Microsoft Azure services: How to leverage them
Microsoft Azure is a cloud computing service that hosts and scales applications. It was made by Microsoft.
Microsoft Azure is a cloud computing service that hosts and scales applications. It was made by Microsoft. It offers a wide range of services for computing, storage, databases, analytics, machine learning, and application services.
Azure provides you with access to all the tools needed to build your apps including Visual Studio 2017 (with cross-platform support), Visual Studio Code Editor (with cross-platform support), PhoneGap Build Plugin that allows you to target smartphones or tablets running iOS 9 or Android 5 KitKat or higher versions respectively.
Azure also offers a variety of services to help you manage your application and its data. Among these are: — Application Insights, a service that assists you in understanding how users interact with your app, monitoring performance and availability, and identifying issues. — Azure Backup — an agentless backup solution that allows you to protect on-premises workloads like SQL Server or SharePoint Server.
App Service
App Service is a Platform as a Service (PaaS) offering from Microsoft Azure. App Service provides an easy way to create, deploy and manage web apps. It’s perfect for building web apps without having to worry about the backend infrastructure, scaling, or maintaining your code.
You can use App Service to build web applications that run in the cloud or on-premises inside your organization’s data center. You can even run multiple versions of your same app at once — giving you flexibility when it comes to choosing which version will be deployed first based on business needs and traffic patterns.
App Service has a wide range of features that can help you build and deploy a web application. It offers integrated tools for continuous deployment, debugging and diagnostics, load balancing, security, site recovery, and more. App Service also makes it easy to make an app that is always up and running, thanks to built-in availability zones that are meant to prevent downtime. You can use the service in the cloud or on-premises inside your organization’s data center.
Azure Web Apps
Azure Web Apps is a development and deployment service that lets you create, deploy, and scale web apps in the cloud.
Azure Web Apps provides you with a fully managed web hosting environment. It does this by running your app on its own virtual machine instances and providing you with access to all the services it needs to run your app: databases (SQL Server), file storage (Azure Files), and user authentication (Azure Active Directory).
Azure Web Apps has been around since 2013. It was the first PaaS offering from Microsoft and remains one of the most popular choices for hosting a website on Azure.
Microsoft SQL Database
SQL Database is a relational database service that is fully managed and available through the cloud. It can be used to store and query data in a variety of formats, including JSON, XML, and spatial data.
The SQL Database supports SQL Server features such as indexes, stored procedures, triggers, and views. It also includes some built-in functions, including string and date/time.
DocumentDB
DocumentDB is a fully managed, NoSQL database service that makes it easy to build high-performance applications using Azure. With DocumentDB, you can store, query, and sync structured, semi-structured, and unstructured data in the cloud.
With DocumentDB, you can store and query JSON documents, index them using the full spectrum of SQL capabilities, and scale out with ease. DocumentDB is built on the same infrastructure as our other cloud offerings, so it’s secure, reliable, and scalable.
Blob Storage
Blob Storage is a service for storing large amounts of unstructured data, such as text or binary data, that can be accessed from anywhere in the world via HTTP or HTTPS. It can store any type of data, including files and images.
Storj is a decentralized, open-source cloud storage platform that uses blockchain technology to provide secure and private data sharing. The company was founded in 2014 by Shawn Wilkinson, who also serves as the company’s CEO.
Application Insights
Application Insights is a service for monitoring, diagnostics, and analytics for web-based applications. It provides an overview of the health and performance of your web application by providing insights into how it’s performing at runtime, or in real-time when you make changes to your code. With this information, you can troubleshoot issues before they occur, improve response times, and reduce errors by optimizing resources for optimum efficiency.
Application Insights can be used to gain insight into how users are interacting with your site (usage patterns), what pages they visit most often (visitor journey maps), or which parts need improvement (heatmaps). You will also receive alerts if there are any problems detected during testing or monitoring phases such as high disk activity on one server instance where no issues were detected previously — giving immediately actionable advice without waiting hours before seeing results
Azure Websites
Azure Websites is a Platform as a Service (PaaS) offering that allows you to create, deploy, and manage websites on Microsoft Azure. It is a fully managed platform that provides the computing and storage resources required to run web applications.
Azure Websites uses the same technologies as Azure App Services: Python or Node.js, SQL database services, and Cloud SQL backup service for data protection in case of disaster recovery scenarios. It’s a great service for web developers and IT professionals who want to monitor their applications. You can also use Application Insights with other Azure services such as Azure Stream Analytics or Cortana Intelligence Suite to create more customized solutions.
Elastic Compute
Elastic Compute is a service that allows you to run virtual machines in the cloud. It’s similar to Amazon EC2, but it’s cheaper and better suited for running Linux or Windows virtual machines. You can use Elastic Compute for your own development projects and test environments, as well as for applications like email servers and websites that require high availability, high-performance computing (HPC) capabilities, or storage solutions without needing dedicated hardware on-premises.
Elastic Compute also offers an easy way to deploy Docker containers using its continuous integration tooling called Docker Hub Server (DHS). DHS lets developers create Docker images from any source code repository they have access to (such as GitHub), and connect them with their own internal services through ports exposed by DHS itself so that they don’t need port forwarding rules set up manually either before deploying them into production environments where more complex security policies might apply such as those provided by Azure Security Center
Azure Websites supports the following programming languages: -C# -JavaScript (Node.js) -PHP
Machine Learning Services A set of APIs that make it easy to deploy, manage and run machine learning models in the cloud using Internet-scale optimization and cost control features. It makes possible to train models on petabytes of data in minutes by using efficient algorithms designed specifically for large datasets.
Machine Learning Services A set of APIs that make it easy to deploy, manage and run machine learning models in the cloud using Internet-scale optimization and cost control features. It makes possible to train models on petabytes of data in minutes by using efficient algorithms designed specifically for large datasets.
The MLLib library is an open-source library for developing self-managed machine learning models in Azure ML Environment (MLE). It provides functionality such as training a model from text input or images; tuning parameters; predicting labels from inputs with multiple classes; handling missing values; analyzing logs during the training process, etc., which are important when you want to build your own inference engine without having access to any infrastructure resources like servers running Hadoop/Spark jobs, etc. For example, you could set up a Docker image to run an application on one of your web servers in the cloud, and connect it to your database server which is also running in EC2. Then you can use the AWS CLI or AWS Management Console to deploy this Docker image into production. The Azure Machine Learning API for Python is an open-source library for building self-managed machine-learning models in the cloud. It provides functionality such as training a model from text input or images; tuning parameters; predicting labels from inputs with multiple classes; handling missing values; analyzing logs during the training process etc., which are important when you want to build your own inference engine without having access to any infrastructure resources like servers running Hadoop/Spark jobs etc.
