There are a few unspoken rules in IT: disk space is always scarce, coffee is always cold, and someone on the team will inevitably suggest, “Let’s just Dockerize it!” – whether it’s a cloud backend, a local script, or the office toaster.
Docker certainly has its advantages. You can wrap nearly anything in neat little containers, ship them around, and deploy them on any host with enough RAM. And that’s exactly the problem: “enough RAM” in the embedded world is like “enough vacation” – great in theory, rarely found in practice.
When IoT Solutions Start Getting Hungry
Many of today’s popular IoT stacks rely on Docker or similar container orchestration tools. Sounds modern, feels modern – but they consume resources like a hungry teenager after football practice.
A typical setup? 2–4 CPU cores, 4 GB of RAM, and several hundred MB of storage, just to run the container engine and its sidecars. Add even a lightweight (or not-so-lightweight) Kubernetes on top, and suddenly your IoT box in the control cabinet needs more computing power than the PLC it’s supposed to be monitoring.
The result? “IoT” doesn’t stand for “Internet of Things” anymore; it now stands for “I/O Timeout”. Because your poor controller must boot an army of containers before it can even read the motor temperature.
The Alternative: Diet Instead of All-You-Can-Eat
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Now imagine an IoT solution that doesn’t scream for a server room. One that runs smoothly on a single CPU core, about 1 GB of RAM, and just 100 MB of storage.
Nope, that’s not a typo – 100 MB. In Docker-land, that’s barely enough to download Kubernetes' README file.
The trick? Instead of spinning up an army of containers, the IoT engine runs in a slim, dedicated partition under a hypervisor. So you avoid bloated layers, redundant sidecars and messages along the lines of, “Oops, your container needs 300 MB more RAM.”
You just get the functions you actually need: read hardware, control devices, process data, manage configurations, store, analyze, translate protocols, forward messages, and visualize results.
More Zen, Less Circus
The beauty? Less chaos. No self-orchestrating orchestration. No “image pull failed” alerts during the night shift. Just: boot, run, done.
It’s a bit like camping: The Docker crew shows up with a motorhome, diesel generator, and satellite dish, and spends the first hour just getting the grill set up.
With the right IoT platform, all you need is a tent, a sleeping mat, and a campfire, and you’re already enjoying marshmallows while the others are still debugging their power supply.
Bottom Line (With a Wink)
Docker absolutely has its place, especially in the cloud and for developers who enjoy juggling containers. But in the IoT world, where devices stay in the field for years, run on limited resources, and simply need to work, the rule is clear: less overhead, more payload.
You don’t need monster infrastructure to run modern IoT features. Sometimes, all it takes is a lean approach and the courage to not containerize every toaster.
Want to learn more about our lean IoT approach? Click here for details.
And for our lightweight virtualization solution, head over here.
