Common use cases of Cloud Computing

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Contents

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Introduction
1
Introduction
FREE3m 13s
How Data Center architecture is reflected in the Cloud
Overview
8
Summary
1m 47s
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Overview
DifficultyBeginner
Duration34m
Students16366
Ratings
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Description

Course Description

With a wide range of Cloud courses already available at a deep technical level, this course is aimed as an introduction to those, looking at Cloud Computing from the perspective of a beginner who may have no previous experience of the topic at all.

Before implementing or adopting Cloud technology you will want to have an understanding of what it is exactly and what options you have when thinking about your deployment. This course covers a wide range of Cloud Computing topics areas providing you with a solid foundation of understanding.

We will start by looking at what Cloud Computing is and its definition before breaking this down to understand what that definition means. We will look at the different deployment models such as Public, Private and Hybrid Clouds before digging into what actually makes a Cloud a Cloud. Here we break down the Cloud model by looking at its key concepts and characteristics that make it so appealing to a wide range of organizations and individuals.

This course also looks at the different service models of Cloud Computing, Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) providing examples and differences between each.

With all of these different deployment and service options, this course looks at ways other organizations are utilizing the Cloud with some common use cases that you may be familiar with.

Lastly, an overview is given on how typical on-premise data center solutions are reflected within the Cloud. Some people may already be aware of these solutions but are unsure of how certain infrastructure such as networks is architected from a Cloud Computing perspective. As well as networking we will also look at Storage and compute (server) resources and how these are deployed in comparison to on-premise solutions.

Learning Objectives

The key learning objectives of this course will enable to student to have:

• A clear definition of what Cloud Computing is

• A comprehensive understanding of Cloud Computing

• An understanding of Cloud Computing benefits and key concepts

• An understanding on when and where to use it using the appropriate industry models

Intended Audience

This course is intended for anyone who wants to learn about Cloud Computing, and that may have NO or very little of it knowledge of it currently. It’s for those of you who are looking to learn more about the Cloud to decide if it's something you want to adopt within your business, or those of you that may be seeking a career move and want to learn the foundation of Cloud principles, then this course is certainly for you.

• Beginners to Cloud Computing

• Business Managers

Prerequisites

• A basic understanding of server hardware components

• A basic understanding of what a Data Center is

This Course Includes

• 35 minutes of high-definition video

• 8 Lessons

• Links to key documentation by Public Cloud providers

What You'll Learn

Lesson: Introduction - This lesson provides an introduction to the trainer and covers the intended audience. We will also look at what lessons are included in the course and what you will gain as a student from attending the course.

Lesson: What is Cloud Computing? - Following this lesson the student will be able to explain what Cloud Computing is and the underlying technology that its based upon, virtualization. The student will also be aware of the primary resources of the Cloud: Compute, Storage and Network.

Lesson: Cloud Deployment Models - Following this lesson the student will know the different deployment models available and will be able to give an understanding and distinction between Public, Private and Hybrid Clouds.

Lesson: Key Cloud Concepts -  Following this lesson the student will be able to describe what makes a Cloud a Cloud and what its key characteristics and concepts are.

Lesson: Cloud Service Models - Following this lessons the student will be able to explain what Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) are and the differences between them.

Lesson: Common use cases of Cloud Computing - Following this lesson the student will have a comprehensive understanding of the different use cases cloud computing can have.

Lesson: How Data Center architecture is reflected in the Cloud - Following this lesson the student will understand how typical on premise infrastructure is architected differently within the Cloud.

Lesson: Key Points - This lesson will review all of the key points of the previous lesson.

If you have thoughts or suggestions for this course, please contact Cloud Academy at support@cloudacademy.com.

Transcript

Hello and welcome to this lecture. Looking at some of the use cases of cloud computing, and how enterprises have adopted this technology. Following the cloud concept section discussed previously you may already be thinking of some of your own uses that you could use a public cloud for. However, in this lecture I just want to cover some of the common use cases of why organizations implement cloud computing. I want to start by touching one of the bigger use cases where people migrate production services from their existing on-premise solutions into the cloud. We have discussed the benefits of the cloud, and so with all those in mind many businesses are choosing to do just that. Migrate their existing production services to the public cloud. Some companies even have all of their infrastructure within the cloud. Traffic Bursting. As an example you may experience times within the year perhaps for predicted seasonal circumstances where your infrastructure takes a heavier load impact than that of other times of the year. Perhaps you are in the retail business, and over the Christmas holiday period demand increases on your infrastructure significantly. 

