Describe core solutions and management tools on Azure Flashcards
Internet of Things (IoT) Hub
IoT Hub is a managed service hosted in the cloud that acts as a central message hub for communication between an IoT application and its attached devices. You can connect millions of devices and their backend solutions reliably and securely. Almost any device can be connected to an IoT Hub.
Several messaging patterns are supported, including device-to-cloud telemetry, uploading files from devices, and request-reply methods to control your devices from the cloud. IoT Hub also supports monitoring to help you track device creation, device connections, and device failures.
IoT Hub scales to millions of simultaneously connected devices and millions of events per second to support your IoT workloads. For more information about scaling your IoT Hub, see IoT Hub Scaling. To learn more about the multiple tiers of service offered by IoT Hub and how to best fit your scalability needs, check out the pricing page.
You can integrate IoT Hub with other Azure services to build complete, end-to-end solutions. For example, use:
Azure Event Grid to enable your business to react quickly to critical events in a reliable, scalable, and secure manner.
Azure Logic Apps to automate business processes.
Azure Machine Learning to add machine learning and AI models to your solution.
Azure Stream Analytics to run real-time analytic computations on the data streaming from your devices.
IoT Central applications use multiple IoT hubs as part of their scalable and resilient infrastructure.
IoT Hub has a 99.9% Service Level Agreement for IoT Hub. The full Azure SLA explains the guaranteed availability of Azure as a whole.
IoT Central
IoT Central is an IoT application platform that reduces the burden and cost of developing, managing, and maintaining enterprise-grade IoT solutions. Choosing to build with IoT Central gives you the opportunity to focus time, money, and energy on transforming your business with IoT data, rather than just maintaining and updating a complex and continually evolving IoT infrastructure.
The web UI lets you quickly connect devices, monitor device conditions, create rules, and manage millions of devices and their data throughout their life cycle. Furthermore, it enables you to act on device insights by extending IoT intelligence into line-of-business applications.
Azure Sphere
Azure Sphere are services and products from Microsoft that allows vendors of Internet of Things devices to increase security by combining a specific system on a chip, Azure Sphere OS and an Azure-based cloud environment for continuous monitoring.
Azure Synapse Analytics
Azure Synapse is an enterprise analytics service that accelerates time to insight across data warehouses and big data systems. Azure Synapse brings together the best of SQL technologies used in enterprise data warehousing, Spark technologies used for big data, Data Explorer for log and time series analytics, Pipelines for data integration and ETL/ELT, and deep integration with other Azure services such as Power BI, CosmosDB, and AzureML.
HDInsight
Azure HDInsight is a managed, open-source, analytics, and cloud-based service from Microsoft that can run both on the cloud as well as on-premises and provide customers broader analytics capabilities for big data. This helps organizations process large quantities of streaming or historical data.
Azure Databricks
Azure Databricks is a data analytics platform optimized for the Microsoft Azure cloud services platform. Azure Databricks offers three environments for developing data intensive applications: Databricks SQL, Databricks Data Science & Engineering, and Databricks Machine Learning.
Databricks SQL provides an easy-to-use platform for analysts who want to run SQL queries on their data lake, create multiple visualization types to explore query results from different perspectives, and build and share dashboards.
Databricks Data Science & Engineering provides an interactive workspace that enables collaboration between data engineers, data scientists, and machine learning engineers. For a big data pipeline, the data (raw or structured) is ingested into Azure through Azure Data Factory in batches, or streamed near real-time using Apache Kafka, Event Hub, or IoT Hub. This data lands in a data lake for long term persisted storage, in Azure Blob Storage or Azure Data Lake Storage. As part of your analytics workflow, use Azure Databricks to read data from multiple data sources and turn it into breakthrough insights using Spark.
Databricks Machine Learning is an integrated end-to-end machine learning environment incorporating managed services for experiment tracking, model training, feature development and management, and feature and model serving.
Azure Machine Learning
Azure Machine Learning (Azure ML) is a cloud-based service for creating and managing machine learning solutions. It’s designed to help data scientists and machine learning engineers leverage their existing data processing and model development skills & frameworks.
