The purpose of this GitHub repository is to help startups quickly engage and get up and running on Azure services. You'll find links to key documentation, tutorials and code packets. If you have feedback on the content please submit an issue.
| - Getting started on Azure Learning paths, tutorials, videos, and all you need to know to get ramped up on Azure - Migrating to Azure Tools & services, tutorials, and official information on how to move your existing solution to Azure. - Tools and links Azure price calculator, Azure Trust Center, and other useful additions to help your success on Azure. |
- Infrastructure Services Compute, Networking, Storage - Platform Services Web & Mobile, Data, Intelligence & Analytics, IoT - Cloud Architecure patterns, practices, and architecture blueprints. - Azure Resource Manager overview and availability chart - Feature highlights Get beyond the basics. Helpful features in Azure for Start-ups |
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Get started on Azure – Link to Azure.com Getting Started page.
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Interactive Azure Map - Interactive overview of services available on Azure. Click on a service to learn about it.
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Azure Learning Paths - Get started with these learning paths for different Azure Services.
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Azure on Microsoft Virtual Academy - Virtual courses on cloud development.
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Azure on Channel9 - Video tutorials about Azure services.
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Startup Offers - Get free cloud credits and offers through Microsoft’s BizSpark program.
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Microsoft Azure for Amazon AWS Cloud professionals: Getting Started - Showcase and demo of Microsoft Azure features and comparison to Amazon Web Services to see how they match up.
- Getting Started on Azure: *Overview of the Azure portal*- An introduction to the Azure portal, covering navigation and key elements of the portal including the Azure dashboard, marketplace, and resources.
- Getting Started on Azure: *Resource Groups* - Learn what to consider and how to create and manage a resource group on the Azure portal.
- Getting Started on Azure: *Storage Accounts* - Learn how to create and manage a storage account on the Azure portal and select the storage option that is right for you.
- Getting Started on Azure: *Virtual Networks* - Learn how to set up a virtual network including IP address blocks, DNS settings, security policies, and routing tables on the Azure portal.
- Getting Started on Azure: *Virtual Machines* - Learn how to set up and configure an Ubuntu virtual machine on the Azure portal.
- Additional Getting Started on Azure videos - View additional Getting Started on Azure videos such as Windows Server Virtual Machines, Web Apps, SQL Database on Azure and more.
[Automation just got easier—with Ansible in Azure Cloud Shell Ansible can automate the provisioning of virtual machines, containers, and cloud infrastructures. You can also use Ansible to automate the deployment and configuration of resources in your environment. So we’re excited to announce that Ansible is now available—pre-installed and ready to use for every Azure user—in the Azure Cloud Shell. Microsoft Azure Cloud Shell is a browser-based command-line experience that enables Ansible commands to be executed directly in the Azure portal. This shell can run on any machine or browser. It even runs on your phone! You don’t need to install Python dependencies, and don’t need to do any additional configuration or authentication. It just works, and that makes it easy for anyone to get started with Ansible. Microsoft also released an Ansible extension for Visual Studio Code that allows for faster development and testing of Ansible playbooks. You can use this extension to get code snippets for any Ansible module, get syntax highlighting, and even run the playbook locally, in Docker containers, or directly in Azure Cloud Shell.
Azure HDInsight for big data is now cheaper—and better Microsoft just announced a significant price reduction for the Azure HDInsight analytics service, and we’re also making some exciting new capabilities generally available. HDInsight makes it easy, fast, and cost-effective to process massive amounts of data and deploy big data solutions. The price of HDInsight has decreased by as much as 52%. If you run code in R, you’ll see even more savings: an 80% cost reduction in the surcharge for the R Server on HDInsight. If that’s not enough, there are also some significant improvements to HDInsight: Apache Kafka and Azure Log Analytics integration have reached general availability. And if you have Scala or Java developers building production data pipelines in HDInsight, Microsoft now offers plug-ins for IntelliJ and Eclipse that have the unique ability to submit and debug Spark jobs on the HDInsight clusters, and support for distributed debugging of Spark code running across multiple Spark executors.
New features in Azure Search help you add security to your sophisticated search experiences Azure Search is expanding its enterprise security capabilities with two new features: data encryption and user-identity access control. The encryption feature automatically encrypts your data before persisting it to storage and decrypts it before retrieval. And encryption now extends throughout the entire indexing pipeline—from connection, through transmission, and down to indexed data stored in Azure Search. The new security trimming feature enables administrators to configure Azure Search with a greater level of security and to take advantage of technologies like Azure Active Directory to define groups and roles, which are then matched to user privileges to determine what content users can search and view. At query time, you can implement user-identity access controls that trim search results of documents the requestor is not authorized to see. Enhancements to filters enable integration with third-party authentication providers in addition to Azure Active Directory.
