Internet of things

The Azure Sphere 19.02 release is available today.

Built-in machine learning models for anomaly detection in Azure Stream Analytics significantly reduces the complexity and costs associated with building and training machine learning models. This feature is now available for public preview worldwide.

Customers love Azure Stream Analytics for its ease of analyzing streams of data in movement, with the ability to set up a running pipeline within five minutes.

The IT industry is experiencing a shift from monolithic applications to microservices-based architectures.

Connectivity is often the first challenge in the Internet of Things (IoT) world, that’s why more than three years ago we released Azure IoT SDKs.

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.

Analytics in Azure is up to 14x faster and costs 94% less than other cloud providers; Announcing updates to 3 great Azure Data services; Azure Cost Management now GA for EA customers; and more.

With Azure DevOps Projects we want to make it is easy for you to set up a fully functional DevOps pipeline tailored to the development language and application platform you want to leverage.

Many of the conveniences we enjoy today are dependent on the infrastructure cities and municipalities provide, such as water mains, streetlights, and roads. This infrastructure and its associated technology support our transportation systems, schools, hospitals, and more.

Azure IoT Edge is supported on virtual machines, allowing customers to leverage existing infrastructure as part of a solution which spans the intelligent edge and intelligent cloud.

Our goal in the Azure Stream Analytics team is to empower developers and make it incredibly easy to leverage the power of Azure to analyze big data in real-time.

This week, at The Things Conference in Amsterdam, Microsoft and The Things Network Foundation collaborate with 2,000 LoRaWAN developers, innovators, and integrators on connecting devices to Azure IoT Central using the open source project Azure IoT Central Device Bridge.