AZ-900 Certification Notes

Chapter 9.7 - Azure Solutions Quiz

Question 1

• Which is a valid Internet of Things service on Azure?
  • IoT App Services
  • IoT Management Studio
  • IoT Services
  • IoT Central

IoT Central is a valid Azure service for Internet of Things. It provides a fully managed global IoT software as a service (SaaS) solution that makes it easy to connect, monitor, and manage your IoT assets at scale.

Question 2

• What is the best definition of Azure DevOps?
  • A suite of five different tools to create more robust software, faster
  • A specific section of the Azure portal where you can manage operational parts of your infrastructure
  • A way to write better code and find bugs faster
  • A platform to manage Azure resources meant for development, such as App Services, Azure Functions, and Visual Studio Online.

Azure DevOps is a set of modern tools to create more robust software, faster. It is used by both operational people and developers to manage the entire lifecycle of software products. It has its own separate web portal, but it is fully integrated into Azure. It isn't only meant for development services on Azure but all services to which you can deploy code and infrastructure.

Question 3

• Which of the following is a tool in Azure DevOps?
  • Azure Operations
  • Automation
  • Azure Pipelines
  • Azure Deployment

Azure Pipelines is a service in Azure DevOps that helps you to build, test, and deploy your code. It is one of the five services in Azure DevOps.

Question 4

• Which of the following are valid Internet of Things services on Azure?
  • IoT App Services and IoT Virtual Box
  • IoT Central and IoT App Services
  • IoT Services and IoT Management Studio
  • IoT Central and IoT Hub

Azure provides many services for Internet of Things, two of which are IoT Hub and IoT Central.

Question 5

• What is a primary use case for Azure Logic Apps?
  • To perform fundamental compute actions that can be run millions of times per second.
  • To schedule, automate, and orchestrate tasks and processes
  • To perform single tasks that run once every time they are invoked.
  • To manage multiple Azure subscriptions simultaneously.

Azure Logic Apps are primarily used to schedule, automate, and orchestrate tasks and processes. They provide a way to simplify and implement scalable integrations and workflows in the cloud.

Question 6

• Which of the following is NOT a tool in Azure DevOps?
  • Azure Automation
  • Azure Artifacts
  • Azure Boards
  • Azure Pipelines

Azure Automation is not a valid tool in Azure DevOps.

Question 7

• Which of the following best represents a set of tools in Azure DevOps?
  • Azure Artifacts, Azure Boards, and Azure Pipelines
  • Azure Artifacts, Azure Boards, and Azure Operations
  • Azure Automation, Azure Boards, and Azure Pipelines
  • Azure Artifacts, Azure Deployment, and Azure Pipelines

Azure DevOps includes five services: Boards for managing and tracking projects; Azure Pipelines for building, testing, and deploying projects; Azure Repos for storing and managing code; Azure Test Plans for conducting manual tests and automating tests; and Azure Artifacts for hosting and sharing packages to share functionality across teams. Azure Artifacts, Azure Boards, and Azure Pipelines are all part of these services.

Question 8

• What is the purpose of "models" in machine learning and artificial intelligence?
  • The framework for integrating other Azure services with your particular machine learning instance
  • The definition of what you want your machine learning implementation to learn
  • The size and capacity of the machine learning service
  • Defining the version of your machine learning application

A model is the way you define what you want your machine learning implementation to learn. You give it a model, which is a set of rules, and the application then starts playing this model over and over again with the data you have provided. Over time, usually very fast, the model will find patterns in the data that follow the rules you have provided.

Question 9

• Which of the following is NOT a likely outcome from using Azure Data Lake Analytics to analyze big data?
  • More secure access to company infrastructure.
  • Better decision-making from immediate analysis.
  • A cost reduction on data storage.
  • Creating products better aligned to customer needs.

This is not a likely outcome from using Azure Data Lake Analytics. Azure Data Lake Analytics is a service for analyzing big data, it does not inherently provide more secure access to company infrastructure.