Improving the TypeScript support in Azure Functions
TypeScript is becoming increasingly popular in the JavaScript community.
Internet of things
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Microsoft and SAP extend partnership to Internet of Things
The Internet of Things (IoT) is becoming mainstream. -
MWC 2019: Azure IoT customers, partners accelerate innovation from cloud to edge
The Internet of Things (IoT) has expanded the world of computing far beyond mobile and PC, bringing a new and ever-growing class of cloud-connected devices that is on track to reach 20 billion devices by 2020. -
Azure.Source – Volume 71
Catch up on Azure – Preview: Distributed tracing support for IoT Hub; Update to Azure DevOps Projects support for Azure Kubernetes Service; More reliable event-driven applications in Azure with an updated Event Grid; and more. -
Announcing Azure Spatial Anchors for collaborative, cross-platform mixed reality apps
It’s amazing to look back at everything we’ve learned from our customers since we first released HoloLens. -
Announcing the general availability of Java support in Azure Functions
Azure Functions provides a productive programming model based on triggers and bindings for accelerated development and serverless hosting of event-driven applications. -
Preview: Distributed tracing support for IoT Hub
Most IoT solutions, including our Azure IoT reference architecture, use several different services. -
More reliable event-driven applications in Azure with an updated Event Grid
We have been incredibly excited to be a part of the rise of event-driven programming as a core building block for cloud application architecture. -
Azure.Source – Volume 70
Actuating Mobility in the Enterprise with New Azure Maps Services and SDKs; Under the hood: Performance, scale, security for cloud analytics with ADLS Gen2; Moving your Azure Virtual Machines has never been easier; and more! -
Update 19.02 for Azure Sphere public preview now available
The Azure Sphere 19.02 release is available today. -
Anomaly detection using built-in machine learning models in Azure Stream Analytics
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. -
Maximize throughput with repartitioning in Azure Stream Analytics
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.
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