Information technologies have evolved significantlyÂ over the last decade. For those of us in the professions of creating, building, and developing within these changes, cloud computing is one of the fastest-growing areas in our world. Cloud is the keyword of our new age, and it will be a fundamental part of everything in our future.
As an IT professional, I believe that being successful in IT is really about being a lifelong student, which means that we must constantly learn new skills and different platforms. Thus, this exam guide is not only a tool to help IT professionals get certified, but it will also to help them to get hands-on experience through practice labs. I would love to share my experience on how to build our knowledge of Microsoft Azure from the conceptual level to the operational level.
It has been several years since Microsoft started its Microsoft Certified Professional (MCP) program. The MCP program provides a great way to enable IT professionals and developers acquire an industry-recognized certification by passing a specific exam so that they can validate their technical expertise in this area.
Each exam has its own official outline in the Register for an exam page (You can find all the eligible Microsoft exam at this link:Â https://www.microsoft.com/en-us/learning/exam-list.aspx), Most topics will be covered in each Microsoft certification is mentioned in the outline of each exam,Â for each for the certification 70-533, all the related topics Â are indicated at https://www.microsoft.com/fr-fr/learning/exam-70-533.aspx.
Generally, the Microsoft certification contains 40 to 60 questions, depending on the knowledge domain and difficulty level of the exam. There are different types of questions in the exam such as build list, case studies, drag and drop, and multiple choice. If you want to know how to register and possible exam formats or questions types, you can check here atÂ https://www.microsoft.com/en-us/learning/certification-exams.aspx. The qualified candidates should score more than 70% for each exam to get certified successfully.
A Microsoft Certification title doesn't expire over time but it can be marked with the year that you archived it, and every year ( start from 365 days of the date you validated your exam )Â you can repass the selective exam to renew your title. Microsoft Learning provides a certification planner in which you can track your status, acquired certification, and additionally a couple of proposed options to help MCPs complete different potential paths and to achieve the target title.
Microsoft updates and retires certifications every year; check your Microsoft Learning transcript regularly to keep an eye on the status of your certifications.
Cloud computing has been a star since it was born; it appears with big data, Internet of Things (IoT), and Artificial Intelligence (AI) in our conversations. There are so many definitions of cloud computing in different MOOC courses and official documentation of different public cloud providers.
To explain it in a simple way, the cloud is the internet and the cloud providers provide different services via the cloud. A famous example is Apple providing an online storage service, which is known as iCloud, that lets users store their files, videos, pictures, and so on, in the cloud.
Modern cloud computing services providers such as AWS, Microsoft Azure, and Google Cloud Platform, generally consist of four basic components: compute, network, database, and storage. These providers provide computer services such as virtual machine, storage services to store objects/files on the cloud, provide the different cloud-based databases to store data, and network service to deploy virtual networks. Nowadays, the popular cloud providers seem more ambitious than we thought they were. They don't limit themselves to act as infrastructure that supports application deployments but they also provide the management services to supportÂ DevOps, monitoring, logging, and alarming, backup andÂ restoreÂ in time on the cloudÂ and integration tools to build CI/CD pipelines.Â More and more, it provides advanced services support such as the ETL (extract, transform and load) processing and data analytics, Machine Learning (ML), AI, and also IoT services to communicate with IoT devices. Theoretically, cloud computing technology can help us do everything we want in the cloud.
Predominantly, cloud computing is built into three types of cloud computing service models: Infrastructure as a Service(IaaS), Platform as a Service(PaaS),andSoftware as a Service(SaaS). Each service offering provides a different level of virtualization and management responsibilities. The following is a screenshot showing which responsibilities each service model provides for:
Different cloud computing service models
As shown in the preceding screenshot, the IaaS service model provided is generally the capability of infrastructure level to the users; the cloud providers managed the hardware and infrastructure such as virtual servers, storage, networks, connectivity, operating systems and other fundamental computing resources. Based on the IaaS offering, users should manage them with administration works such as installing the patches, updates, and configurations. One of the best examples of this model is the virtual machine in the cloud.
The PaaS services model provides the capability that comprises deployed and configured IT resources in a ready state based on the IaaS model. Users don't need to care about the infrastructure level and even the administration work they face when they're in the IaaS model. It directly provides the environment with the specified runtime. What users need to do is focus their work on the application level. An example of this is where Microsoft Azure provides a .NET / Node.js / PHP runtime in-app service, which we'll explain in Chapter 5, Designing and Implementing Azure App Service Apps.
