained in the same runtime environment — is no longer the case, according to Silver, as each microservice is actually running inside of its own container.

“So, the question is ‘how can we improve programmability by making it easier for one microservice that’s being used in an application environment to be able to access another service and kind of all of that context?’” Silver said. “And so, you want to be able to access the services, the API endpoint, that containers, the ingresses, make everything work together as though it felt just as easy as a server application development.”

Another challenge is that teams often need to get all of the different containers running at the same time, and this can be a problem for the developer and the test loop. With that in mind, Microsoft created Project Tye, which is an open-source experimental developer tool that makes developing, testing and deploying microservices and distributed applications easier.

“What Project Tye does is it improves the programmability and it actually allows you to just write a command … so that you can actually instantiate all of these containers, get them up and running, and basically deploy it and run your application on that environment,” she said. “Ultimately, [it] makes the dev test inner loop much faster.”

Bringing devs and machine learning together

Microsoft is also enabling resources for the use of machine learning in the development environment. The company now allows developers to train machine learning models using the Visual Studio Code Tools for AI extension and Azure Machine Learning service.

The number of machine learning developers in the world is relatively small, but it is growing, according to Silver. “And it’s obviously a very important set of developers because to train … an ML model, actually requires a significant amount of compute resources,” she added.

What is different about this particular developer stack is that it usually runs on systems like Python.

“And for those of you who have developed in Python, you know just how difficult it is to actually set up a Python environment with the right interpreter, with the right run time, with the right libraries that can actually get going super quickly and you can be productive as a developer,” Silver pointed out.

The Azure Machine Learning Visual Studio Code Extension is designed exactly to solve this issue.

“This allows you to become a machine learning developer without having to spend all of your time just setting up the Python runtime environment,” she explained.

With these innovations, Microsoft wants to ensure that Azure is the most useful cloud for developers.

“We have to make sure that we’re building fantastic tools and platforms to host Java applications, JavaScript applications, no JS applications, Python applications, all of those things,” Silver concluded.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of DockerCon. (* Disclosure: Microsoft sponsored this segment of theCUBE. Neither Microsoft nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE

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