Visual authoring and monitoring in Azure Data Factory Microsoft released a public preview of visual tools for Azure Data Factory v2—a visual, low-code approach to big data analytics in the cloud. Azure Data Factory is a managed cloud service that's built for complex hybrid extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects. With this preview, your devs can easily monitor data factory pipelines without writing a single line of code. They can drag and drop activities on a pipeline canvas, perform test runs, debug iteratively, and deploy and monitor pipeline runs. The tool also provides guided tours of the new visual authoring and monitoring features and a mechanism for providing feedback.
general availability of Azure Event Grid, which gives you all you need for event-driven archi)tectures Event Grid is the first tool of its kind, enabling applications and services to subscribe to all the events they need, whether the events come from Azure services or from other parts of the same application. Events are delivered through push semantics, simplifying your code and reducing your resource consumption. You no longer need to continuously poll for changes, and with the pay-per-event pricing model, you only pay for what you use. The service automatically scales dynamically to handle millions of events per second. And it provides multiple ways to react to events, so any service running anywhere can publish events and subscribe to your reliable Azure events.
Build the most advanced conversational bots by using Azure Bot Service and Language Understanding Microsoft recently announced the general availability of Azure Bot Service and Microsoft Cognitive Services Language Understanding (LUIS), giving developers new ways to create natural language interfaces and chatbots in the Azure cloud. Azure Bot Service enables your developers to create conversational interfaces on multiple channels, while LUIS helps developers create customized natural interactions on any platform, for any type of application, including bots. Making these two services generally available on Azure extends the capabilities of your developers to build custom models that can naturally interpret the intentions of people conversing with bots. Your apps will be able to understand natural language, apply reason to content, and take intelligent actions. Your developers will be able to create custom models that interpret the intentions of the people conversing with bots.
More easily connect your applications to Azure services with Open Service Broker API for Azure Microsoft recently annnounced the preview of Open Service Broker for Azure (OSBA), the most flexible way to connect your applications to a suite of the most popular Azure services- from standard offerings like Azure Database for MySQL to unique Azure solutions like Azure Cosmos DB, a globally distributed multi-model database. OSBA can be deployed to any OSB-compatible platform running in any environment. Whether you’re using Kubernetes, Cloud Foundry, or OpenShift on Azure- on Azure Stack in your own on-prem environment, or somewhere else- you can take advantage of all the great services Azure has to offer via a standard, multi-cloud API. OSBA gives your developers a single simple and elegant way to deliver services to applications running on cloud native platforms like Cloud Foundry, OpenShift, and Kubernetes.
Drive digital transformation with new Azure serverless and DevOps capabilities Kubernetes, an open-source container management and orchestration system, makes it easier than ever to use containers. Microsoft is aiming its focus on Kubernetes community projects and partnerships that extend what customers like you can do with Kubernetes and Azure. As a part of this push, Microsoft has announced its latest efforts to bring serverless computing and DevOps capabilities to users of Kubernetes. Among these efforts is the new Virtual Kubelet, which is a connector that allows you to target Azure Container Instances (ACI)—a service that speeds the creation and deployment of containers on Azure. Microsoft has also announced the Open Service Broker for Azure (OSBA), which allows applications running in Kubernetes, Cloud Foundry, and other platforms to tap into underlying cloud services like Azure Cosmos DB and Azure Blob storage. And finally, Microsoft has introduced Kashti, a dashboard and visualization tool for Brigade pipelines that enables DevOps teams to automate and accelerate their workflows by combining tasks and running them within containers in Kubernetes.
Accelerate your IoT deployment by automatically provisioning devices with Azure IoT Hub Device Microsoft has announced the general availability of Azure IoT Hub Device Provisioning Service, which simplifies the enrollment process by enabling you to automatically register and provision your devices to IoT Hub. IoT Hub Device Provisioning Service enables zero-touch provisioning to the right IoT hub without human intervention, and it brings the scalability of the cloud to what was once a laborious one-at-a-time process. It’s a secure and scalable way to save time and resources and is currently being used by many early adopters to validate various solution deployment scenarios. It supports all protocols that IoT Hub supports, including HTTP, AMQP, MQTT, AMQP over websockets, and MQTT over websockets. It also corresponds to expanded SDK language support for the device and client sides.
Maximize your cloud investments and get a better view of your resources by using Azure Reserved VM Instances Microsoft has launched Azure Reserved Virtual Machine Instances (RIs), which allow you to reserve virtual machines at low prices on Azure. With Reserved Virtual Machine Instances and Azure Hybrid Use Benefit, you can save as much as 82 percent as compared to pay-as-you-go prices, and as much as 72 percent for all virtual machines. Azure Reserved Virtual Machine Instances are flexible and easy to exchange or cancel as business needs evolve. You can purchase Reserved Virtual Machine Instances in three steps—specify your Azure region, your virtual machine type, and a term (one year or three years). That's it. And the built-in capablity to schedule auto-shotdown of VMs saves you even more. Finally, with free Azure Cost Management, you can further optimize your cloud resources, manage departmental budgets, and allocate costs.
