Compute resources are the brains (CPU) and brawn (RAM) required by applications and systems to complete computations through multiple instructions. Think of a physical server within a data center. This would be considered a compute resource; its CPUs and RAM complete tasks directed by the operating system and applications.
In this lecture, we will discuss the AWS compute options from both ends of the spectrum including:
- EC2 virtual servers—hundreds of instances running continuously for months or years processing millions of instructions
- Lambda deployments—milliseconds to execute a few lines of code before releasing the resources back for other uses.
Additional features such as elastic load balancing (ELB) and auto scaling give control and management of compute resources used by the other services.
By the end of the lecture, you will see that compute resources are available in multiple quantities for varying lengths of time spanning a wide range of categories offering performance and benefit options.
Hello and welcome to this very short lecture where we are going to answer the question: what is compute in AWS?
Before we begin to explore compute services resources and features we must first understand what is meant by the term compute. So what is it? Put simply compute resources can be considered the brains and processing power required by applications and systems to carry out computational abilities via a series of instructions.
So essentially compute is closely related to common server components which many of you will be more familiar with. Such as central processing units - CPU's and random access memory - RAM. With that in mind a physical server within a data center would be considered a compute resource as it may have multiple CPU's and many gigs of RAM to process instructions given by the operating system and applications.
Within AWS there are number of different services and features that offer compute power to provide different functions. Some of these services provide compute which can comprise of utilizing hundreds of EC2 instances virtual servers which may be used continuously for months or even years processing millions upon millions of instructions. On the other end of the scale you may need to utilize a few hundred milliseconds of compute resource to execute just a few lines of code within Lambda before relinquishing that compute power. Lambda is a compute resource in AWS which we'll cover later in this course.
Other features as elastic load balancing, ELB and auto scaling which will be discussed in more detail in a later lecture do not actually function as compute resources themselves. Rather they allow you to control and manage the amount of compute resource used by other services. Such as EC2 whilst maintaining high availability of your EC2 fleet of resources.
As you can see compute resources can be consumed in different quantities for different lengths of time across a range of categories offering a wide scope of performance and benefit options. So it really will depend on your requirements as to which compute resource you use within AWS and this course will discuss them all allowing you to decide which is best for your implementation. That brings us to the end of this very short lecture.
Now we are aware of what compute is let's start by looking at some of the services offered by AWS that provide this compute resource starting with elastic cloud compute; EC2.
Stuart has been working within the IT industry for two decades covering a huge range of topic areas and technologies, from data center and network infrastructure design, to cloud architecture and implementation.
To date, Stuart has created 150+ courses relating to Cloud reaching over 180,000 students, mostly within the AWS category and with a heavy focus on security and compliance.
Stuart is a member of the AWS Community Builders Program for his contributions towards AWS.
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.
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