Understanding the fundamentals of AWS is critical if you want to deploy services and resources within the AWS Cloud. The Compute category of services are key resources that allow you to carry out computational abilities via a series of instructions used by applications and systems. These resources cover a range of different services and features, these being:
- EC2 - Amazon Elastic Compute Cloud
- ECS - Amazon Elastic Container Service
- ECR - Amazon Elastic Container Registry
- EKS - Amazon Elastic Container Service for Kubernetes
- AWS Elastic Beanstalk
- AWS Lambda
- AWS Batch
- Amazon Lightsail
This course will provide the fundamental elements of all of these Compute services and features that will allow you to select the most appropriate service for your project and implementations. Each have their advantages by providing something of value that’s different to the others, which will all be discussed.
Topics covered within this course consist of:
- What is Compute: This lecture explains what 'Compute' is and what is meant by Compute resources and services
- Amazon Elastic Compute Cloud (EC2): This is one of the most common Compute services, as a result this will likely be the longest lecture as you will cover a lot of elements around EC2 to ensure you are aware of how it’s put together and how it works
- Amazon ECS (EC2 Container Service): Within this lecture you will gain a high-level overview of what the EC2 Container Service is and how it relates to Docker
- Amazon Elastic Container Registry: In this lecture you will consider how this service links closely with ECS to provide a secure location to store and manage your docker images
- Amazon Elastic Container Service for Kubernetes (EKS): Here you will look at how EKS provides a managed service, allowing you to run Kubernetes across your AWS infrastructure without having to take care of running the Kubernetes control plane
- AWS Elastic Beanstalk: This lecture will provide an overview of the service, showing you how it’s used to automatically deploy applications using EC2 and a number of other AWS services
- AWS Lambda: This lecture covers the Lambda ‘serverless’ service, where you will explore what serverless means and how this service is used to run your own code in response to events
- AWS Batch: Here you will consider a high-level overview of this service that relates to Batch Computing
- Amazon Lightsail: Finally we will look at Amazon Lightsail, a Virtual Private Server solution used for small-scale projects and use cases
If you want to learn the differences between the different Compute services, then this course is for you!
With demonstrations provided, along with links to a number of our labs that allow you to gain hands-on experience in using many of these services, you will gain a solid understanding of the Compute services used within AWS.
If you have thoughts or suggestions for this course, please contact Cloud Academy at firstname.lastname@example.org.
Resources referenced within this lecture:
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 tasks via a series of instructions. So essentially Compute is closely related to common server components, which many of you will already be familiar with, such as CPUs and RAM. With that in mind, a physical server within a data center would be considered a Compute resource, as it may have multiple CPUs and many gigs of RAM to process instructions given by the operating system and applications.
Within AWS, there are a 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, or virtual servers, which may be used continuously for months or even years, processing millions upon millions of instructions. On the other end of this scale, you may only utilize a hew hundred milliseconds of Compute resource to execute just a few lines of code within AWS Lambda before relinquishing that Compute power. AWS Lambda is a serverless Compute resource in AWS, and I'll cover more on this service later in this course. 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 will really depend on your requirements as to which Compute resource you use within AWS.
In this course, we'll discuss them all, allowing you to decide which is best for your implementation. As a quick high level reference, AWS offers a Cloud Compute Index, which can be found using the link onscreen. And this shows different examples and scenarios of where you might use different Compute deployment units. That brings me 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.
Stuart enjoys writing about cloud technologies and you will find many of his articles within our blog pages.