The intersection of cloud and edge computing – Getting Started with Edge Computing on AWS

In recent years, a new operating model known as “edge computing” has emerged as a key enabler of digital transformation strategies across a variety of industries and organization types 1. The exponential growth of data generated by an ever-increasing number of connected devices, coupled with an insatiable appetite for real-time processing and analysis, has driven new operational models in the cloud. An example of this is the Industrial Internet of Things (IIoT). Also known as Industry 4.0, IIoT involves a fusion of traditional industrial processes with advanced techniques such as Artificial Intelligence (AI), Machine Learning (ML), and real-time data analytics.

1 Gartner Predicts the Future of Cloud and Edge Infrastructure

Due to this, “edge computing” has become a buzzword. Its meaning has been diluted through overuse by vendors who want in on the opportunities presented by this emerging model of computing. This book uses the term to mean “an architectural design that locates appropriate AWS cloud processing closer to where data is generated”.

By disaggregating AWS services closer to the source of data generation, edge computing facilitates shorter time from data generation to decision-making, reduced system costs, and enhanced data security.

In this chapter, we’re going to cover the following main topics:

The intersection of cloud and edge computing

The AWS edge computing strategy

Overview of the AWS edge computing toolbox

The intersection of cloud and edge computing

Definition of cloud computing – according to NIST

Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (for example, networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider (SP) interaction.

AWS can deliver client-server computing in the same way a utility delivers electricity to you – pay-as-you-go with no upfront investment. AWS achieves economies of scale that even the largest businesses struggle to compete with. This is true in obvious ways such as data center and server prices it can negotiate.

It is true in many non-obvious ways as well. AWS has millions of customers and an infrastructure that must be secured both within and without. AWS security operations are world-class because they have to be. When you pay for an EC2 instance, you’re not just getting a virtual machine. You’re also getting that world-class security operations team protecting its data physically, but also against – for example – a Distributed Denial of Service (DDoS) attack. Those are two things that are very costly to do in your own data center.

Your EC2 instance is also sitting right next to a panoply of additional services it can consume. Storage, networking, AI/ML, databases, analytics – the list is long2. It is this proximity to all that computing power and value-add services AWS provides that pushes architectures more and more toward centralization. The more things you move in-region, the greater the benefit, and thus the flywheel of migrating things into the AWS cloud.

2 List of AWS Services Available by Region

Great – so what are the problems with centralizing all applications into an AWS region? Well, they fall into four categories: physics, economics, regulatory compliance, and good old-fashioned organizational inertia.