EC2 instances take longer. Lambda is “serverless,” so you can't use it to run a web server. CloudFront provides caching but isn't a web server. See Chapter 13 for more information.37 A. Almost everything in CloudFormation is case sensitive. See Chapter 14 for more information.
38 A, C. CodeDeploy looks for the appspec.yml file with the application files it is to deploy, which can be stored in S3 or on GitHub. See Chapter 14 for more information.
39 B. You can use CodeDeploy to deploy an application to Lambda or EC2 instances. But an AWS Systems Manager command document works only on EC2 instances. See Chapter 14 for more information.
Chapter 1 Introduction to Cloud Computing and AWS
The cloud is where much of the serious technology innovation and growth happens these days, and Amazon Web Services (AWS), more than any other, is the platform of choice for business and institutional workloads. If you want to be successful as an AWS solutions architect, you'll first need to understand what the cloud really is and how Amazon's end of it works.
TO MAKE SURE YOU'VE GOT THE BIG PICTURE, THIS CHAPTER WILL EXPLORE THE BASICS:
What makes cloud computing different from other applications and client‐server models
How the AWS platform provides secure and flexible virtual networked environments for your resources
How AWS provides such a high level of service reliability
How to access and manage your AWS‐based resources
Where you can go for documentation and help with your AWS deployments
Cloud Computing and Virtualization
The technology that lies at the core of all cloud operations is virtualization. As illustrated in Figure 1.1, virtualization lets you divide the hardware resources of a single physical server into smaller units. That physical server could therefore host multiple virtual machines (VMs) running their own complete operating systems, each with its own memory, storage, and network access.
FIGURE 1.1 A virtual machine host
Virtualization's flexibility makes it possible to provision a virtual server in a matter of seconds, run it for exactly the time your project requires, and then shut it down. The resources released will become instantly available to other workloads. The usage density you can achieve lets you squeeze the greatest value from your hardware and makes it easy to generate experimental and sandboxed environments.
Cloud Computing Architecture
Major cloud providers like AWS have enormous server farms where hundreds of thousands of servers and disk drives are maintained along with the network cabling necessary to connect them. A well‐built virtualized environment could provide a virtual server using storage, memory, compute cycles, and network bandwidth collected from the most efficient mix of available sources it can find.
A cloud computing platform offers on‐demand, self‐service access to pooled compute resources where your usage is metered and billed according to the volume you consume. Cloud computing systems allow for precise billing models, sometimes involving fractions of a penny for an hour of consumption.
Cloud Computing Optimization
The cloud is a great choice for so many serious workloads because it's scalable, elastic, and, often, a lot cheaper than traditional alternatives. Effective deployment provisioning will require some insight into those three features.
Scalability
A scalable infrastructure can efficiently meet unexpected increases in demand for your application by automatically adding resources. As Figure 1.2 shows, this most often means dynamically increasing the number of virtual machines (or instances as AWS calls them) you've got running.
FIGURE 1.2 Copies of a machine image are added to new VMs as they're launched.
AWS offers its autoscaling service through which you define a machine image that can be instantly and automatically replicated and launched into multiple instances to meet demand.
Elasticity
The principle of elasticity covers some of the same ground as scalability—both address how the system manages changing demand. However, though the images used in a scalable environment let you ramp up capacity to meet rising demand, an elastic infrastructure will automatically reduce capacity when demand drops. This makes it possible to control costs, since you'll run resources only when they're needed.
Cost Management
Besides the ability to control expenses by closely managing the resources you use, cloud computing transitions your IT spending from a capital expenditure (capex) framework into something closer to operational expenditure (opex).
In practical terms, this means you no longer have to spend $10,000 up front for every new server you deploy—along with associated electricity, cooling, security, and rack space costs. Instead, you're billed much smaller incremental amounts for as long as your application runs.
That doesn't necessarily mean your long‐term cloud‐based opex costs will always be less than you'd pay over the lifetime of a comparable data center deployment. But it does mean you won't have to expose yourself to risky speculation about your long‐term needs. If, sometime in the future, changing demand calls for new hardware, AWS will be able to deliver it within a minute or two.
To help you understand the full implications of cloud compute spending, AWS provides a free Total Cost of Ownership (TCO) Calculator at aws.amazon.com/tco-calculator. This calculator helps you perform proper “apples‐to‐apples” comparisons between your current data center costs and what an identical operation would cost you on AWS.
The AWS Cloud
Keeping up with the steady stream of new services showing up on the AWS Console