Bind the power of real-time streaming data to your applications with Apache Kafka on HDInsight Micorosoft Azure announced the general availability of Apache Kafka on HDInsight as a managed service. Now you don’t need to worry about managing Kafka clusters because HDInsight manages and fixes the issues involved with running Kafka at an enterprise scale. The general availability of Apache Kafka on HDInsight completes an end-to-end streaming pipeline on the Azure platform. You can deploy highly scalable, fault-tolerant, and secure real-time architectures with Apache Kafka on the managed HDInsight platform with a single click. Kafka clusters are up and running within minutes, with a 99.9% SLA. This means you can concentrate on writing real-time applications, improving their logic, and building higher-level pipelines instead of worrying about the intricacy of installing new Kafka brokers or fixing broken ones.
Create a globally distributed database with new multi-model APIs from Azure Cosmos DB Microsoft Azure Cosmos DB provides the perfect platform which enables you to focus on building and scaling your application with a globally distributed, multi-model database service rather than spending time on management. And Microsoft continues to improve the Azure Cosmos DB service: the company recently announced of general availability of Azure Cosmos DB Gremlin API and Azure Cosmos DB Table API By using the Cosmos DB multi-model and multi-API capabilities to access and query data, your developers can easily build powerful, scalable apps. Azure Cosmos DB Gremlin API can deliver critical improvements to the performance of graph operations, improved import and backup scenarios through new tooling, and enhanced support for open-source frameworks recommended by Apache TinkerPop, including Python client support. The Azure Cosmos DB Table API enables your applications written for Azure Table storage to take advantage of premium capabilities of Azure Cosmos DB, like turnkey global distribution, low latency reads/writes, automatic secondary indexing, dedicated throughput, and more.
Harness the power of IoT with Azure-based Time Series Data Repositories and analytics Microsoft recently announced the general availability of Azure Time Series Insights, which gives you a global view of data that’s being sent in near real time, allowing you to drill deeper and letting you to quickly validate your IoT solution, see data that devices are sending to your Azure IoT Hub, or to Azure Event Hubs. It’s a scalable, commercial-grade solution for storing and analyzing data without the headaches and expense of tedious resource management. It enables you to easily explore and analyze time series data streams without having to write a single line of code. And it avoids costly downtime to mission-critical devices by helping you discover hidden trends, spot anomalies, and conduct root-cause analyses in near real time.
Build great apps rapidly and easily with your favorite MariaDB language As a part of its continued efforts to provide a first-class experience to developers using open source technologies on Azure, Microsoft is adding MariaDB to the list of open source relational database platforms it will bring to Azure. MariaDB will join MySQL and PostgreSQL, whose additions were announced earlier this year, in Azure to provide more choices to developers. In addition to this, Microsoft has joined the MariaDB Foundation as a Platinum sponsor. MariaDB will be a fully managed service on Azure. You’ll be able to provision a new instance in minutes and quickly scale the compute power you need up and down online. These services come with built-in high availability and security and a 99.99% SLA at general availability. And Azure lets you easily add new modern experiences to your apps through cognitive service APIs and the Bot Framework. All this allows you to focus on your apps instead of on managing a database or your Infrastructure.
Simplify and speed up your Azure resource deployment with Azure Building Blocks You’ve created an elegant solution to meet the needs of your customers by using a cloud architecture that’s the envy of competing startups—but deploying updates from dev to staging to production can be challenging, even with Microsoft Azure Resource Manager templates. To solve this problem, Microsoft has announced the release of Azure Building Blocks an open-source command-line tool and set of Azure Resource Manager templates designed to simplify deployment of Azure resources. With Azure Building Blocks, you don't need to author any templates. You only need to specify the parameter settings for the resources you want to deploy. These parameter settings are then merged with best practice defaults and deployed with the command-line tool. Azure resources currently supported in Azure Building Blocks include virtual networks, security groups, user-defined routes, Windows and Linux VMs, VM extensions, load balancers, and Application Gateway. This enables you to use infrastructure as code in Azure without worrying about the complexity of Azure Resource Manager resources.
Accelerate artificial intelligence and high-performance computing with the new Azure NVIDIA GPUs User experience is critical to an app’s success. Bring smarter experiences to your customers by using AI, machine learning, and high-performance computing to deliver power and pull meaningful insights from your data. To democratize these technologies, NVIDIA has partnered with Microsoft to offer GPU deep learning in the cloud. Microsoft is already providing VM sizes with NVIDIA’s K80s, M60s, P40s, and P100s. A new VM size—NCv3—will further support your GPU workloads. The NCv3 will offer the new NVIDIA Tesla V100 GPU. Two other VM sizes—the NCv2, offering NVIDIA P100s, and the ND-series, offering NVIDIA P40s—have entered general availability. Azure Batch AI and Data Science Virtual Machine images can also take advantage of these GPU VMs. Azure Batch AI can use all the new types of Azure GPU VMs, giving you ready access to great AI hardware coupled with simple AI job execution. Data Science Virtual Machine images on Azure are being updated to take advantage of the new GPUs and can be used for data analytics, machine learning, and AI training. Azure is the only cloud with dedicated InfiniBand interconnects to enable accelerated multi-VM computations with the new VM sizes.
Fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure Apache Spark is the platform of choice for building cloud-scale applications because it enables you to run powerful analytics algorithms at scale and in real time to drive business insights. Microsoft recently announced the preview of Azure Databricks, designed collaboratively with the founders of Apache Spark, to provide a Spark-based analytics platform on Azure. It’s integrated with Azure to provide one-click setup, streamlined workflows, and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts. It curates and processes massive amounts of data and manages the whole workflow process throughout a project. And it has built-in integration with Azure Blog storage, Azure Data Lake storage, Azure SQL Data Warehouse, Cosmos DB, Azure Event Hubs, Apache Kafka for HDInsight, Power BI, and Azure Active Directory. Let Databricks help you simplify the creation of modern data warehouses and enable you to provide self-service analytics and machine learning over all your data—with enterprise-grade performance and governance.
Gain all the benefits of Kubernetes without the complexity and operational overhead by using Azure Container Service (AKS) Kubernetes, an open-source container management system, has surged in popularity in the past several years. You might be considering—or already using—Kubernetes for managing and orchestrating your containerized applications. But ongoing operations and maintenance is challenging, and you don’t want to dedicate precious time and resources to it. To solve with this problem, Microsoft announced the preview of AKS (Azure Container Service) to make it quick and easy to deploy and manage containerized applications without container orchestration expertise and without sacrificing portability. You can quickly provision clusters to be up and running in no time, and simplify your monitoring and cluster management. The new service features an Azure-hosted control pane, automated upgrades, self-healing, easy scaling, and a simple user experience for developers and cluster operators. To provide scale across the global footprint of Azure, Microsoft also announced the preview of geo-replication in Azure Container Registry. By clicking on a map, you can now manage a single registry replicated across any number of regions. Azure Container Registry geo-replication enables you to manage your global deployments as one entity.
Extend and accelerate your development with support for Java to Azure Functions You need to harness the power of serverless computing with Azure Functions, but you use OSS tools and languages that once blocked you from doing that. Microsoft rearchitected the Azure Functions runtime to allow support for various programming languages, and Java is the first language that Microsoft is introducing in a new preview.The new Java runtime will share all the features provided by Azure Functions, such as the wide range of triggering options and data bindings, the serverless execution model with autoscaling, and pay-per-execution pricing. As a Java developer, you don’t need to use any new tools to develop with Azure Functions. You can use popular IDEs and editors like Eclipse, IntelliJ, and Visual Studio Code to develop and debug Azure Functions locally. In fact, with the newly released Maven plug-in from Microsoft, you can create, build, and deploy Azure Functions from your existing Maven-enabled projects. The new Azure Functions Core Tools will enable you to run and debug your Java Functions code locally on any platform.
Proactively monitor application health and resolve issues faster with Azure App Service diagnostics App Service diagnostics lets you diagnose and troubleshoot problems with your apps. It provides an intelligent and interactive experience, analyzing what’s wrong with your web apps and quickly guiding you to information that will help you troubleshoot and resolve issues faster. You can run proactive health checkups against common web app metrics and tap into a pool of built-in knowledge that will help you troubleshoot efficiently. App Service diagnostics detects issues in four main areas that are common problem areas for web applications: requests and errors, performance, CPU usage, and memory usage. If you’ve had issues with your web app within the past 24 hours, diagnostic graphs will be available for you to analyze, together with additional troubleshooting tools and links to helpful documentation and forums.
Grow fast and go far—build hybrid data integration at scale with Microsoft Azure Data Factory Data is no longer something to be stored and ignored—it’s one of your biggest business assets. If you want to kickstart growth and beat the competition, you need a system to refine enormous stores of raw data into actionable business insights. But you’re also focused on the bottom line, so that solution has to be cost effective, flexible, and scalable. Azure Data Factory is a cloud-based data integration service that allows you to create data-driven workflows in the cloud for orchestrating and automating data movement and data transformation. Microsoft has announced expanded capabilities in a new public preview of in Data Factory. You can now create, schedule, and orchestrate your extract-transform-load (ETL), extract-load-transform (ELT), and data integration projects at scale, whether your data lives in the cloud or on a self-hosted network. With the addition of SQL Server Integration Services (SSIS), you can easily lift your SSIS packages into the cloud by using new managed SSIS hosting capabilities in Data Factory. By spinning up an SSIS package with a new feature called Integration Runtime (IR) in Data Factory, you’ll be able to execute, manage, monitor, and deploy SSIS packages in the cloud.
