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.
Modern analytics and the resulting business insights unlock new opportunities to optimize company performance and open new revenue streams. Since these initiatives also heighten the need for greater security and governance of company data, Identity and Access Management (IAM) needs to be a foundational component of any corporate security plan that covers company data.
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.
Introduction Over the last few years IoT devices, machine learning (ML), and artificial intelligence (AI) have become very popular and now a lot of companies are moving forward to use them in production. All cloud providers, including Microsoft Azure, provide services on how to deploy developed ML algorithms to edge devices.
From startups to the global 2000, Elastic powers search solutions for thousands of companies worldwide to find documents, monitor infrastructure, protect against security threats, and more. With Elastic Cloud managed services on Azure, you have the power of Elastic Enterprise Search, Elastic Observability, and Elastic Security.
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.
There’s a popular saying that reads “Any application that can be written in JavaScript will eventually be written in JavaScript.” Known as Atwood’s Law, it highlights the flexibility of the language: JavaScript is already everywhere and its popularity only continues to grow.
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.
J4K is a developer-oriented conference focused on open source and hybrid cloud application development of Java and Kubernetes. This is a community event, delivered by stellar Java community leaders, and is dedicated to enriching developers and architects with cloud-focused solutions. Registration is free.
