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Edge Computing with Amazon Web Services

Edge Computing with Amazon Web Services

By : Sean Howard
5 (10)
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Edge Computing with Amazon Web Services

Edge Computing with Amazon Web Services

5 (10)
By: Sean Howard

Overview of this book

The surge in connected edge devices has driven organizations to capitalize on the opportunities presented by the massive amounts of data generated by these devices. However, adapting to this landscape demands significant changes in application architectures. This book serves as your guide to edge computing fundamentals, shedding light on the constraints and risks inherent in selecting solutions within this domain. You’ll explore an extensive suite of edge computing services from AWS, gaining insights into when and how to use AWS Outposts, AWS Wavelength, AWS Local Zones, AWS Snow Family, and AWS IoT Greengrass. With detailed use cases, technical requirements, and architectural patterns, you’ll master the practical implementation of these services and see how they work in real life through step-by-step examples, using the AWS CLI and AWS Management Console. To conclude, you’ll delve into essential security and operational considerations to maximize the value delivered by AWS services. By the end of this book, you'll be ready to design powerful edge computing architectures and handle complex edge computing use cases across multiple AWS services.
Table of Contents (21 chapters)
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Free Chapter
1
Part 1: Compute, Network, and Security Services at the Edge
5
Part 2: Introducing AWS Edge Computing Services
10
Part 3: Building Distributed Edge Architectures with AWS Edge Computing Services
15
Part 4: Implementing Edge Computing Solutions via Hands-On Examples and More

Leveraging IP Anycast with AWS Global Accelerator

In Chapter 2, we discussed how the primary causes of packet loss on the internet are congestion or throttling at the junction of two autonomous systems along the way:

Figure 8.15 – A client in Dallas, USA, accessing an application in Stockholm, SE, via the public internet

Figure 8.15 – A client in Dallas, USA, accessing an application in Stockholm, SE, via the public internet

Let’s think about an application that runs on an EC2 instance in the AWS region in Stockholm, SE. The preceding figure provides an example of the path such a connection might take from a client in Dallas, USA.

As you can see, four different autonomous systems are traversed before the packets enter the AWS network in Stockholm. This is a lot of opportunity for congestion or QoS throttling mechanisms to cause a poor user experience.

Now, let’s look at the same application, but this time with AWS Global Accelerator configured in front of it. Yes, the client in Dallas still has to physically get to Stockholm, so...

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