Whether it’s in self-driving vehicles, mixed reality, or smart buildings, the autonomous edge has incredible potential to transform our lives for the better. In this post, we'll review four challenges to a smarter edge, and how to get started with Azure IoT Edge.
We recently announced Cognitive Services running in Docker containers with an initial set of containers ranging from Computer Vision, Face, Text Analytics, and Language Understanding.
Azure IoT Edge is a fully managed service that allows you to deploy Azure and third-party services—edge modules—to run directly on IoT devices, whether they are cloud-connected or offline.
Today, we are announcing the general availability of Azure Stream Analytics (ASA) on IoT Edge, empowering developers to deploy near-real-time analytical intelligence closer to IoT devices, unlocking the full value of device-generated data.
Azure Stream Analytics is Microsoft’s serverless real-time analytics offering for complex event processing. It enables customers to unlock valuable insights and gain a competitive advantage by harnessing the power of big data.
We recently announced the general availability of Azure IoT Edge, allowing you to deploy cloud workloads like AI and machine learning to run directly on your IoT devices.
Today we are excited to announce and highlight several tooling improvements for developers building solutions that are using Azure IoT Edge.
Harvard Business Review, McKinsey, and Gartner all agree: The Internet of Things (IoT) will transform business.
Azure IoT Edge which recently became generally available, designs in security from the ground up with avenues for custom security hardening. Security hardening entails additional security measures for given deployments in response to perceived higher threats like physical accessibility of devices by malicious actors.
Migrate your IoT Edge solution to GA bits today!