The event-driven promise is helping developers light up new product ideas quickly! Using Azure Functions and event-driven best practices, developers are now able to build in days what usually used to take weeks in the on-premises world. Join us to learn how to enhance your existing cloud applications using serverless technologies and event-driven design patterns. We will share learnings gathered from customers running Functions apps at scale and talk about common pitfalls to avoid.
Democratizing data empowers customers by enabling more and more users to gain value from data through self-service analytics. Processing raw data for building apps and gaining deeper insights is one of the critical tasks when building your modern data warehouse architecture. In this session, we will show you how to build data pipelines with Spark and your favorite .NET programming language (C#, F#) using both Azure HDInsight and Azure Databricks, and connect them to Azure SQL Data Warehouse for reporting and consumption.
If you build SaaS applications that manage multiple customers, this session is for you! Power BI Embedded engineering team will help you weigh the different options across several important evaluation criteria and share design best practices for choosing the tenancy model that best fits your needs.
Build a resilient application by leaning on the distributed nature of the cloud. Join this session and learn about 5 different resilient application patterns in Azure. See demos and learn what factors you should consider as you use them. We will share, at the architectural level, how resilient application patterns are designed to reduce different types of failures and achieve high availability, disaster recovery and restoring data. Time for Q&A is built in!
From smart sensors and actuating devices to integrated robotic systems, industrial organizations are employing increasingly sophisticated automation technologies to drive efficiency and productivity. Microsoft is accelerating the journey toward a world where machines operate in more dynamic and intuitive ways. From smart buildings, to industrial machinery, to robotics, Microsoft is democratizing the development of increasingly autonomous systems by providing domain experts, developers, and data scientists with the tools they need to seamlessly develop and manage autonomous systems.
The holy grail of the Internet of Things is the ability to easily distribute the intelligence of your application across the Cloud and the Edge. Being able to run analytics, AI or store data at the Edge addresses many common and key enterprise IoT scenarios. Come learn how to easily create deployments for IoT devices that include AI, Machine Learning, Stream Analytics, as well as your own custom code on devices smaller than a Raspberry PI.
Many say data is the new oil, but electricity may be a better analogy. Data powers insights behind critical business decisions but must also be handled safely, properly harnessed, and effectively delivered. Microsoft’s unique combination of Power BI and Azure SQL Data Warehouse (SQL DW) enables customers everywhere to use industry-leading services not only to power their businesses with rich insights, but also store and deliver that data with unmatched efficiency and performance. Join us to learn how Power BI and SQL Data Warehouse empowers your organization to analyze trillions of rows of data and extract instant insights, leveraging Power BI aggregations and composite models to unify data from multiple connections with surprising ease.
Machine learning development has new complexities beyond software development. There are a myriad of tools and frameworks which make it hard to track experiments, reproduce results and deploy machine learning models. Learn how you can accelerate and manage your end-to-end machine learning lifecycle on Azure Databricks using MLflow and Azure Machine Learning to reliably build, share and deploy machine learning applications using Azure Databricks.
You’d expect Microsoft’s cloud-hosted Continuous Integration platform to have great support for .NET. However, you can use Azure Pipelines with any language, on any platform, thanks to cloud-hosted build agents for Linux, macOS and Windows. Edward Thomson will show you how you can use Azure Pipelines for everything you need. Build a Swift app on macOS, then deploy a Node.js app on Linux; all without having to create any infrastructure yourself. But what if you want to target other platforms? No problem! In this session you'll also see how you can bring your build server to harness the power of Azure Pipelines and build your code for almost any imaginable platform, including x86, ARM or even something truly outrageous like a Commodore 64.
AI, machine learning, deep learning, and advanced analytics are being infused into every team and service at Microsoft—understanding customers and the business, operating services, and delivering innovative new features. But doing machine learning at the scale of Microsoft is challenging. ONNX (open neural network exchange format) has bridged the different model formats for ML frameworks (e.g. TensorFlow, Pytorch, MXNet) to a single execution environment with the ONNX Runtime. Learn how Bing, Ads, Speech, Office, Cognitive Services, and others use frameworks like TensorFlow, PyTorch, Scikit-learn, Caffe for training and rely on ONNX Runtime for high performance inferencing. You’ll also learn how to use ONNX and ONNX Runtime in your AI application with Azure ML.