The Internet of Things (IoT) is a network of interconnected devices, buildings, and objects connected to the Internet. IoT has become an integral part of our lives, and it will continue to grow in the coming years. The IoT revolution has brought DevOps practices from the cloud to the nascent world of edge devices. Enterprises are increasingly adopting cloud-native technology for devices at the edge to leverage the sophisticated computing, networking, and storage capabilities of cloud computing. Enterprises need the advantages that cloud-native approaches offer. However, most embedded devices are built as fixed-function, single-purpose devices, so their hardware constraints can make it difficult for them to support cloud-native approaches such as CI/CD, secrets management, and service meshes. If embedded developers are to ensure that their devices stay competitive, they need a lightweight, distributed software architecture that extends the cloud without exceeding the physical constraints of the embedded devices. The most effective way to extend the cloud to embedded IoT devices is by capitalizing on container technologies.
Centralized vs. decentralized IoT
IoT systems are becoming more complicated than ever before. Numerous types of IoT devices exist, from lightweight to high-powered. Different types of data are generated, including device-generated or human-generated data, sensor data, and machine-generated data. There is the hardware and the software that powers the hardware. Which one is of more importance will depend on the purpose of the system.
There are different approaches to managing IoT data. One is attaching cloud computing capability to physical devices by embedding microprocessors on boards that can help process the IoT data locally for low-power devices with limited communication capabilities. These include industrial IoT sensors that are embedded into factory machinery. The other approach is to rely on heavy hardware processing capabilities, as is found in a self-driving car. While both are used for different scenarios, in this article, we focus on the first approach of low-powered embedded devices, which make up the bulk of connected IoT devices.
Data from embedded devices can be managed centrally or managed at the edge. Parts of the data processing in an IoT system need to be centralized, and parts need to be decentralized. For example, in IoT devices like a sensor in a factory machine, data is collected and transferred to a centralized IoT cloud where it is processed. The sensor has to be reliable when collecting data, and the network needs to be equally reliable for transferring the data collected.
IoT sensors and embedded devices collect data from the physical world and feed that data into public or private cloud servers. They also have lightweight operating systems and applications running on them that need to be maintained, updated, and secured. This is where containers come into play. They help manage this complexity by maintaining the integrity of the underlying system. Containers enable developers to create complex systems with ease while maintaining scalability, security, and portability.
What are containers?
Containers, in essence, are lightweight virtualized software environments that can run isolated instances of an application or an operating system. Containers reduce overhead by allocating system resources only as required. This makes them a perfect match for embedded devices, which often have limited RAM and storage capabilities. Since most embedded devices run on a Linux OS, Linux containers (LXC) are quickly emerging as the container technology of choice to drive the migration of embedded systems to the cloud. LXC containers run virtualized instances of the Linux OS. They can be leveraged to deliver a modular Linux distro that is customized to run safely within the storage limits of embedded systems (more on that later).
While LXC containers have been making a resurgence thanks to the IoT boom, Docker containers continue to maintain their place at the top of the container market. Docker containers are quickly becoming popular among embedded developers due to their lightweight, user-friendly features. While LXC containers offer system-level virtualization, Docker focuses on application containerization. Each Docker container runs a single virtualized application in isolation, packaging only the application’s code and dependencies. With the right kind of container management system, an embedded device can execute all of its processes in isolation using containers, preventing bugs and faulty updates from crashing the entire system and enabling the implementation of security best practices.
Why use container technology with IoT devices?
Importantly, containers enable the deployment of cloud-native architecture in embedded systems. They support the implementation of DevOps concepts, microservices architecture, and continuous delivery in embedded systems, all of which are crucial to cloud migration. Containerizing cloud-native technology can give enterprises many benefits, including cost savings, flexibility in switching cloud service providers, and the ability to scale up services to meet demand quickly.
Containerization has been an important part of the DevOps movement. Containers help with portability and security by providing sandboxed environments for software, enabling developers to test apps on their local machines without worrying about breaking anything. These benefits are now being applied to IoT and embedded systems development.
Containers, as a technology, allow the management of IoT devices and sensors in a way that they can be easily scaled up and down. Containers also eliminate the need for running heavy hypervisors. This way, we can reduce the load on IoT systems and make them more reliable.
Containers and microservices
Microservices refers to an architectural approach involving developing an application as a collection of independent modules rather than a monolithic software entity. Containers enable applications and distros for embedded systems to be deployed in loosely coupled microservices, which optimizes the use of the restricted RAM and storage of embedded devices. This is more secure and agile than monolithic architectural approaches that develop an application as a unit with tightly coupled modules.
Monolithic architectures are hard to update since new updates require an application to be updated as a unit. Furthermore, monolithic architectures on embedded systems often take up valuable space with redundant components that are hard to exclude without compromising the functionality of other components.
On the other hand, containerized microservices can easily be updated component by component in isolation without affecting other running processes. This allows updates to be pushed out more frequently and automatically, ensuring that cloud-native embedded devices are always up-to-date and secured against vulnerabilities. In essence, implementing a containerized microservices architecture enables the adoption of a continuous delivery framework within an enterprise’s IoT architecture.
In addition, containerized microservices can be quickly replicated across different edge locations in a predictable and repeatable manner. This improves the pace of operations as it makes code reusable across devices and edge locations. It also decouples the software from the hardware layer, giving organizations agility at the edge.
Container technology and IoT: Numerous benefits
The opportunities for building smart IoT systems across the edge and cloud are endless. For this reason, businesses should be well-informed of the risks and benefits before deciding to adopt this technology. When evaluating IoT solutions, do consider how container-native they are. Containers offer numerous benefits when managing IoT data and deploying and maintaining applications and operating systems. Containers have revolutionized the world of IT and DevOps. These are still early days, but containers are all set to do the same for the world of IoT.
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