Leveraging Docker for IoT Applications

Article originally published on IoT For All

As the hardware of connected devices becomes more capable and affordable, the complexity of IoT applications increases. Docker, a popular containerization platform, can help simplify and streamline the process, making it easier for developers to create and maintain IoT applications. In this article, we’ll explore some advantages that Docker brings to IoT development and challenges to consider when deploying and maintaining apps, plus how to apply security best practices to IoT.

Advantages of leveraging Docker in IoT applications

#1: Lightweight and scalable

Docker containers are lightweight, as they share the host operating system and resources, making them ideal for IoT applications where resources may be limited. This lightweight nature also allows for easy scaling, as developers can quickly deploy multiple instances of an application without consuming significant system resources.

#2: Simplified development and deployment

With Docker, developers can create a consistent environment across the entire application lifecycle, from development to production. By packaging the application and its dependencies into a single container, developers can ensure that the application will run consistently regardless of the underlying infrastructure. This simplifies the development process and eliminates the “it works on my machine” issue, making it easier to deploy and manage IoT applications.

#3: Docker security

Docker enables developers to isolate applications and their dependencies in containers, reducing the attack surface and enhancing security. By running each application in its own container, developers can limit the potential impact of security vulnerabilities and maintain better control over the application’s environment.

As discussed in this 2023 research report, the majority of CVEs aren’t as severe as their public severity rating. By intelligently scanning in context of the application, developers can be more productive by working on relevant potential vulnerabilities. More on this under Securing IoT Applications, below.

#4: Easier versioning and rollbacks

Containers inherently make versioning and rollbacks more manageable by allowing developers to create new containers for each application update. If a problem arises, or new features are added, a new version can be pushed out the update of the previous release.

Because IoT devices may be deployed in challenging network environments, the update itself could be interrupted and fail. It’s useful to be able to automatically rollback to the previous version if the update fails, which could leave the device in a non-working state. IoT platforms like JFrog Connect provide this ability to rollback updates automatically.

#5: Enhanced collaboration

Docker makes it easier for developers to collaborate on IoT projects by providing a consistent environment that can be shared across team members. Developers can quickly spin up containers with the required dependencies, making it easier to share with other team members for testing and further development.

#6: Docker and IoT in a DevOps environment

Docker is simply another artifact to be managed in a DevOps environment. As such, Docker benefits from the process automation for building, testing, and security and compliance checks, which are established best practices in modern DevOps.

Leveraging Docker in IoT applications offers numerous advantages. By adopting Docker, developers can streamline their workflows, improve application security, and ensure consistent performance across diverse IoT environments. With its compatibility with modern DevOps practices, it’s easy to see how Docker becomes an integral part of the development and deployment pipeline for IoT applications.

Challenges of Docker in IoT

Docker was originally designed with servers and data centers in mind but its advantages of simplicity, portability, and relatively low overhead have made it a popular choice for IoT applications. That being said, IoT devices have their own challenges to consider.

#1: Scalability

Deploying and updating Docker application images to a small number of devices is straightforward. However, managing deployments across hundreds or thousands of devices poses challenges. One option is to develop custom scripts, but this entails ongoing maintenance, testing, and updates.

Alternatively, investing in an IoT management platform offers full control while automating the process. Such a platform streamlines deployments, updates, and provides additional features like device monitoring, automated alerts, secure remote access, device management, and significant time savings.

#2: Size

While Docker is known for being a lightweight container, you still have to consider the application image, which can affect the overhead from Docker. If you’re targeting Linux on relatively inexpensive hardware like Raspberry Pi, you probably have more than enough power for most use cases.

#3: Network bandwidth and availability

IoT devices can be distributed far and wide with varying levels of network connectivity. Network access can be challenging. Networks may be slow or intermittent. Devices will be deployed behind firewalls with no public IP address to target. You’ll need to find the device, create a secure connection, and make sure the update works accordingly. And you need to do that to the entire fleet of devices.

In the event of a network interruption that causes an update failure, a proper IoT platform can automatically rollback to the previous instance so that the device isn’t left in a non-functional state between updates. That’s what happened to Roomba not so long ago when their update to their Roomba vacuums didn’t go as planned.

