Prioritizing inclusion—our commitment to building healthy open source communities
Microsoft products and services run on trust, an extension of our commitment to building healthy open source communities.
Microsoft products and services run on trust, an extension of our commitment to building healthy open source communities.
We hear about open source projects every day, but we rarely hear from the people who maintain them. Maintaining an open source project is a full-time, often thankless, job. The Maintainers Spotlight blog series is an opportunity to highlight the essential role maintainers play in moving projects and communities forward.
2020 fundamentally changed how many companies and teams work—seemingly overnight, remote-first cultures became the new norm and people had to change how they communicate and collaborate.
Scikit-learn is one of the most useful libraries for general machine learning in Python. To minimize the cost of deployment and avoid discrepancies, deploying scikit-learn models to production usually leverages Docker containers and pickle, the object serialization module of the Python standard library.
Managing Kubernetes clusters is hard. Managing Kubernetes clusters at scale across a variety of infrastructures is—well—even harder. The Kubernetes community project Cluster API (CAPI) enables users to manage fleets of clusters across multiple infrastructure providers.
Since its open source debut two years ago, ONNX Runtime has seen strong growth with performance improvements, expanded platform and device compatibility, hardware accelerator support, an extension to training acceleration, and more.
In summer 2019, I worked as a high school intern for the ONNX AI team at Microsoft and loved working on various projects with the team, including the BERT text classification model. However, due to Covid-19, the Microsoft Internship Program for high school students was canceled in the summer of 2020.
About two years ago, we heard an increasing demand from the .NET community for an easier way to build big data applications with .NET, outside of needing to learn Scala or Python. Thus, in a collaboration between Azure Data and .NET teams, we started the .NET for Apache® Spark™ open source project.
Overview One of the hallmarks of “the edge” in computing is the array of sensors, controllers, and microcontroller unit (MCU) class devices that produce data and perform actions. For Kubernetes to be a versatile edge computing solution, a cluster needs to easily find these leaf devices.
ONNX Runtime is an open source project that is designed to accelerate machine learning across a wide range of frameworks, operating systems, and hardware platforms. Today, we are excited to announce ONNX Runtime release v1.5 as part of our AI at Scale initiative.
The Java on Microsoft Azure team has been strengthening its commitment and outreach to Java EE users. This effort includes additional technical guidance, tools, scripts, workshops, and more to better support migrations to Virtual Machines, Kubernetes, OpenShift, and managed service (PaaS) offerings.
With the growing trend towards deep learning techniques in AI, there are many investments in accelerating neural network models using GPUs and other specialized hardware. However, many models used in production are still based on traditional machine learning libraries or sometimes a combination of traditional machine learning (ML) and DNNs.
Since Windows worker node support reached general availability in Kubernetes, Microsoft and Tigera have listened closely to feedback from the community. A big contention point of Windows container users in the Kubernetes community is: “One of the most important open source network policy tools in the market is not available for Windows.