Azure Cognitive Services
Azure Cognitive Services is a machine-learning service from Microsoft that brings AI within the reach of developers. Through a set of machine learning algorithms developed by Microsoft, you can solve all kinds of problems in the realm of Artificial Intelligence. Learn how to use Cognitive Services through an API call that embeds the ability to see, hear, speak, search, understand and accelerate decision making into your apps. Azure Cognitive Services helps reach human level parity in computer vision, speech, and language. And best of all, no machine-learning expertise is required to get started.
Azure Bot Service
Azure Bot Service is a managed bot development service that helps you seamlessly connect to your users via popular channels. Pay only for messages delivered using Premium channels, which allow your bot to communicate with users within your own application or on your website.
Azure Functions
Azure Functions is a cloud service available on-demand that provides all the continually updated infrastructure and resources needed to run your applications. You focus on the pieces of code that matter most to you, and Functions handles the rest. Functions provides serverless compute for Azure. You can use Functions to build web APIs, respond to database changes, process IoT streams, manage message queues, and more.
Azure Logic Apps
Azure Logic Apps is a cloud-based platform for creating and running automated workflows that integrate your apps, data, services, and systems. With this platform, you can quickly develop highly scalable integration solutions for your enterprise and business-to-business (B2B) scenarios. As a member of Azure Integration Services, Azure Logic Apps simplifies the way that you connect legacy, modern, and cutting-edge systems across cloud, on premises, and hybrid environments.
The following list describes just a few example tasks, business processes, and workloads that you can automate using the Azure Logic Apps service:
Schedule and send email notifications using Office 365 when a specific event happens, for example, a new file is uploaded.
Route and process customer orders across on-premises systems and cloud services.
Move uploaded files from an SFTP or FTP server to Azure Storage.
Monitor tweets, analyze the sentiment, and create alerts or tasks for items that need review.
Azure DevOps
Azure DevOps provides developer services for allowing teams to plan work, collaborate on code development, and build and deploy applications. Azure DevOps supports a culture and set of processes that bring developers, project managers, and contributors together to collaboratively develop software. It allows organizations to create and improve products at a faster pace than they can with traditional software development approaches.
You can work in the cloud using Azure DevOps Services or on-premises using Azure DevOps Server. For information on the differences between the cloud versus on-premises platforms, see Azure DevOps Services and Azure DevOps Server.
Azure DevOps provides integrated features that you can access through your web browser or IDE client. You can use one or more of the following standalone services based on your business needs:
Azure Repos provides Git repositories or Team Foundation Version Control (TFVC) for source control of your code. For more information about Azure Repos, see What is Azure Repos?.
Azure Pipelines provides build and release services to support continuous integration and delivery of your applications. For more information about Azure Pipelines, see What is Azure Pipelines?.
Azure Boards delivers a suite of Agile tools to support planning and tracking work, code defects, and issues using Kanban and Scrum methods. For more information about Azure Boards, see What is Azure Boards?.
Azure Test Plans provides several tools to test your apps, including manual/exploratory testing and continuous testing. For more information about Azure Test Plans, see Overview of Azure Test Plans
Azure Artifacts allows teams to share packages such as Maven, npm, NuGet, and more from public and private sources and integrate package sharing into your pipelines.
GitHub
GitHub is a code hosting platform for version control and collaboration. It lets you and others work together on projects from anywhere
GitHub Actions
GitHub Actions is a continuous integration and continuous delivery (CI/CD) platform that allows you to automate your build, test, and deployment pipeline. You can create workflows that build and test every pull request to your repository, or deploy merged pull requests to production.
Azure DevTest Labs
Azure DevTest Labs is a service that enables developers to efficiently self-manage virtual machines (VMs) and Platform as a service (PaaS) resources without waiting for approvals. DevTest Labs creates labs consisting of pre-configured bases or Azure Resource Manager templates. These labs have all the necessary tools and software that you can use to create environments.
By using DevTest Labs, you can test the latest versions of your applications by doing the following tasks:
Quickly create Windows and Linux environments by using reusable templates and artifacts.
Easily integrate your deployment pipeline with DevTest Labs to create on-demand environments.
Scale up your load testing by creating multiple test agents and pre-prepared environments for training and demos.