Compared to PaaS, SaaS has a more advanced virtualization level, which is widely accessed over the internet and directly used by users. The most common example is Google's G Suite and Microsoft's Visual Studio Team Services (which is also known as Visual Studio Online or VSTS).
Based on these models, there are also some extension concepts which are known as X as a service such as:
- Database as a Service (DBaas): A managed database service in the cloud that aims to offer the database layer to the applications; the cloud provider manages the complex database environments.
- Container as a Service (CaaS): A managed service model that provides the container-based virtualization technology to let users manage and deploy containers; and applications as well as container clusters in the cloud.
- Messaging as a Service (MaaS): A messaging service in the cloud that allows sending and receiving messages through a queue. Originally implemented for the purpose of resolving queue-based load-leveling problems for a service whose peaks in demand make services or applications in the cloud overload and therefore unable to respond to requests in a timely manner. The queue acts as a buffer, storing the message until itâs retrieved by the service. Applications or services in the cloud retrieve the messages from the queue and process them.
- Logic as a Service (LaaS): Also known as serverless. It gives little control over the infrastructure, the related infrastructure is managed by the cloud providers, and users can focus themselves on coding and configuring settings. Great examples include Azure Functions and Azure Logic Apps.
- Identity as a service (IDaaS): Supplies cloud-based authentication or identity management to enterprises or organizations. The goal is to ensure if a user has access to cloud applications or services and which type of access they could have to cloud applications or services.
There are some other serviceÂ models such as Disaster Recovery as a Service (DRaaS), Data as a Service (DaaS), Big Data as a Service (BDaaS), Log as a Service (LaaS), and more thanÂ the mentioned models here. We believe, as cloud computing is one of the fastest-growing technologies, more and more services will appear and may serve together for future cloud computing platforms.
Typically, within cloud computing, it is possible to build our model as one of the four types of cloud deployment model: public cloud, private cloud, hybrid cloud, and community cloud. Each of them is defined for different levels of management, such as where the IT resource is located and security reasons.
The public cloud is a publicly accessible cloud environment provided by a cloud provider such as Microsoft Azure, Amazon Web Service (AWS), or Google Cloud Platform ( GCP ). These platforms manage the IT resources in their data center and are responsible for the security of these IT resources. With the help of the Internet, users can access cloud services on the public cloud from anywhere around the world. The following is an image showing how the public cloud works:
As compared to the public cloud, aÂ private cloud is more critical in security and can only be accessed it from the internal network where the infrastructure is hosted. IT resources in private clouds are managed by companies' or organizations' own data center. Users can access it only when they're on the internal network. The following is an image showing how aÂ privatecloudworks:
Based on the public cloud and private cloud, aÂ hybrid cloud is intended to combine both of them in the same scenario. Generally, a network connection (dedicated or private) should be established between the private cloud and the public cloud. Hence, it is important to define which IT resources are on-premises and in the cloud and how do they work together. Be careful, as a hybrid cloud is intended to be for short-term configurations. If we are in a transition stage, a hybrid cloud is the most common cloud deployment model. The following is an image showing how a hybridcloud works:
A community cloud is similar to a public cloud, but it is intended to be limited to a specific member of the community (or authorized access by the community); the IT resources can be located in the community's data center and shared by several members. The general scenario is several applications consume the common IT resources, but in this context, the community cloud usually ensures a dedicated connection between each consumer and IT resource, as illustrated in the following diagram:
The reasons why cloud computing acts as a booster for our business today is variable. However, the main reasons are as follows:
- Agility and scalability: Cloud provides a simple way to provide the underlying infrastructure for different types of applications. Itâs easy to scale up and scale down, for its cloud capacity with high agility and scalability which is one of the greatest features that makes cloud computing different from the traditional way when we're working on-premise.
- Cost-effective: Cloud computing provides IT resources in the cloud. It cuts down operational costs as compared to the traditional way. Most cloud providers allow pay as you go or another way to say it:Â pay for use as pricing solutions. Different sizes of business organizations will only pay for what they've consumed; it will cut down cost in a significant way when a cloud solution is applied to an organization, which is architecturally sound and cost-effective.
- Disaster recovery: Cloud makes the deployment of identical IT resources and data replication in a simple way, and provides multiple ways to implement cloud-based or hybrid backup and recovery solutions across the region, which reduce the risk in case of disaster and facilitate a great way to minimize the downtime.
