Bringing cloud computing resources to the edge of the network.
In this blog post, the terms “Cloud at the Edge,” “Edge Cloud,” and “Next-Gen Cloud” are used interchangeably. Most of us are familiar with the following cloud computing environments:
- Private cloud: Access is limited to members of an enterprise and partner networks.
- Public cloud: Access to standardized resources—like infrastructure, multi-tenant hardware, and services, is available to subscribers on a pay-per-use basis
- Hybrid cloud: The use of multiple public and private cloud computing services by an enterprise.
- Multicloud: Enterprise uses a combination of on-premise, private cloud, and public cloud components.
We can now add Cloud at the Edge or Edge Cloud to that list, bringing cloud computing resources to the edge of the network or to where the traffic is.
Please make sure to check out all the installments in this series of blog posts on edge computing:
- Part 1: “Cloud at the edge”
- Part 2: “Rounding out the edges”
- Part 3: “Architecting at the edge”
- Part 4: “DevOps at the edge”
- Part 5: “Policies at the edge”
- Part 6: “Models Deployed at the edge”
- Part 7: “Security at the edge”
- Part 8: “Analytics at the edge”
- Part 9: “5G at the edge”
- Part 10: “Clusters at the edge”
- Part 11: “Automation at the edge”
- Part 12: “Network slicing at the edge”
- Part 13: “Data at the edge”
- Part 14: “Architectural decisions at the edge”
- Part 15: “GitOps at the edge”
- Part 17: “Storage services at the edge”
- Part 18: “Cloud services at the edge”
- Part 19: “Distributed cloud: Empowerment at the edge”
- Part 20: “Data sovereignty at the edge”
- Part 21: “Solutioning at the edge”
- Part 22: “Connected products at the edge”
- Part 23: “Foundational models at the edge”
Edge Cloud
Multi-access edge computing (MEC) is a network architecture concept that offers cloud computing capabilities with an IT service environment at the edge of the network. The basic idea there is running applications and performing related processing tasks closer to the cellular customer. This, in turn, reduces network latency and congestion, thus allowing apps to perform better.
With the advent of 5G, that same paradigm can be applied to cloud computing when it comes to connected devices. The first hop from smart devices, mobile phones, connected cars, drones, robots, etc. would not be to the large public clouds, but rather to something closer. This would be the Edge Cloud operating at the edge of the network. It would mitigate the latency issue and offer more security among other things.
5G: What and why
5G (from 5th Generation) is the latest generation of cellular mobile communications. 5G promises a high data rate, reduced latency, energy saving, cost reduction, higher system capacity, and massive device connectivity. The aspects that 5G brings also happen to be the challenges with current cloud computing—namely network latency, an inability to fully support all mobile scenarios, an inability to meet the real-time requirements of large-scale sensor networks, insufficient bandwidth for all mobile devices, and security concerns.
To analyze data from the multitude of sensors and the unprecedented amount of data generated by Internet of Things (IoT) devices, considerable computing power is needed. These data-generating devices put tremendous strain on the Internet; the latency of going to a large cloud is not acceptable in the era of connected cars. 5G helps with its potential of 10 Gbps throughput and 1 ms latency.
The next-gen cloud computing
Edge computing (originally coined as “fog computing” by Cisco) is an extension of the existing cloud where the smaller infrastructure components are distributed at the edge of the network. It facilitates the operation of end devices by acting as the relay to meet the needs of high-speed IoT devices, thus reducing the bandwidth load of the network core.
Cloudlets are a concept in edge computing that are basically small-scale clouds. They act as offloading units for low-latency demands for emerging sensor-based and real-time streaming applications.
Edge computing promises to bring storage and computing capabilities closer to mobile users, leveraging existing devices to reduce latencies and core network utilization. Cloudlets promise to be well-connected microdata centers at the edge of the network, based on container technology but not offering much storage. They would “localize” the speed for data transmission and computations required by IoT, mobile, and connected devices. The envisioned topology is shown in the figure below.
Deployment of next-gen cloud
The figure depicts a handful of major cloud providers today—Amazon, IBM, Microsoft, Google, and Alibaba. In the future, there could be many new cloud providers at the edge. Their services will have to support, at a much more granular level, numerous Cloudlets. Cloudlets could be hosted on public buildings, within coffee shops, atop traffic camera,s and even on existing cellular towers, creating a mesh of mini-clouds.
Cloudlets may offer low latency and high bandwidth. The emergence of 5G cellular networks and the deployment of Cloudlets will together create the technology platform for the next-gen cloud that will be the Cloud at the Edge. Watch for this cloud computing option to become part of extended multicloud solutions.
IBM offers a combination of technology, services and expertise to enable Telco and Enterprise clients to access data and insights in near-real time and to automate the running of their operations, at the most optimized location. Our open, secure, hybrid approach gives clients the flexibility to deploy cognitive applications and services at scale, with thousands of new use cases across telecom, manufacturing, retail, and other global industries.
Check out all the installments in this series of blog posts:
- Part 1: “Cloud at the edge”
- Part 2: “Rounding out the edges”
- Part 3: “Architecting at the edge”
- Part 4: “DevOps at the edge”
- Part 5: “Policies at the edge”
- Part 6: “Models Deployed at the edge”
- Part 7: “Security at the edge”
- Part 8: “Analytics at the edge”
- Part 9: “5G at the edge”
- Part 10: “Clusters at the edge”
- Part 11: “Automation at the edge”
- Part 12: “Network slicing at the edge”
- Part 13: “Data at the edge”
- Part 14: “Architectural decisions at the edge”
- Part 15: “GitOps at the edge”
- Part 17: “Storage services at the edge”
- Part 18: “Cloud services at the edge”
- Part 19: “Distributed cloud: Empowerment at the edge”
- Part 20: “Data sovereignty at the edge”
- Part 21: “Solutioning at the edge”
- Part 22: “Connected products at the edge”
- Part 23: “Foundational models at the edge”
Learn more
- Explainer: What is edge computing?
- Video: Quick explanation of edge computing (10:39)
- Platform: IBM Edge Computing