Get ahead—and stay ahead—with the next generation of Remote Monitoring in Azure IoT Suite Technology is advancing fast, and devices are getting smarter day by day. To meet this market reality and accelerate the development of your IoT apps, you can work with preconfigured solutions from the Azure IoT Suite. IoT Suite preconfigured solutions combine multiple Azure IoT services. You can deploy them in minutes to get started quickly, and you can customize them to meet your needs. Microsoft has announced a new version of the IoT Suite Remote Monitoring preconfigured solution. It provides two deployment options to match your needs: a Basic version to get started at a low cost, and a Standard version for production-ready IoT solutions. The new version of Remote Monitoring includes a new scalable Microservices architecture that’s available in both .NET and Java toachieve scale and flexibility without compromising development speed. You can also configure rules and alarms over live IoT device telemetry, and troubleshoot and remediate issues within your IoT device groups. The user interface is completely redesigned to visualize the capabilities of a production-ready solution and provide a rich dashboard for deep insights and solution status.
Turn users into loyal fans with new innovations in the Microsoft AI-driven digital transformation User experience is critical to an app’s success. One way to boost your UX game is with the new capabilities in Azure Machine Learning. Microsoft recently shared some exciting innovations in AI development platforms. These announcements span Azure Machine Learning, new Visual Studio tools for AI, Cognitive Services, and new enterprise AI solutions. The next generation of Machine Learning includes powerful new capabilities that enable developers to exploit big data, GPUs, data wrangling, and container-based model deployment. Microsoft also released Visual Studio Code Tools for AI to provide a rich set of capabilities for easily building models with deep learning frameworks, including Microsoft Cognitive Toolkit (CNTK), Google TensorFlow, and more. And Microsoft Cognitive Services has two new cloud-hosted APIs that enable developers to easily add AI capabilities—such as emotion and sentiment detection, vision, and speech recognition—into applications.
Hyperscale to new heights with the general availability of Service Fabric on Linux You’d rather focus on building great apps than re-architect your infrastructure to keep up with growth. With Azure Service Fabric, you can do what you do best and let Azure solve the hard distributed systems problems: reliability, scalability, management, and latency. Microsoft has announced the general availability of Service Fabric on Linux for container orchestration in all regions, including national clouds. With this release, which includes runtime 6.0 and SDK 2.8, you can now run containerized applications on Service Fabric for both Windows Server and Linux. You can also take advantage of orchestration features on Linux. Use Service Fabric to launch and manage container images, govern resources, complete service discovery with DNS, and gain insights from using OMS integration. With volume driver integration, you can truly focus on building applications and not assembling or building a platform across both Windows Server and Linux.
Azure Stream Analytics provides on-demand, real-time analytics to power intelligent action To make your big ideas a reality, you need IT agility and flexibility. Your IT resources have to be able to scale up and out at a moment’s notice. With Azure Stream Analytics, you can instantly scale out the processing power from one streaming unit to hundreds of them for any job, and you pay only for the processing used for the job. Stream Analytics is an on-demand, real-time analytics service that you can use to power intelligent action. Microsoft has announced the preview of several new capabilities in Azure Stream Analytics, including built-in inline machine learning–based anomaly detection, egress to Azure functions, support for compressed data formats, JavaScript user-defined aggregates, and support for CI/CD in Microsoft Visual Studio tooling. A machine learning–based operator in Stream Analytics helps you monitor data from applications or devices in real time and easily detect events or observations that don’t conform to an expected pattern. Microsoft also announced an output adapter to Azure Functions from Azure Stream Analytics. This allows you to connect Stream Analytics to Azure Functions and run a script or piece of code to trigger downstream workflows and accelerate responses to key events. New Visual Studio tooling allows you to perform automated builds and test and deploy scripts with Stream Analytics Visual Studio projects.
Automate the provisioning of devices to Azure IoT Hub Provisioning is an important part of the lifecycle management of an IoT device. Microsoft has announced the preview of Azure IoT Hub Device Provisioning Service to remove the tedium of manually configuring IoT devices. This automated service can be used to provision millions of devices. The IoT Hub Device Provisioning Service is a helper service for your IoT hub that enables zero-touch, just-in-time provisioning to the right IoT hub without human intervention, enabling you to provision IoT devices in a secure and scalable manner. The Device Provisioning Service is the only cloud service that provides complete automated provisioning, including registration of the device to the cloud as well as configuration of the device.
Get deep insights into containers with the newly announced Container Monitoring Solution on Azure Log Analytics Docker containers is a growing technology for running modern applications. It helps developers and DevOps with easy provisioning and continuous delivery in modern infrastructures. To simplify Docker container monitoring and management, Microsoft has announced the general availability of the Container Monitoring Solution on Azure Log Analytics, available on Azure Marketplace. It provides deep insights into containers supporting Kubernetes, Docker Swarm, Mesos DC/OS, and Service Fabric container orchestrators on multiple OS platforms. It helps you know which containers are running, what image they're running, and where they're running. You can view detailed audit information that shows commands used with containers. And you can troubleshoot containers by viewing and searching centralized logs without having to remotely view Docker or Windows hosts.
