Azure IoT Hub C SDK is written in ANSI C (C99), which makes it well-suited for a variety of platforms with small disk and memory footprint. We recommend at least 64KB of RAM, but the exact memory footprint depends on the protocol used, the number of connections opened, as well as the platform targeted. This blog walks through how to optimize the C SDK for constrained devices.
We release our C SDK as packages on apt-get, NuGet and MBED to accelerate the development process. However, if your system is constrained in ROM or RAM, you may want to build the SDK locally and remove certain features to shrink the footprint of the C SDK. We will be using cmake to demonstrate in this blog. In addition, the programming model for working with constrained devices is different. This blog will also discuss some best practices to reduce memory consumption. There is also official documentation on how to develop for constrained devices available to you.
Building the C SDK for constrained devices
First, you need to prepare your development environment following this guide. When you get to the step for building with cmake, you can invoke flags to remove certain features.
If you followed Microsoft’s coverage from the Build 2018 conference, you may have been as excited as we were about the new Visual Studio Live Share feature that allows instant, remote, peer-to-peer collaboration between Visual Studio users, no matter where they are. One developer could be sitting in a coffee shop and another on a plane with in-flight WiFi, and yet both can collaborate directly on code.
The “networking magic” that enables the Visual Studio team to offer this feature is the Azure Relay, which is a part of the messaging services family along with Azure Service Bus, Azure Event Hubs, and Azure Event Grid. The Relay is, indeed, the oldest of all Azure services, with the earliest public incubation having started exactly 12 years ago today, and it was amongst the handful of original services that launched with the Azure platform in January 2010.
In the meantime, the Relay has learned to speak a fully documented open protocol that can work with any WebSocket client stack, and allows any such client to become a listener for inbound connections from other clients, without needing inbound firewall rules, public IP addresses, or DNS registrations. Since all inbound communication terminates inside the
Today we are excited to announce general availability of soft delete for Azure Storage Blobs! The feature is available in all regions, both public and private.
When turned on, soft delete enables you to save and recover your data where blobs or blob snapshots are deleted. This protection extends to blob data that is erased as the result of an overwrite.
How does it work?
When data is deleted, it transitions to a soft deleted state instead of being permanently erased. When soft delete is on and you overwrite data, a soft deleted snapshot is generated to save the state of the overwritten data. Soft deleted objects are invisible unless explicitly listed. You can configure the amount of time soft deleted data is recoverable before it is permanently expired.
Soft deleted data is grey, while active data is blue. More recently written data appears beneath older data. When B0 is overwritten with B1, a soft deleted snapshot of B0 is generated. When the blob is deleted, the root (B1) also moves into a soft deleted state.
Soft delete is 100 percent backwards compatible; you don’t have to make changes to your applications to take advantage of the protections this
The Internet of Things (IoT) presents many compelling opportunities for developers With the right tools and guidance, it doesn’t need to be intimidating. The conceptual and technical differences between IoT and traditional web and application are relatively easy to grasp. Plus, Microsoft offers a full range of managed services to make it even easier, while enabling you to experiment and scale. If your main skillset is in the Microsoft ecosystem, you can jump right in with Visual Studio Code, .NET, and Azure. If you prefer other languages and tools, our open-source SDKs will enable you to work with Azure solutions while staying in your comfort zone. Either way, you can get started quickly with our Azure IoT developer guide that will take you through common application patterns and tutorials that will have you up and running fast.
The IoT Application pattern
When it comes to knowing where to start, it can help to have a conceptual framework that organizes services and technologies in a logical way. We tend to think of IoT architecture as being divided into three main categories, each of which has considerations distinct from traditional development architectures:
Things: The devices and sensors in the field that are
Data is growing at an astounding rate, with an estimated 2.5 quintillion bytes being created everyday. Data analysts predict that by 2020, the world’s collected data will quadruple. In the sea of all this data, we are continually exploring new ways of analyzing and interpreting data in a way that’s productive, meaningful and insightful.
Designed in collaboration with the original founders of Apache® Spark™, Azure Databricks combines the best of Databricks and Microsoft Azure to help customers accelerate innovation with streamlined workflows, an interactive workspace and one-click set up. Azure Databricks is an analytics engine built for large scale data processing that enables collaboration between data scientists, data engineers and business analysts.
Azure Databricks can be used to run workloads faster and write applications in the language of your choice, whether that’s Scala, SQL, R or Python. When in sync with Azure Databricks, businesses can innovate within the safe, protected cloud environment of Microsoft Azure and benefit from the native integration with other Azure services such as Power BI, Azure SQL Data Warehouse, and Azure Cosmos DB.
When you’re getting started with Apache Spark on Azure Databricks, you’ll have questions that are unique to your businesses implementation and use case.
Unravel on HDInsight enables developers and IT Admins to manage performance, auto scaling & cost optimization better than ever.
