Getting began with edge computing
The Microsoft Azure cloud computing dictionary describes edge computing as a framework that “permits units in distant places to course of information on the ‘edge’ of the community, both by the machine or an area server. And when information must be processed within the central datacenter, solely an important information is transmitted, thereby minimizing latency.”
There’s fairly a bit to unpack there. How does constructing edge computing software program differ from writing different cloud functions, what do it’s essential know to get began, and does Microsoft’s definition maintain up within the first place? The ReadME Undertaking Senior Editor Klint Finley gathered three specialists to reply these and different questions.
Let’s meet our specialists:
Jerome Hardaway is a senior software program engineer at Microsoft, the place he works in Trade Options Engineering. He’s additionally a U.S. Air Pressure veteran and the chief developer of Vets Who Code, a tuition-free, open supply, coding-immersive non-profit that makes a speciality of coaching veterans.
Kate Goldenring is co-chair of the Cloud Native Computing Basis IoT Edge Working Group and a senior software program engineer at Fermyon Technologies.
Alex Ellis is the founding father of OpenFaaS, a former CNCF ambassador, and creator of the Linux Basis’s Introduction to Kubernetes on Edge with K3s course.
Klint: Let’s begin by getting on the identical web page about what we’re speaking about. I shared the Microsoft Azure cloud computing dictionary definition of edge computing. Does that definition work? Would you modify something about it?
Jerome: I would make the definition more human-centric. It’s not just about devices, it’s about the person. You want data processed and updated at the edge of the network as close to the person using it as possible, because, without a person to answer it, a cell phone is just a block of electricity.
Kate: I think it’s a good definition, given that it’s 12 words long. I would add more to it. When the CNCF IoT Edge Working Group was working to define edge computing, we found that definitions tend to fall into three main categories. The most common, and the one that Microsoft seems to be using, is geography-based—the distance between devices and servers, for example. The second is a resource-based definition, which prioritizes the resource constraints faced in edge computing. The third was connectivity-based.
Alex: Likewise, I’d change the definition to reflect how broad a topic edge computing can be. Just like with cloud computing, you can have two industry experts with a wealth of experience talking about two very different things when you ask them about edge computing.
Klint: I could see there being some confusion between edge computing and private or hybrid cloud, since all three typically involve some on-premises computing power. What are the main differences between edge computing architectures and more traditional architectures?
Jerome: A big part of the difference is about the intent, and that will affect how you architect your solution. Private and hybrid cloud computing is usually more about controlling where your data can go. For example, a healthcare company might need to make sure that patient data never leaves their premises. Edge computing is more about specific requirements, like the need to have an extremely responsive application, for example. Edge computing is about ensuring you have the right resources in the right places.
Kate: One way to think about it is that edge computing is a continuum that includes the downstream devices; upstream cloud resources, whether those are part of a public or private cloud; and whatever nodes you might have in between. You have to think about what sort of storage and computing resources you will have available at each point in the continuum. Network connectivity is a big constraint for much of what we talk about when we talk about edge computing.
Alex: You’re not always necessarily working around resource constraints in edge computing. Sometimes you might be working with rather capable devices and servers. But resources and environment are certainly something you have to consider when designing an edge computing solution in a way you might not have to for a more traditional scenario. For example, in a hybrid cloud scenario, you might be able to assume that devices will maintain a traditional TCP/IP network connection at all times. But what if you have a remote sensor powered by a battery that has to be changed manually? You might want to plan to have that sensor only intermittently connect to a network, rather than maintaining a constant connection, to conserve power and reduce the number of trips someone has to make to change the batteries. The device might only support a low-power wireless protocol to communicate with the intermediary device, so you’ll need to accommodate that as well.
Klint: What applications are NOT a good fit for edge computing?
Jerome: Adding more intermediaries between a device and a data store creates a bigger attack surface that you have to secure, so some industries, healthcare for example, will need to pay extra attention to the possible trade-offs. You have to think about the requirements and the benefits versus the challenges for your specific use case. You need to make sure you understand the business problems you’re trying to solve for your organization.
Alex: I don’t want to pigeonhole edge computing by saying it’s good for certain things and not others. It’s more about building an appropriate solution, which can differ greatly depending on the requirements. To continue with the healthcare example, building an edge computing system for medical devices will be quite different from building one for restaurant point-of-sale systems, which will be different from a solution for airlines. A POS device might run a full installation of Android and you might need to reboot it periodically to install updates. For medical devices, you’re probably going to want something like a real-time operating system that can run continuously without the need to take it offline to install updates.
Kate: It comes down to the characteristics of the application. If you have a highly stateful application that needs constant connectivity and lots of storage, then maybe you’d be better off running that application in the cloud. But you still might want to have some intermediaries near the edge to handle some lighter processing.
Klint: How portable between platforms do edge computing applications tend to be? Any tips on making them more portable?
Kate: It depends on what you mean by platform. Edge computing software tends not to be very portable between scenarios because of how customized it is to its circumstances. There are many different ways to connect to different devices, so there often needs to be a lot of custom logic to facilitate that. But one thing you can make consistent is what you do after ingesting data from your devices. You can focus on these elements to make things more portable.
Jerome: The more features of a platform you use, the less portable it is. To use an analogy, the more you use the built-in functionality of a framework from Ruby on Rails as opposed to implementing your own solutions, the harder it will be to move. But it’s also more work on your end. The tradeoff is that the more you leverage the technology, the more dependent you are on it. That’s not always bad but you need to be aware of it.
Alex: Again, it depends on what you’re running at the edge and what resources and capabilities are available. Embedded software for bespoke devices might not be very portable, but if your hardware can run a container or a virtual machine, your solution can be very portable.
Klint: What sorts of skills should developers learn to prepare to work in edge computing development?
Alex: I have a free course on Kubernetes and K3s on the edge. It has an inventory of related abilities which might be helpful on this house, resembling MQTT, shell scripting, and Linux. After all, what it’s essential be taught will depend on what kind of edge computing you may be doing. In some circumstances you could be making an in any other case conventional net or cellular utility extra responsive by placing assets nearer to the person, however in others you could be working with industrial gear or vehicles. Both approach, Kubernetes isn’t a nasty ability to have.
Jerome: Language-wise, I like to recommend Python, since you’ll be working with many various platforms and environments, and Python performs nicely with nearly every thing. It’s one of the transferable technical abilities you possibly can be taught. Edge computing can also be one of many few areas the place I like to recommend getting skilled certifications for the applied sciences you employ, as a result of it showcases that you just’re actually taking the time to be taught them. And as all the time, work in your communication abilities, since you’re going to FUBAR a factor or two.
Kate: Edge computing is a extremely broad area. It’s additionally pretty new, so that you’re not alone in determining what it’s essential be taught. Studying about networking applied sciences and all the assorted protocols that units use to speak could be a superb place to begin. And you may all the time simply get a Raspberry Pi and construct one thing. Join it to an edge computing platform and begin studying the terminology. Have some enjoyable, that’s the easiest way to be taught.
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