Microsoft announces Azure Event Grid, a unique and intelligent event service for modern applications Modern applications—including Internet of Things (IoT), mobile apps, business process applications, and more—are built around events. This drives the need for event-based programming. To support this need, Microsoft recently announced the first-of-its-kind Azure Event Grid, a fully managed, intelligent event-routing service that allows for uniform event consumption using a publish-subscribe model. You can build event-based, serverless applications with a higher level of abstraction, so you don’t need to worry about infrastructure, provisioning, or scaling. You can use Event Grid to react to relevant events across Azure and non-Azure services in near-real time. And you can create richer app scenarios by connecting serverless logic to events from multiple sources.
Deploy your Java app to Azure by using a new Maven Plugin With the release of a new Maven Plugin for Azure Web Apps, developers can now deploy or redeploy Java-based web applications over Linux Azure App Service or Windows App Service in a couple easy steps. The Azure App Service provides a managed web app environment to enable your Java application to run smoothly on Azure. The only thing the developer needs to worry about is the code of the Java app. App Service handles the provisioning, load balancing, auto-scaling, and app health monitoring. You can also customize the settings and create a custom layout for your application.
New Azure Batch Rendering to run large-scale rendering workloads seamlessly on Azure Rendering visual effects is one of the most complex aspects of a cinematic production. Major challenges in rendering include finding the right infrastructure, setting up and managing a render farm made up of high-performance computing clusters, and managing associated workflows. To overcome these challenges, Microsoft has announced the public preview of Azure Batch Rendering service, which offers cloud-scale rendering capabilities on a pay-per-use basis. The Batch Rendering service handles job scheduling and queueing, managing failures and retries, and auto-scaling for your rendering jobs. You can submit rendering jobs via client applications like Autodesk Maya, 3ds Max, and Arnold and get easy scaling, monitoring, and asset management. A flexible programming model and an SDK that’s available in various languages allow your developers to integrate their own pipelines and workflows into the solution. Batch Rendering accelerates large-scale rendering jobs to deliver results to your customers faster.
Microsoft brings container orchestration for Windows Server Containers to Azure Service Fabric Running a traditional application inside containers is an easy first step to gain some of the benefits of a microservices architecture, such as improved density and easier application lifecycle management. Azure Service Fabric is the Microsoft microservices platform, and Microsoft has announced the release of Service Fabric 5.6 runtime and 2.6 SDK, which support the orchestration of Windows Server Containers. This release includes many new features targeted at container orchestration, including a DNS service, resource governance, Microsoft Operations Management Suite integration, and more. It also contains support for Docker Compose for deploying containerized apps to Service Fabric with Microsoft Visual Studio 2017 tooling integration.
Video Indexer—a cloud service that lets you easily extract insights from your videos When video and audio content lacks human-understandable, time-stamped metadata, it can be difficult to find. Generating such metadata for video and audio is expensive and next to impossible when you have a high volume of this type of content. Microsoft has announced the public preview of a cloud service called Video Indexer as part of Microsoft Cognitive Services. Video Indexer enables organizations with digital video and audio content to automatically extract metadata and use it to build intelligent, innovative applications. It builds upon media AI technologies to make it easier for you to extract insights from video and audio. You can use Video Indexer to power new forms of content discovery, like searching for spoken words, faces, characters, and emotions, and to enrich your apps with embedded video insights to drive user engagement.
Massive-scale cloud rendering with Autodesk on Azure When implementing a rendering project, it’s hard to find the right infrastructure, set up a render farm made up of high-performance compute clusters, and then manage the render farm. Even small projects can take anywhere from days to weeks to complete. The cloud is perfectly suited for variable-length and long-running rendering projects. Microsoft has announced the preview of Azure Batch Rendering and its integration with Autodesk. When used together with Autodesk, Azure opens doors for artists, engineers, designers, and developers. Built on top of Azure Batch, a mature production service, this new rendering platform will allow you to seamlessly submit rendering jobs by using Autodesk’s suite of products—including Autodesk Maya, 3ds Max, and Arnold—together with the agility, flexibility, and scalability of Azure compute.
Build fast, scalable, globally distributed applications by using Azure Cosmos DB Microsoft has announced the general availability of Azure Cosmos DB, a globally distributed multimodel database. Azure Cosmos DB is the first globally-distributed data service that lets you elastically scale throughput and storage across any number of geographical regions while guaranteeing low latency, high availability, and consistency—and it’s backed by the most comprehensive SLAs in the industry. Azure Cosmos DB is the right solution for your globally distributed mission-critical applications—including web, mobile, gaming, and IoT applications—when predictable throughput, high availability, low latency, and a schema-free data model are key requirements.
Your Microsoft-managed admin machine in Azure, for Azure Cloud Shell provides an interactive, browser-accessible, pre-configured shell experience for managing Azure resources without the overhead of installing, versioning, and maintaining a machine yourself. The authenticated shell experience is hosted in the cloud and accessible from virtually anywhere. It enables you to use common tools and programming languages in a shell that’s updated and maintained by Microsoft. You can also persist your files across sessions by using attached Azure File storage.
