Developing Serverless application with Microsoft Azure and Cognitive ServicesJeff Chu
?
Introduction to Serverless computing, how to develop application with Microsoft Azure Functions and Logic Apps, plus Cognitive Service Text Semantic analysis.
The document discusses Microsoft's .NET conference and platform. It highlights that .NET Core 2.0 has been released and is available for download. It promotes .NET as being able to build any application for any platform and develop with any programming language. It also emphasizes that .NET sees large growth in active developers and popularity. Additionally, it provides statistics on customer success with .NET and shows how .NET powers a variety of applications and services.
Microsoft Azure IoT 手把手實作 @ K.NET by Maduka (2017-8-12)Jeff Chu
?
A hands-on lab exercise for Microsoft Azure IoT, help students to learn how to use IoT hub, SQL Database, Stream Analytics services to build their IoT solution.
Developing serverless applications with azure functionsJeff Chu
?
This document discusses developing serverless applications with Azure Functions. Azure Functions allow processing of events using small, isolated pieces of code called functions. Functions can be triggered by events from other Azure services and external sources. Functions are easy to develop, scale automatically, and only charge for the time spent processing events.
The document discusses new features in C# 7.0 including tuples, pattern matching, out variables, and more. It provides code examples demonstrating how to use tuples to return multiple values from functions, type patterns to match types in switch statements, and when conditions to add additional checks to case statements. The examples show enhanced control flow options in C# with these new features.
The document discusses containers and how they compare to virtual machines. It explains that containers provide operating system-level virtualization where the kernel is shared among containers, unlike virtual machines which virtualize hardware. This allows containers to have faster startup and be more resource efficient. The document then provides steps for setting up a container environment on Windows and details how to build, run, distribute, and update container images.
This document discusses Microsoft Azure's support for Linux and Java workloads. It provides an overview of pre-built Linux virtual machine images on Azure including popular distributions like Oracle Linux and Windows Server. It also outlines options for deploying Java applications on Azure infrastructure services, platform services, and using common Java APIs and tools across deployment models. Customer quotes are provided praising Azure's scalability and cost benefits compared to on-premise Linux servers.
13. Devices Device Connectivity Storage Analytics Presentation & Action
Event Hubs SQL Database
Machine
Learning
App Service
IoT Hubs
Table/Blob
Storage
Stream
Analytics
Power BI
Service Bus DocumentDB HDInsight
Notification
Hubs
External Data
Sources
External Data
Sources
Data Factory Mobile Services
BizTalk Services
{ }
#10: This has happened quickly
We had early generations of smart cars, smart refrigerators and smart WiFi scales
However, devices were isolated, stand alone and typically had their own exclusive ecosystem
Devices were typically expensive, or only certain models
#11: - Ecosystems are integrated. Customers expect their phone to work with their watch and their car and their coffee machine.
Boundary is blurring between ‘work’ & ‘play’… many devices have a dual purpose
There are many more devices at the smaller & cheaper end of the spectrum. Not unusual to have network connectivity in a device costing a few bucks.
The explosion of new smart hardware devices needs to be supported by a broad, hyperscale service back-end to allow the integration between hardware ecosystems.
#14: We then think about the different services within Azure IoT that are useful for implementing the Reference Architecture.