AT&T Edge Cloud (AEC)
2017 AT&T. All rights reserved.
PAGE 2 OF 25
Table of Contents
I. Executive Summary ........... 4
II. Background – Cloud Computing Evolution and
the Rise of the Edge Cloud ........... 6
III. AT&T Edge Cloud Architecture .. 11
IV. Edge Computing Drivers . 13
V. Edge Location Tradeoffs . 13
VI. Edge Computing Use Cases ........ 14
VII. Co-existence of Centralized Cloud and Edge
compute .... 15
VIII. Edge Computing Key Requirements ....... 16
IX. Virtualization Infrastructure Manager (VIM) ...... 17
X. Scaling Edge Functions Using Cloud Native
Computing19
XI. Orchestration & Management ..... 21
XII. Open Source Eco-system – Edge Computing
enablers ..... 21
XIII. Conclusion ........... 22
XIV. Glossary ... 22
XV. References 24
AT&T Edge Cloud (AEC)
2017 AT&T. All rights reserved.
PAGE 3 OF 25
AT&T Edge Cloud (AEC)
2017 AT&T. All rights reserved.
PAGE 4 OF 25
Executive Summary
In recent years, there has been a concerted effort among all companies to move their
infrastructure to a centralized cloud, enabled by virtualization. This push started with the
vision of reducing time to market for new services and achieving lower total cost of
ownership (TCO). This surge in the demand for cloud computing led providers like Amazon
and Google to build massive centralized clouds (think data centers) designed for efficiency.
With the emergence of new technologies such as augmented and virtual reality,
autonomous cars, drones and IOT with smart cities, data is increasingly being produced at
the user end of the network. These use cases demand real-time processing and
communication between distributed endpoints, creating the need for efficient processing at
the network edge.
“Edge computing” is the placement of processing and storage capabilities near the
perimeter (i.e., “edge”) of a provider’s network.Edge computing can be contrasted with the
highly-centralized computing resources of cloud service providers and web companies.
Edge computing brings multiple benefits to telecommunications companies:
reducing backhaul traffic by keeping right content at the edge,
maintaining Quality of Experience (QoE) to subscribers with edge processing,
reducing TCO by decomposing and dis-aggregating access functions,
reducing cost by optimizing the current infrastructure hosted in central offices with
low cost edge solutions,
improving the reliability of the network by distributing content between edge and
centralized datacenters,
creating an opportunity for 3rd party cloud providers to host their edge clouds on
the telco real estate.
The computational resources can be distributed geographically in a variety of location
types (e.g., central offices, public buildings, customer premises, etc.,) depending on the use
case requirements. This variety requires flexibility in the hardware and software design to。