Gain powerful info about your web app by using new tools in Microsoft Azure Application Insights Which features of your web app are most popular and most frequently used? Do your users achieve their goals with your app? Microsoft has released new tools in Application Insights to help you understand user behavior and empower your development team to better understand how customers use your web apps. Every time you update your app, you can assess how well it works for users. You can get rich performance monitoring, powerful alerting, and easy-to-consume dashboards to help ensure your applications are available and performing as you expect.
Storage Service Encryption (SSE) for Azure File Storage. When enabled, SSE automatically encrypts data at rest using a 256-bit encryption key—helping organizations meet organizational security and industry compliance requirements.
Simplify VM deployment using custom templates in Azure Resource Manager (ARM)Custom Azure Resource Manager (ARM) templates are a great way to make deploying virtual machines and resources a repeatable, easy-to-automate process. The template reference documentation explains the available resource types you can use to create custom templates for various Azure resources—including what values to use in your template.
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Azure Portal - The best way to get started is with the Azure portal, a web based interface for managing Azure.
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Azure SDKs & Tools - SDKs for many common languages such as .NET, Java, Node.js, Python, Ruby and other tools.
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Azure PowerShell - Work with PowerShell cmdlets to perform Azure operations.
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Azure CLI – Create/manage Azure resources using a set of open-source shell-based commands.
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Azure API Reference - Reference for Azure REST and .NET APIs.
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Azure Solutions - A listing of top Azure solutions and their brief descriptions
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Azure Products and services – A searchable list of all Azure products and services
- AWS to Azure mapping - Map between Azure and AWS services
- AWS to Azure migration - Migrate virtual machines in Amazon Web Services (AWS) to Azure with Azure Site Recovery
- MongoDB to Azure Migration resources
AWS VM to Azure VM migration AWS CDN to Azure CDN Migration AWS S3 to Azure Blob Storage migration AWS CDN to Azure CDN Migration ASP.NET Web App migration from AWS to Azure - AWCopy - Azure service that provides parallelized copies of S3 files in Amazon Web Services to Azure blobs.
- CloudBerry Cloud Migrator - service to transfer files from one cloud storage to another (Amazon S3 & Glacier, Windows Azure Blob Storage, Rackspace Cloud Files and FTP servers).
- Azure Import/Export Service - Transfer Data to Blob Storage.
Infrastructure as a service (IaaS) refers to the compute, networking and storage building blocks which allow you to build any kind of cloud solution. IaaS allows you to have maximum control on how you manage virtual machines, network configuration but requires you to invest in attaining robustness, availability and scalability in the cloud.
- Learning Path for Azure VMs - Learn how to deploy and manage VMs.
- Linux VM – Get started creating a Linux VM on the Azure Portal and utilize proven practices to run the Linux VM.
- Windows VM – Get started creating a Windows VM on the Azure Portal
- VM Extensions - Gain an overview of extensions to virtual machines such as the Chef, Docker or custom script extensions. Direct link to Docker VM Extension
- VM Scale Sets Overview - Learn about deploying and managing VM scale sets.
- Service Fabric Overview – a distributed systems platform that makes it easy to package, deploy, and manage scalable, reliable microservices.
- Choose between App Services, Service Fabric and VMs - including scenarios and recommendations.
- Docker Documentation - Starting point for documentation on Dockers including Docker for MAC, Windows, Linux, etc.
- Docker VM Extension - Create a Docker environment in Azure using the Docker VM extension.
Containers on Azure - Perform heavy computational tasks (for example video or audio encoding, hash calculation, data encryption, etc.) and make the process scalable and cost effective using Docker containers. Deploy to Azure using the Docker VM Extension - use Resource Manager templates to deploy the Docker VM Extension in a custom, production-ready environment that you define AWS S3 to Azure Blob Storage migration Ruby on Rails web app on Azure VM - Virtual Networks (Vnets) Overview – Learn about Azure Virtual Networks and how to create them.
- Network Security Groups – Learn about Network Security Groups (NSGs) and how to configure them.
- Load-Balancers – Learn about Azure Load Balancer and to configure one.
- Introduction to Azure Storage – Learn the basics of Azure Storage including Blob, Table, Queue, and File storage.
- Azure Backup – Learn about and how to implement Azure Backup to back up (or protect) and restore your data in the Microsoft cloud.
- Azure Site Recovery – Orchestrate your disaster recovery plan.
- Create a storage account – Learn how to create a general purpose or blob storage account with links to getting started on Blob, Table, Queue, and file storage accounts.
Platform as a Service (PaaS) resources are Azure services which are built for most cases and allow you to enjoy high availability, scalability and robustness out of the box. Instead of managing VMs directly, let Azure manage the underlying infrastructure and focus on building your applications and solutions.
- Azure App Service overview – Learn about Web Apps, Mobile Apps, API apps.
- Azure Web Apps – Create and deploy mission-critical web apps that scale with your business.
- Azure Mobile Apps – Build engaging iOS, Android, and Windows apps.
