Azure is a powerful platform with many amazing services, but it can also be hard to know which ones you need to know about when you’re first getting started with cloud development. In this talk we’ll cover five common services that most .NET applications designed to run in the cloud will benefit from using.
Come learn about new security features like Vulnerability Assessment, Information Protection, Thread Detection and Always Encrypt to see how Azure SQL Database is securing your data in the most secure database on the planet.
In this session, you will learn how technologies such as Low Latency Analytical Processing [LLAP] and Hive 2.x are making it possible to analyze petabytes of data with sub second latency with common file formats such as csv, json etc. without converting to columnar file formats like ORC/Parquet. We will go deep into LLAP’s performance and architecture benefits and how it compares with Spark and Presto. We also look at how business analysts can use familiar tools such as Microsoft Excel and Power BI and do interactive query over their data lake without moving data outside the data lake.
Microservices is an architectural style that can bring many benefits when building cloud-scale apps. But working with microservices can be painful. Developers working on one or two microservices in an app that has 10s find it difficult to reproduce the entire application locally to test their changes. In a team that's working in parallel on different parts of an application, developers often find surprises when they integrate their changes. This session will show you how to rapidly iterate and debug code directly in Kubernetes. You get to use familiar dev tools like Visual Studio Code and Visual Studio with the programming language of your choice, but you are always working on Kubernetes in the cloud, in the context of your team and overall application.
In this talk we’ll show why you’d want to modernize your existing .NET apps (traditional ASP.NET WebForms, MVC apps and WCF services) with Windows Containers and Azure. What are the benefits you get with those new technologies and how you can actually implement it and move it to the cloud quickly, showing you many demos about it.
The app development cycle does not finish by submitting your app to the store. Understanding how your app is behaving in the wild, what crashes and errors are your users experiencing, and how your users are using it is very critical to the success of your company. Join us to learn how to integrate App Center into your existing toolchain to monitor your apps with App Center with just few lines of code.
H2O’s AI platform provides open source machine learning framework that works with sparklyr and PySpark. H2O’s Sparkling Water allows users to combine the fast, scalable machine learning algorithms of H2O with the capabilities of Spark. With Sparkling Water, users can drive computation from Scala/R/Python and utilize the H2O Flow UI, providing an ideal machine learning platform for application developers. H2O's open AutoML also fully automates the process training ML algorithms, tuning the right parameters and building ensemble models. Setting up an environment to perform advanced analytics on top of big data is hard, but with H2O Sparkling Water for HDInsight, customers can get started with just a few clicks. This solution will install Sparkling Water on an HDInsight Spark cluster so you can exploit all the benefits from both Spark and H2O. The solution can access data from Azure Blob storage and/or Azure Data Lake Store in addition to all the standard data sources that H2O support. It also provides Jupyter Notebooks with in-built examples for an easy jumpstart, and a user-friendly H2O FLOW UI to monitor and debug the applications.
Learn how to get more out of your serverless investments using the innovative Durable Functions. See how this truly differentiates Azure serverless platform by providing a code-focused method for enabling stateful scenarios and non-trivial orchestrations in real world apps.
In this session you will learn how to develop data pipelines in Azure Data Factory and build a Cloud-based analytical solution adopting modern data warehouse approaches with Azure SQL Data Warehouse and implementing incremental ETL orchestration at scale. With the multiple sources and types of data available in an enterprise today Azure Data factory enables full integration of data and enables direct storage in Azure SQL Data Warehouse for powerful and high-performance query workloads which drive a majority of enterprise applications and business intelligence applications.
Because implementing complete E2E IoT solutions from devices all the way up to Business applications can prove challenging, especially if you are not in the IT business, Azure offers solutions that will simplify your experience and minimize time to production. Come discover the latest and most advanced SaaS and Preconfigured Solutions for IoT on the market today.