Compute Services in AWS

Name: Compute Services in AWS
Author: Demetria Crawford

Learn the AWS services for computation.

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Course: On-Demand

Hello, my name is Demetria Crawford. And in this lesson, we will review the AWS Compute Basics. First, let's talk about the components required for computation from a computer. We have the central processing unit, the CPU, which is the brains of your computer. It does all the thinking, or in this case, processing, for you. We have RAM, random access memory, which stores the active functions or applications which are waiting to be processed by the CPU. Next is storage, we typically use hard drives or some form of storage, such as external disks. These are the same components required for cloud computation or virtualization. When creating instances such as EC2s, you will configure the amount of each of these items. Let's take a look at some of the AWS Computation services. Now, I mentioned EC2s, which is the Amazon Elastic Cloud Computing or Elastic Compute Cloud, EC2s. It is a web service that provides secure, resizable compute capacity in the cloud. It's designed to make web-scale computing easier for developers. Now, when we take a look at the various type of EC2s, the first thing you'll have to be able to identify is what type or instance type you would like to use. In this case, we're saying, how many CPUs would you like to use? What type of architecture, i386 or x86? How much memory or RAM? What type of storage? These are all some of the things you would have to configure with EC2s, which we'll get more detailed into in further lessons. Next, we have containers as a form of compute services. Amazon ECS, or rather, Amazon Elastic Container Service, is a fully managed container orchestration service that makes it easy for you to deploy, manage, and scale containerized applications. So what we do when we're using containers is we are decoupling or minimizing the size of applications. We're taking the application apart and putting it into pieces, and each of those pieces will have its own container such that it helps you to manage those parts and pieces. For example, if you have an application that has to have updates or patch management done to different pieces of that application, to minimize the effects of this, you can apply these changes just to specific parts or the containers themselves. So with Amazon Elastic Container Service, you can define your application, select the container images and resources needed for your application, then apply the compute options. You can launch containers on various supported compute services, and then you simply manage those containers. Amazon, ECS scales your application and manages your containers for availability. Next, we have Serverless Service. With AWS Serverless Service, we are using the AWS Lambda Service. Lambda lets you run code without provisioning or managing servers. You pay only for the compute time you consume, there is no charge when your code is not running. With Lambda, you can run code for virtually any type of application or backend service, all with zero administration. Let's take a look at an example. So let's say you take a photograph and you place a copy of this photograph into a Amazon S3 bucket for storage. Something has to trigger Lambda or a Serverless Service to actually function. In this case, whenever a photo is placed in the bucket, Lambda is triggered to resize this image so that it will fit based off of the device that is accessing it. So AWS Lambda runs the image-resizing code once triggered, and then the photo is resized into web, mobile, or tablet sizes. In this case, there are no servers running for you, the customer. There are servers in the background, but that's at the AWS or Amazon facility that runs this. It's more like a script, so consider it a script that is ran when triggered. So for you, the customer, computation is happening, but you don't have to have a server or EC2 just to run this particular action or make this action happen. So it saves you cost and administration time because the only time that this service computes or computation is happening is if it's triggered. So you're not paying for a constant use of a server that's not being used at all times. Next, we have Edge and Hybrid. Now, with Edge and Hybrid, these are services that we use to minimize latency and to make sure that we're getting the best functionality based off of our location, our needs at our on-premise location, and the services that we're using from AWS. So in this case, you may use or run servers on your location while also using services that are within the cloud, within AWS. For example, storage, you may use the AWS Snow Family to collect and process data in a disconnected Edge environment. So you may have some data that is stored for longer period of time that you may want to keep in a vault, whereas data stores that you use on a regular basis, you may wanna have on premises. So we have the option to use both Edge and Hybrid resources from AWS. Now finally, we have our cost and management computation services. Now, in this case, we are not creating servers or specific computation. We're managing computation, we're managing the availability and the capacity levels of our computation services. There are two main services that we use for this, we have Auto Scaling and we have Elastic Load Balancing. Auto Scaling helps you maintain application availability and allows you to automatically add or remove EC2 instances according to conditions you define. You can use the Fleet Management feature of Amazon EC2 Auto Scaling to maintain the health and availability of your fleet. Next is Elastic Load Balancing, which automatically distributes incoming application traffic across multiple targets and virtual appliances in one or more availability zones. A perfect example of this is the use of web servers. So let's say we have 10 web servers, we don't want all of the traffic coming to one server. All of the workload on one server is not good use of the remaining nine. So with Elastic Load Balancing, it makes sure that the workload, the traffic, spans across all servers. So it tells the traffic where to go based off of the health of the web servers. And we could say based off of location, based off of the content, based off of the servers that it's previously used before, so sticky sessions. So we have a lot of different ways that we can manage the traffic based off of our needs. This helps to provide high availability, and it also is a good use of our servers that we have available through AWS. Stay tuned for the next lesson where we will review the AWS Elastic Compute Cloud. Thanks for watching.