- Global accessible: Cloud makes the deployment of the application in multiple regions around the world in an easy way. Users can access the public cloud from anywhere in the world once they've got an internet connection.
- Consider implementing with resilience: The cloud-native application is intended to be loosely coupled. This is the reason why the 12-factor app, which was first presented by Adam Wiggins in 2011, is becoming more and more popular while designing cloud-native applications. While designing IT resources in the cloud, try to design it a way so that each resource can be scaled independently to reduce downtime; applications with more portability and resilience can be recovered in time.
- Consider implementing with high availability: While implementing cloud-based infrastructure, always consider the availability of applications, replicating identical infrastructure in another data center, which is nearest and can provide higher availability rather than deploying to a single data center. A load-balancer policy can be implemented to fail over to the secondary data center to reduce downtime and risk. For example, the most widely used deployment strategy to reduce downtime is blue/green deployment and canary releases.
- Consider implementing disaster recovery strategy: While implementing cloud-based infrastructure, you also need to consider the strategy to achieve your recovery time objective (RTO) and recovery point objective (RPO). Designing an appropriate DR strategy when working with cloud backup and recovery services is pretty important.
- Consider implementing themonitoringstrategy: While implementing a cloud-based infrastructure, you also need to consider the strategy so that you can have a comprehensive vision of each resource to detect issues, problems, and take actions in a short time. Cloud-monitoring tools provide metrics and analysis, which are also great decision-support tools that provide a better understanding of the state of your application and the working condition of your infrastructure.
The adoption of cloud computing has become a key driving force to boost the fast-growing business of today. According to Google statistics in 2017, 5% of enterprises all over the world are going to move out of on-premise data centers to public cloud for the sake of saving costs and especially to increase the agility and scalability of their enterprise-level applications.
Mission-critical systems such as e-commerce websites, real-time transaction systems working with banking, stocks, and other financial institutions send a special request to public cloud providers to invest huge efforts to improve the security, high availability, and disaster recovery services. Until today, the cloud computing arena has largely been addressed by the big three public cloud vendors: Amazon Web Service (AWS), Microsoft Azure, and Google Cloud Platform (GCP). There are also some open source private cloud providers such as OpenStack, Apache CloudStack, VMware vCloud Suite, RedHat OpenShift, and so on.
Microsoft Azure was announced in October 2008 and then released on February 1, 2010 as Windows Azure. By March 25, 2014, it was renamed Microsoft Azure. The Microsoft Azure public cloud platform offers IaaS, PaaS, and SaaS services to enable businesses worldwide to create, deploy, and operate cloud-based applications and infrastructure services.
One of the reasons why Microsoft Azure is popular and fast-developing in the current market is because it is easy to work along with other Microsoft solutions such as Microsoft System Center, and can be leveraged together to extend an organization's current data center into a hybrid cloud that expands capacity and provides capabilities beyond what could be delivered solely from an on-premises standpoint.
The exam 70-533 focuses on implementing the Azure cloud solutions by taking advantage of different IaaS or PaaS offerings. The best way to prepare yourself is starting from the skills measured for 70-533 exam (refer to the URL https://www.microsoft.com/en-us/learning/exam-70-533.aspx to see the details).
This book will not only guide you to pass 70-533 certification successfully but also help readers to realize the transition from a beginner to an expert on Microsoft Infrastructure solutions. This book will cover all the topics that will appear in the real exam. Each chapter will start with explaining the basics in a conceptual view, help you to build your content knowledge on each topic, and then dive into the practical demonstration. Finally, there will be reflection questions to simulate the real-world scenario. I believe in learning by doingâhands-on is the key. I recommend getting your hands dirty with every demo in each chapter while reading this book to make sure you really understand them. I hope after studying in depth with this book, you will be confident to achieve great results in your upcoming exam.
In this chapter, we saw the three most widely used public cloud providers: Amazon Web Service (AWS), Microsoft Azure, and Google Cloud Platform (GCP). We also learned about the four basic components: compute, network, database, and storage for a cloud computing platform and the three cloud computing service models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Then we saw the four cloud computing deployment models: public cloud, private cloud, hybrid cloud, and community cloud. Then we looked into the things that we should consider while implementing cloud-based infrastructure services like resilience, high availability, disaster recovery, and monitoring strategy.
In the upcoming chapter, Chapter 2,Â Overview of Microsoft Azure, we will be looking in more depth at Microsoft Azure which is the most important cloud provider that we cover in the book.