Azure AZ-900 quiz with complete solutions

Cloud Computing is the delivery of computing services—servers, storage, databases, networking, software, analytics, intelligence and more—over the internet (the cloud), enabling faster innovation, flexible resources, and economies of scale. You typically pay only for cloud services you use, helping lower your operating costs, run your infrastructure more efficiently, and scale as your business needs change. Cloud provider company providing the services Cloud computing services Compute power - such as Linux servers or web applications. Storage - such as files and databases. Networking - such as secure connections between the cloud provider and your company. Analytics - such as visualizing telemetry and performance data. VMs aren't the only computing choice there are two other popular options: containers and serverless computing. Containers provide a consistent, isolated execution environment for applications. They're similar to VMs except they don't require a guest operating system. Instead, the application and all its dependencies is packaged into a "container" and then a standard runtime environment is used to execute the app. This allows the container to start up in just a few seconds, because there's no OS to boot and initialize. You only need the app to launch. Serverless computing lets you run application code without creating, configuring, or maintaining a server. The core idea is that your application is broken into separate functions that run when triggered by some action. This is ideal for automated tasks - for example, you can build a serverless process that automatically sends an email confirmation after a customer makes an online purchase. you only pay for the processing time used by each function as it executes. VMs and containers are charged while they're running - even if the applications on them are idle High availability The ability to keep services up and running for long periods of time, with very little downtime, depending on the service in question. Scalability The ability to increase or decrease resources for any given workload. You can add additional resources to service a workload (known as scaling out), or add additional capabilities to manage an increase in demand to the existing resource (known as scaling up). Scalability doesn't have to be done automatically. Elasticity The ability to automatically or dynamically increase or decrease resources as needed. Elastic resources match the current needs, and resources are added or removed automatically to meet future needs when it's needed (and from the most advantageous geographic location). A distinction between scalability and elasticity is that elasticity is done automatically. Agility The ability to react quickly. Cloud services can allocate and deallocate resources quickly. They are provided on-demand via self-service, so vast amounts of computing resources can be provisioned in minutes. There is no manual intervention in provisioning or deprovisioning services. Fault tolerance The ability to remain up and running even in the event of a component (or service) no longer functioning. Typically, redundancy is built into cloud services architecture, so if one component fails, a backup component takes its place. This type of service is said to be tolerant of faults. Disaster recovery The ability to recover from an event which has taken down a cloud service. Cloud services disaster recovery can happen very quickly, with automation and services being readily available to use. Global reach The ability to reach audiences around the globe. Cloud services can have a presence in various regions across the globe, which you and your customer can access, giving you a presence in those regions even though you may not have any infrastructure in that region. Customer latency capabilities If customers are experiencing slowness with a particular cloud service, they are said to be experiencing some latency. Even though modern fiber optics are fast, it can still take time for services to react to customer actions if the service is not local to the customer. Cloud services have the ability to deploy resources in datacenters around the globe, which addresses any customer latency issues. Predictive cost considerations The ability for users to predict the costs they will incur for a particular cloud service. Costs for individual services are made available, and tools are provided to allow you to predict the costs a service will incur. You can also perform analysis based on planned growth. Technical skill requirements and considerations Cloud services can provide and manage hardware and software for workloads. Getting a workload up and running with cloud services demands less technical resources than having IT teams build and maintain a physical infrastructure for handling the same workload. A user can be an expert in the application they want to run without requiring skills to build and maintain the underlying hardware and software infrastructure. Increased productivity On-site datacenters typically require a lot of hardware setup (otherwise known as racking and stacking), software patching, and other time-consuming IT management chores. Cloud computing eliminates the need for many of these tasks. This allows IT teams to spend time focusing on achieving more important business goals. Security Cloud providers offer a broad set of policies, technologies, controls, and expert technology skills that can provide better security than most organizations can otherwise achieve. The result is strengthened security, which helps to protect data, apps, and infrastructure from potential threats. economies of scale is the ability to reduce costs and gain efficiency when operating at a larger scale in comparison to operating at a smaller scale Capital Expenditure (CapEx) This is the up front spending of money on physical infrastructure, and then deducting that up front expense over time. The up front cost from CapEx has a value that reduces over time. Operational Expenditure (OpEx) This is spending money on services or products now and being billed for them now. You can deduct this expense in the same year you spend it. There is no up front cost, as you pay for a service or product as you use it. consumption-based model which means that end users only pay for the resources that they use. Whatever they use is what they pay for. Public Cloud is owned by the cloud services provider (also known as a hosting provider). It provides resources and services to multiple organizations and users, who connect to the cloud service via a secure network connection, typically over the internet. Public cloud models have the following characteristics Ownership - Ownership refers to the resources that an organization or end user uses. Examples include storage and processing power. Resources do not belong to the organization that is utilizing them, but rather they are owned and operated by a third party, such as the cloud service provider. Multiple end users - Public cloud modes may make their resources available to multiple organizations. Public access - Public access allows the public to access the desired cloud services. Availability - Public cloud is the most common cloud-type deployment model. Connectivity - Users and organizations are typically connected to the public cloud over the internet using a web browser. Skills - Public clouds do not require deep technical knowledge to set up and use its resources. Private Cloud is owned and operated by the organization that uses the resources from that cloud. They create a cloud environment in their own datacenter and provide self-service access to compute resources to users within their organization. The organization remains the owner, entirely responsible for the operation of the services they provide. Private cloud models have the following characteristics Ownership. The owner and user of the cloud services are the same. Hardware. The owner is entirely responsible for the purchase, maintenance, and management of the cloud hardware. Users. A private cloud operates only within one organization and cloud computing resources are used exclusively by a single business or organization. Connectivity. A connection to a private cloud is typically made over a private network that is highly secure. Public access. Does not provide access to the public. Skills. Requires deep technical knowledge to set up, manage, and maintain. Hybrid Cloud combines both public and private clouds, allowing you to run your applications in the most appropriate location Hybrid cloud models have the following characteristics Resource location. Specific resources run or are used in a public cloud, and others run or are used in a private cloud. Cost and efficiency. Hybrid cloud models allow an organization to leverage some of the benefits of cost, efficiency, and scale that are available with a public cloud model. Control. Organizations retain management control in private clouds. Skills. Technical skills are still required to maintain the private cloud and ensure both cloud models can operate together. IaaS Infrastructure as a Service. requires the most user management of all the cloud services. The user is responsible for managing the operating systems, data, and applications. PaaS Platform as a Service. requires less user management. The cloud provider manages the operating systems, and the user is responsible for the applications and data they run and store. SaaS Software as a Service. requires the least amount of management. The cloud provider is responsible for managing everything, and the end user just uses the software. Things to know about regions • Azure has more global regions than any other cloud provider. • Regions provide customers the flexibility and scale needed to bring applications closer to their users. • Regions preserve data residency and offer comprehensive compliance and resiliency options for customers. • For most Azure services, when you deploy a resource in Azure, you choose the region where you want your resource to be deployed. Things to know about regional pairs: • Physical isolation. When possible, Azure prefers at least 300 miles of separation between datacenters in a regional pair, although this isn't practical or possible in all geographies. Physical datacenter separation reduces the likelihood of natural disasters, civil unrest, power outages, or physical network outages affecting both regions at once. • Platform-provided replication. Some services such as Geo-Redundant Storage provide automatic replication to the paired region. •Region recovery order. In the event of a broad outage, recovery of one region is prioritized out of every pair. Applications that are deployed across paired regions are guaranteed to have one of the regions recovered with priority. •Sequential updates. Planned Azure system updates are rolled out to paired regions sequentially (not at the same time) to minimize downtime, the effect of bugs, and logical failures in the rare event of a bad update. Data residency refers to the physical or geographic location of an organization's data or information. It defines the legal or regulatory requirements imposed on data based on the country or region in which it resides and is an important consideration when planning out your application data storage. Availability Options • A single virtual machine with premium storage has an SLA of 99.9%. You can quickly migrate existing virtual machines to Azure through "lift and shift". Lift and shift is a no-code option where each application is migrated as-is, providing the benefits of the cloud without the risks or costs of making code changes. • By placing virtual machines in an availability set, you protect against datacenter failures and increases the SLA to 99.95%. • Adding virtual machines to availability zones protects from entire datacenter failures and increases the SLA to 99.99%, which is highest level of protection that is provided. • For multi-region disaster recovery, region pairs protect and provide data residency boundaries.