#4: Security

Security is usually an afterthought. Is checking for a CVE related to Docker top of mind for every developer? Probably not. They’re working on app features, not checking for the latest vulnerabilities. That’s why it’s useful to have a built-in background process that checks for potential vulnerabilities from the CVE database while they’re coding. Better yet, you can perform contextual vulnerability analysis to counter the burden of false positive alerts that aren’t applicable to you.

While Docker offers simplicity, portability, and low overhead for IoT applications, challenges can arise when it comes to scalability, size, network bandwidth, and security. Managing deployments across many devices can be challenging, but investing in an IoT management platform can streamline the process and provide additional benefits such as device monitoring and secure remote access.

Securing IoT Applications

Docker containers keep each other isolated, so the risk of one hacked container affecting the others is low. Still, remember that the app within the container isn’t safe from vulnerabilities and attacks. With the rise of IoT and more people using Docker, IoT projects have gone from small proof-of-concept experiments to vital parts of enterprise software. This means you have to follow certain release processes, but you also get access to the trustworthiness, speed, and protection that come from modern DevOps tools — so scaling up is seamless.

Here are a few ways to apply security best practices to IoT apps, plus what you gain by doing so:

Open-source software, favored by software developers across the spectrum ranging from small companies to Fortune 500 enterprises, is commonly used but also carries some inherent risk from unintended vulnerabilities, to malicious intent. That’s why it’s critical to build software composition analysis (SCA) tools into the software supply chain process and ensure common vulnerability exposures (CVEs) and malicious packages are detected and appropriately dealt with. Vulnerability and compliance scans should be done early and often throughout the software development lifecycle – from code to deployment.
Insecure and default passwords are an all-too common mistake when it comes to IoT devices. Scanning for “secrets’ such as weak credentials/passwords, or hard coded encryption keys, used for convenience during the development/testing cycle, but accidentally left in the code, should be an automated part of the DevOps process.
Shifting left, that is, helping developers avoid vulnerabilities while they work – without interfering with their workflow, or inundating them with false positives – is a great way to catch problems early in the cycle. This is where static application security testing (SAST) analyzes source code to find vulnerabilities and provides instant feedback to developers while they code, by delivering intelligent prompts of potentially vulnerable code being used as well as suggestions for possible remediation.
Better yet, you can shift left-of-left, by curating the open source packages being requested for use and pre-scanning them before they enter your software supply chain, even before developers start working. This initiates the software development cycle from a safer and trusted foundation.
Given Docker’s inherently self-contained nature of the application, Docker containers are a natural fit for performing vulnerability contextual analysis scans. Scanning Docker containers for vulnerabilities in context of the overall application helps to eliminate false positive reports on vulnerabilities that aren’t applicable. By minimizing low-risk distractions and emphasizing higher risk discoveries, contextual analysis conserves development resources and enables developers to concentrate on critical matters.
While nothing is perfect, it’s much easier and cheaper to catch problems early than it is to address them after release. However, in the less likely event that issues are discovered farther down the cycle, it’s important to establish a plan and remediation process. That requires a strong DevOps foundation that tracks everything from code, to binaries and artifacts, to deployment. Further, it helps to have automated systems that can find all the impacted applications and packages involved. Having an end-to-end integrated process in place will accelerate the remediation process from days (or weeks, or months) to hours.
Automation is essential for speed. The security of all deployed devices shouldn’t be left to a manual process. Once a new or updated Docker image is ready, an automated update should scale to all known devices. You can create and maintain custom scripts, or use an IoT platform like JFrog Connect to automatically manage them for you.

Conclusion

Docker offers a proven, efficient solution for packaging and deploying IoT applications. By leveraging Docker for IoT, you can streamline the development process, improve security, and readily scale IoT application development and deployments. With the growing demand for IoT solutions, adopting Docker to deploy IoT applications to devices will simplify the development process. Bring Docker for IoT apps into your DevOps workflows, add automated security, and you’ve got IoT development with the reliability, security, and agility of modern DevOps best practices.