Cloud computing has dominated the computing platform market for the last decade and is not showing any sign of slowing down. However, the emergence of new technologies such as autonomous vehicles have pushed the need for new computing paradigms. Among those trends, edge computing has been getting a lot of attention recently as the potential driver of the next major revolution in computing platforms.
By edge computing, we are referring to architectures that involve a large number of independent nodes that can autonomously execute business logic and computations without a centralized authority. While the concept of edge computing has been around forever, it is just recently that technology has gotten to the point of enabling the mainstream implementation of that type of architecture.
The Need for Decentralization: What is Pushing Edge Computing?
Back in the 60s, IBM famously proclaimed that the vast majority of software applications in the world will be ran by a handful of mainframes( I am paraphrasing on purpose to make the statement sound less ridiculous than what it really was ;) ). While the prediction didn’t turn out to be truth for mainframes, it certainly became valid five decades later with the mainstream adoption of cloud platforms. After all, aren’t platform as a service(PaaS) stacks just like big mainframes? (just kidding…).
Today, a significant percentage of the cloud application sin the world are ran on an incredibly small number of platforms. Even more astonishingly is that one of those platforms (AWS) currently controls over 60% of the market. If you are looking for a text-book example of a fragile ecosystem it doesn’t get much better than the cloud platform market
While cloud computing is likely to become the architecture model of choice for an important percentage of the software applications in the world, a new generation of technologies are claiming the need for decentralized, autonomous computing models. This group of technologies are known as edge computing. There are many examples of edge computing models but, in terms of the market impact, we can cite these top four examples:
— Autonomous Vehicles: Self-driving vehicles are the most notable examples of edge computing architectures.
— IOT: Internet of things(IO)T and industrial enterprise applications require sensors and smart devices to operate autonomously without a centralized authority.
— Bitcoin: Bitcoin is a primal example of decentralized architectures powering mission critical capabilities.
— Drones: Drones architectures are a great example of edge computing operating at a global scale.
Some Cool Edge computing Models to Draw Inspiration From
There are many great examples of edge computing architectures and technologies. Below I listed some of my favorites that are helping to drive the mainstream adoption of edge computing paradigms.
— Blockchain Platforms: Technologies such as Ethereum, Ripple o rHyperledge are great frameworks for building decentralized, edge computing models based on the blockchain.
— Akka: Akka is a popular framework to author distributed, decentralized architectures.
— AWS Greengrass: Announced late last year, Greengrass extends AWS Lambda with edge computing capabilities.
— Consul.io: Consul.io is a decentralized platform to enable DNS-like discovery of services in a network.
Knowing that edge computing is likely to become a relevant trend in the software platform market, we can start brainstorming the capabilities of edge computing platforms. That will be the topic of the next post…