We are pleased to announce Unravel on Azure HDInsight Application Platform. Azure HDInsight is a fully-managed open-source big data analytics service for enterprises. You can use popular open-source frameworks (Hadoop, Spark, LLAP, Kafka, HBase, etc.) to cover broad range of scenarios such as ETL, Data Warehousing, Machine Learning, IoT and more. Unravel provides comprehensive application performance management (APM) for these scenarios and more. The application helps customers analyze, optimize, and troubleshoot application performance issues and meet SLAs in a seamless, easy to use, and frictionless manner. Some customers report up to 200 percent more jobs at 50 percent lower cost using Unravel’s tuning capability on HDInsight.
To learn more please join Pranav Rastogi, Program Manager at Microsoft Azure Big Data, and Shivnath Babu, CTO at Unravel, in a webinar on June 13 for how to build fast and reliable big data apps on Azure while keeping cloud expenses within your budget.
How complex is guaranteeing an SLA on a Big Data solution?
The inherent complexity of big data systems, disparate set of tools for monitoring, and lack of expertise in optimizing
https://cloudblogs.microsoft.com/sqlserver/2018/05/29/cloud-data-and-ai-services-training-roundup-may-2018/Source: https://cloudblogs.microsoft.com/sqlserver/2018/05/29/cloud-data-and-ai-services-training-roundup-may-2018/ To help you stay up to date on online training opportunities, were releasing a monthly list of the latest free Data and Artificial Intelligence (AI) sessions in one convenient post. SQL Database Azure SQL Database is READ MORE
This post is authored by Mary Wahl, Data Scientist; Daniel Hartl and Wilson Lee, Senior Software Engineers; Xiaoyong Zhu, Program Manager; Erika Menezes, Software Engineer; and Wee Hyong Tok, Principal Data Scientist Manager, at Microsoft.
AI for Earth puts Microsoft’s cloud and AI tools in the hands of those working to solve global environmental challenges. Land cover mapping is one goal of the AI for Earth program, which was created to fundamentally change the way that society monitors, models, and ultimately manages Earth’s natural resources. The ability to perform ultra-fast land cover mapping using deep neural networks on terabytes of high-resolution aerial images from the National Agriculture Imagery Program (NAIP), provided by our partners at Esri, fuels new intelligent AI applications, delivering quick insights to land cover map users like conservation scientists. In this blog post, we share what we learned from deploying deep neural network models to field-programmable gate array (FPGA) services using Project Brainwave, and applying these FPGA services to perform land cover mapping.
Aerial Imagery Dataset Construction
We developed our benchmarking dataset using ~120 TB of NAIP aerial imagery spanning the continental U.S. at one-meter resolution at multiple timepoints. These data were provided by Esri in
This blog post is authored byBob Ward, Principal Architect, Microsoft; Travis Wright, Principal Program Manager, Microsoft; and Jamie Reding, Senior Program Manager, Microsoft.
A few weeks ago, developers from around the world gathered for the Microsoft Build Conference. It was an amazing display of Microsofts products and cloud services to meet the needs of all types of applications. I missed the //build event this year because I found myself in San Francisco at the Red Hat Summit 2018. I cant even imagine five years ago someone telling me I would represent Microsoft and SQL Server at an open-source based event.
Travis Wright, Jamie Reding, and I travelled to the event to speak and show amazing demos of SQL Server running on Red Hat Enterprise Linux (RHEL) and OpenShift. We were part of the Microsoft team attending the event to continue to show the great partnership we have and are building with Red Hat. Get an overview of the Microsoft presence at the summit from Robin Ginns blog post.
This was not the first time for Travis or Jamie attending this event. Microsoft demonstrated SQL Server on Linux at the Red Hat Summit 2016. Travis and Jamie both presented at the
Did you miss Build Conference this month? We made some big announcements about our marketplace including new features, new functionality, and new services. You can get the quick overview of these announcements in the Azure Marketplace is reaching new audiences blog.
Got a little more time to spare and want to go deeper? Check out some of the key marketplace sessions and content on-demand.
Building Apps and Services for Azure Marketplace and AppSource
Learn what’s new in marketplace and how to leverage the new capabilities and offers types available. Understand the technical roadmap to make the most out of publishing an application or service in Azure Marketplace or AppSource. Building Solution Templates and Managed Applications for the Azure Marketplace
Understand the difference between our storefronts, learn which storefront is right for you, and tools, best practices, and demos on how to develop Azure application’s solution offers. Deliver Compelling Experiences on Microsoft AppSource
Learn how to deliver a compelling experience on Microsoft AppSource. You’ll hear best practices for publishing your app, how to create a Test Drive, and discover how ISVs are achieving success on our platform. Distribute Your Apps to Millions of Users Via AppSource
Learn how to package apps