Beginner Provider : Demetria Crawford 6 Lessons · 40m in Arabic, German, English, Spanish, French, Portuguese, Chinese

Course Description

Amazon Web Services provide virtualization and serverless solutions for computation services in the cloud. Reliable and scalable infrastructure on demand allows the creation of servers at a fast past whenever the need arises. The creation of virtual servers provides on demand computation in the cloud. The time required to build infrastructure to support databases and applications is minimized providing organizations with higher benefits and efficiency than an on-premise infrastructure. As a cloud administrator, understanding the available computation services provided by Amazon Web Services is critical to designing an efficient and secure cloud solution.

In this course, you will discover the various AWS computation services as well as the components required to build a virtual server. You’ll learn how to create Elastic Cloud Compute instances with cloud attached storage. You'll be introduced to the tools used to support Elastic Cloud Compute instances, such as Elastic Load Balancers and Auto Scaling.

What You'll Learn

Identify cloud computation basics and the components required to build a virtual server
Explain Elastic Compute Cloud (EC2) and create EC2 instances with cloud-attached storage
Review the AWS services used to support high availability
Configure Elastic Load Balancers to support EC2 instances
Set up AWS Auto Scaling for EC2 instances
Describe the virtualization and serverless solutions AWS provides for computation in the cloud

Key Takeaways

Amazon Web Services provides virtualization and serverless solutions for computation services in the cloud.
Reliable and scalable on-demand infrastructure allows servers to be created quickly whenever the need arises.
Creating virtual servers minimizes the time required to build infrastructure for databases and applications, offering organizations higher efficiency than on-premise infrastructure.
Elastic Load Balancers and Auto Scaling are tools used to support Elastic Compute Cloud (EC2) instances.
Understanding the available AWS computation services is critical for a cloud administrator designing an efficient and secure cloud solution.

Frequently Asked Questions

Who is this course for?

It is aimed at cloud administrators, for whom understanding the computation services provided by Amazon Web Services is critical to designing an efficient and secure cloud solution.

What AWS compute services does this course cover?

The course covers AWS compute basics, Elastic Compute Cloud (EC2), Elastic Load Balancer (ELB), and Auto Scaling, along with the components required to build a virtual server.

What skills will I gain from this course?

You will learn to create Elastic Compute Cloud (EC2) instances with cloud-attached storage and to use the tools that support EC2 instances, such as Elastic Load Balancers and Auto Scaling. Related skills include Amazon Elastic Compute Cloud, AWS Lambda, AWS SDK, and Cloud Services.

How is the course structured?

The course is organized into six lessons: AWS Compute Basics; AWS Elastic Compute Cloud (EC2); AWS Elastic Load Balancer (ELB) Part 1 and Part 2; and AWS Auto Scaling Part 1 and Part 2.

What will I be introduced to regarding high availability?

You will review the services used for high availability, including Elastic Load Balancers and Auto Scaling, which are used to support EC2 instances.