Continual change is driven in the cloud landscape by the need to constantly search for newer ways to improve productivity and efficiency. In the past decade, organizations have stepped away from launching their own on-premise data centers, as they have favored cloud infrastructure. Nowadays, the cloud computing world is transforming rapidly, mainly due to the emergence of the Internet of Things (IoT).
You can define IoT as a system of computing devices that are interrelated, digital, and mechanical machines that come with UIDs (unique identifiers) and the ability to transfer data over networks with no need for human-to-computer or human-to-human interactions. The best part about IoT is that small devices ranging from point-of-sale systems to wearables to beacons create more data and have processing power of their own.
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In general, sending all this data to be processed in the cloud isn’t efficient, as that process, even if it’s quick, will enhance the response latency at the location of the device. That’s not all, because it will rely on network availability and there are going to be several challenges related to privacy, security, and data protection.
That’s the main reason why so many companies have removed their IoT operations at retail outlets and restaurants. They have started allocating activities for processing back to on-site local systems. However, that doesn’t mean they are looking to build data centers locally. Instead, they want to leverage the IoT devices’ abilities on-premises, like the cash registers of restaurants and point-of-sale systems in a store, etc.
As they adopt this approach known as ‘computing on edge’, most companies are in a better position to implement innovation rapidly, and ensure higher availability for applications. We are going to be taking a closer look at this process here.
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Transforming Processes On the Edge
When you push devices that are computing on the fringe, it is known as ‘computing at the edge’ or better called ‘edge computing’, which is essentially a different term for distributed instead of centralized computing. The Internet of Things is more effective when computing occurs on-site based on that location’s immediate needs. However, you can use the cloud to collect data from multiple places, especially for large companies. For instance:
- All the locations of a chain restaurant must track items that are being sold, so that they know exactly what is required. There’s no point in tracking that in the cloud, as you don’t want to use the bandwidth for sending data to and from, mainly because the restaurant will immediately want to restock items. However, the chain needs to collect information from all locations to help management plan marketing and follow trends.
- WiFi beacons can be used in retail operations for recognizing previous customers and sending coupons to them whenever they enter the store. The point-of-sale systems can also display the shopping history of the customer when they check out. Once again, the parent company of that store will want to collect data from all branches, so that it can be accessed from a central place in the cloud, but every location will need to be able to respond and recognize customers immediately as well.
- Wearables are used by hospitals for tracking the whereabouts of patients and staff members, and beds for every patient that is admitted are also equipped with medication delivery systems such as IVs and insulin pumps, and sensors for monitoring vital signs. These systems have to quickly adjust medications after reviewing the measurements, which means lower latency, and that means it will be better to have onsite processing.
Most people see the combination of edge computing and IoT as networked systems’ next paradigm shift. It is predicted in numerous reports that communication and computing will be moving from their core networks and central cloud architectures and going towards the edge.
There are many reasons for that, but the main premise is that to serve the communications, data, and computing demands of people, objects, and sensors, it’s a given that compute, intelligence, and resources must move to the edge to do it in the most cost-effective manner and allow newer use cases, which the traditional cloud architecture can’t support.
Laying Down the Foundations
The next evolution of the Internet of Things and edge computing will be reliant on the ability to process data on the smaller, lighter hardware that is found on-site, for example, cash registers, sensors, and beacons. Containerization is the best way to implement this by deploying applications as tiny packages of codes containing all the components necessary for running configuration files, dependencies, libraries, and more.
In this manner, they can share lightweight operating systems that run independently, which makes them ideal for deploying in distributed locations. The application packages will also not rely heavily on the hardware due to containerization, as everything will be packed together.
Kubernetes is an open-source platform that is like a master tool to manage containerized systems, which can be deployed across multiple machines and can balance loads as well. You can use Kubernetes to ensure that a master machine can coordinate with a cluster of machines to manage them.
Amazon Web Services also offers the infrastructure to run master machines with their EKS (Amazon Elastic Container Service for Kubernetes). You can manage all the applications with EKS as they will be compatible with the traditional environment for Kubernetes and will allow you to leverage the advantages of open-source contributions.
Every Kubernetes cluster will stand alone in the framework, but will communicate with the EKS cluster with the help of load balancers in the cloud. All EKS clusters will be able to transfer data from their local Kubernetes clusters, ensuring it is aggregated, processed, and stored in the database for Amazon Relational Database Service for analysis and retrieval later.
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Conclusion
In short, the Internet of Things will be upgraded in the future and that will have a profound impact on the way that data is stored, collected, and analyzed. Leveraging Kubernetes for IoT is one of the best ways that organizations can ensure that they are able to remain one step ahead of their competitors and ensure that they are able to store, collect, and analyze data in the best manner possible.
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