- Getting Started with Xamarin - Create cloud-powered mobile apps faster across iOS, Android, and Windows. Overview of Xamarin and how to use it.
- Notification Hub overview - An easy-to-use, multiplatform, scaled-out push infrastructure.
- Azure Search - Ready-to-use service that you can populate with your data and then use to add search to your web or mobile apps.
- Azure Mobile Services REST API Reference MSDN – Documentation on Mobile Services REST API and the available operations.
- Azure Deployment Using Git – Learn the basics and understand available resources to support publishing web applications on Azure using Git workflows.
- Azure Media Services (AMS) Overview – Learn about Azure Media Services and how to build scalable media management and delivery apps.
Notification Hub demo - Deliver push notification messages to mobile applications on iOS, Android and Windows Phone platforms using Azure Notification Hub PHP, Node.js, and Python - Deploy PHP, Node.js and Python web apps on Azure and learn how to configure Azure App service - Azure SQL Overview – Gain an overview on SQL and how to create a SQL DB on Azure.
- Azure SQL (PaaS) vs. SQL Server on Azure VMs (IaaS) - Learn what scenarios are better for an IaaS vs. PaaS SQL solution.
- DocumentDB – Learn about this fully managed NoSQL database service and how to build and manage DocumentDB applications.
- MongoDB on Azure – Learn about MongoDB on Azure and deployment recommendations.
Import data to DocumentDB with the Database Migration tool – Learn how to use the open source DocumentDB data migration tool to import data to Azure DocumentDB Install MongoDB on a Windows VM - Learn how to install MongoDB on a Linux VM in Azure. Install MongoDB on Linux - Learn how to install MongoDB on a Linux VM in Azure. Create a web app that connects to MongoDB – Learn how to create a web page in Azure that connects to MongoDB running on a VM. SQL DB and Elastic pool feature tutorials – simple step-by-start tutorial for different SQL feature areas -
Azure HDInsight - An introduction to Hadoop on Azure HDInsight, its ecosystem, and big data. Learn about the Hadoop components, common terminology, and scenarios for big data analysis.
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Stream Analytics - Overview of Azure stream analytics, low-cost solutions to gain real-time insights from devices, sensors, infrastructure, and applications
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Additional Intelligence and Analytics services – HDInsight, Machine Learning, Data Factory, Log Analytics, Data Catalog, Power BI Embedded, Data Lake store and much more.
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Machine Learning Overview - Overview and tutorial on Machine Learning. Or explore further Machine Learning
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Azure Machine Learning Studio - A collaborative, drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions.
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Get started with Microsoft Cognitive Services – Learn how to easily add powerful artificial intelligence capabilities to your applications with Microsoft Cognitive Services. See Cognitive Services for more information.
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Cognitive Services: Making AI Easy – The rise of machine learning has produced an explosion of APIs to make your applications more intelligent. Learn about more than 20 Cognitive Services APIs. You'll see powerful demos, experience the simplicity of calling this code, and get ideas for adding this functionality to your own applications.
Data Science and Machine Learning – Microsoft Imagine course content - learn fundamental concepts of machine learning and use Spark to predict the trend and patterns of massive data sets -
Azure IoT suite documentation - Starting point to learning and using the Azure IoT suite.
IoT Microsoft Imagine course content – learn how to collect streaming data from IoT devices and analyze the streaming data MyDriving App IoT sample – MyDriving app uses a wide range of Azure services to process and analyze car telemetry data for both real-time insights and long-term patterns and trends - Cloud Patterns & Practices - Best practices for building cloud solutions. Including checklists and design patterns.
- Architecture Blueprints - Architectures for an array of different cloud scenarios.
- Azure Price Calculator - Easily calculate pricing of Azure Services.
- Azure Trust Center - Learn about Azure security, compliance, privacy and transparency.
- Azure Subscription Service Limits - Learn about Azure subscription and service limits, quotas, and constraints.
- Azure Resource Explorer - A very useful web application to explore the Azure REST API.
- Azure Storage Explorer - A client application for Linux, Mac or Windows to easily work with storage accounts on Azure.
The Azure Resource Manager is at the core of the Azure platform and is used to deploy and manage Azure services. Every resource in Azure managed under ARM can be described and managed in a consistent way. It's very helpful to understand the Azure Resource Manager and how to work with Resource Groups.
- ARM Overview - Get an overview of the Azure Resource Manager.
- ARM vs. Classic - Understand the difference between ARM and the Classic (ASM) deployment model.
- Azure portal availability chart – use the availability chart to determine what services are supported by ARM and the Azure portal
ARM templates are JSON descriptions of ARM deployments which can be used for "Infrastructure as Code".
- Deploying ARM Templates – Learn how to deploy ARM templates using PowerShell, Azure CLI or REST API.
- Quick Start Templates - A Github maintained, vast collection of templates for common use cases to help you get started authoring your own templates or deploying simple solutions.
- Template Authoring - How to author custom templates.
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