In a classic data center environment you would need to provision your compute storage database, and network capacity to reflect this additional traffic, and have it take up additional space, power, and cooling all of the time. This is not an effective method of scaling not only this, but there will be additional costs for this extra infrastructure to obtain, maintain and operate, and you may only use it for a couple of months of the year. A far better method of handling this peak traffic road will be to look at cloud computing. The public cloud can be used to scale your networking resources to manage, and handle this additional traffic over your peak season. When the traffic has reduced you can then terminate your infrastructure within this cloud and stop paying for it. Remember you only pay for what you use when you use it. Backup and Disaster Recovery. 

Due to the public clouds built-in resiliency, and durability, this makes way for a great solution for your backup requirements. To a degree you have access to unlimited storage space with built-in data management lifecycle policies allowing you to make use of even cheaper storage. For example, using Amazon Web Services S3 service, you can implement a policy to archive any data that is over 30 days old to another service called AWS Glacier which is a cold storage service with an even lower storage cost. The data is still available to you for as long as you have access to the Internet. These storage services are often replicated by the vendor to ensure its durability. Couple that with a very low cost of storage, and you can see why more and more enterprises are adopting cloud computing for this very reason. Web Hosting. Many organizations choose to host their web services on the cloud due to its ability to load balance across multiple instances as well as scale up and down quickly and automatically as traffic increases and decreases with demand. The ability to provision, and implement automatic scaling simplifies the whole process and takes out much of the administrative input, and maintenance required. Not only can your web application, and database service be enhanced by design, but they can also make use of other services such as a content delivery network a CDN, and Domain Name Services DNS. 

Remember earlier when we were talking about selecting a geographic region for your instance depending on where end-users are. Well, what if you had end-users all over the world? A CDN is a set of systems which redirects traffic to the closest caching server which can deliver the content much faster. As a result a CDN can reduce the latency of a website for users across the globe if there are sufficient caching servers in place. DNS services can help to manage demand on your web servers by redirecting any requests to a load balancer first. This load balancer can then evenly distribute the requests to multiple web instances that you may have, therefore, reducing demand on a particular web server. Test and Development Environments. Similarly to our first point of traffic bursting, you may not have the capacity to hosting lots of servers, and storage in your data center for tests, and development purposes and from a financial perspective this would be a huge expense. Using the public cloud allows you to spin up instances as and when you need them, and then shut them down when finished. This also allows you to provision the size, and capacity of your compute resources say, for example, if you need a high-end powerful instance for your testing for an hour you can have it. 

It would not be financially viable for you to have this wide range of compute resource within your own data center. Proof of Concept. The cloud easily allows you to implement a proof of concept design and ideas to help bring them to life at a fraction of the cost for the reasons that I've already covered in the previous points. This includes hosting costs and only paying for what you use. The results of your proof-of-concept can help you to build a successful business case when presenting to senior management. Big Data and Data Manipulation. The cloud also makes it easier, and cheaper to manage big data. Maintaining and implementing compute resources to handle huge data sets can be expensive and complicated. By using cloud computing resources you have the ability to use only the resources you need to analyze data when you need it. Some public cloud vendors offer specialized managed Big Data services. Which gives you a managed resource infrastructure, and framework to run your workloads on, in addition to allowing for scalability, scheduling, monitoring et cetera. Having some of these elements managed by the vendor allows you to focus on the data, and processing and not worry about the maintenance, or the underlying architecture. There are many many more use cases of services within the cloud computing space, and you'll more than likely have a few ideas, or requirements of your own. Whatever you choose to do you will have the benefits of the concepts discussed earlier at your disposal. That now brings me to the end of this lecture. Coming up next I shall look at the comparisons between Data Center Architecture and that of the cloud.

About the Author

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Stuart has been working within the IT industry for two decades covering a huge range of topic areas and technologies, from data centre and network infrastructure design, to cloud architecture and implementation.

To date, Stuart has created 50+ courses relating to Cloud, most within the AWS category with a heavy focus on security and compliance

He is AWS certified and accredited in addition to being a published author covering topics across the AWS landscape.

In January 2016 Stuart was awarded ‘Expert of the Year Award 2015’ from Experts Exchange for his knowledge share within cloud services to the community.

Stuart enjoys writing about cloud technologies and you will find many of his articles within our blog pages.