Hey everyone, and welcome back to My Weird Prompts. I am Corn, and today we are diving into a topic that hits pretty close to home for anyone who has spent a long, frustrating weekend wrestling with a smart home setup that just will not behave. We have all been there—the lights do not trigger, the dashboard is unresponsive, and you are left wondering why you traded simple light switches for a complex web of silicon and code.
And I am Herman Poppleberry. It is great to be here. Today, we are talking about the inherent fragility of the modern smart home. Specifically, we are looking at what happens when you try to do everything the right way—self-hosted, local, and private—only to realize that local also means you have created a single point of failure right in your own living room.
Exactly. Today's prompt comes from Daniel, and it is a fascinating look at system architecture. Daniel is worried about the risk of running an entire home's intelligence on a single piece of hardware, like a Raspberry Pi or a small N-U-C. If that little board fails, or if the S-D card decides to give up the ghost after too many database writes, your house essentially loses its mind. You cannot turn on the kitchen lights, the heating might not kick in when the sun goes down, and you are left standing in the dark with a very expensive, very silent paperweight.
It is the ultimate irony of the smart home movement, Corn. We spent the last decade fighting to get away from the big tech clouds—the Tuya, the SmartThings, the Nest ecosystems—because we wanted independence and privacy. We wanted our houses to work even if the internet went down. But in building these local fortresses, we have traded one type of vulnerability for another. Instead of a server farm in Virginia going down, it is a five-dollar power supply in your hallway that brings the whole thing crashing down.
Daniel is suggesting a really interesting middle ground. He calls it a decoupled design. The idea is that the core logic—the brain, the rules, the user interface—lives on a professional cloud virtual private server, or V-P-S. Meanwhile, only the bare minimum connectivity hardware stays local at the house. It is like moving the brain to a secure bunker and just leaving the nervous system behind.
It is a sophisticated approach. It is not quite the corporate cloud model where you are at the mercy of a company’s A-P-I or their decision to sunset a product. Since you own the V-P-S, you still have total control over the software. But you are leveraging enterprise-grade reliability. Herman, you have spent a lot of time thinking about system architecture and high availability. Does this decoupled brain approach actually solve the reliability problem, or are we just moving the goalposts?
That is the big question. In engineering, we often say that you do not really eliminate complexity or risk; you just move it around. But Daniel’s idea has some real merit if you are looking at it from a hardware longevity perspective. Think about where your Home Assistant yellow or your Raspberry Pi lives. It is probably in a closet, maybe getting a bit dusty, powered by a consumer-grade wall wart, and writing constantly to an S-D card or a cheap S-S-D.
Compare that to a data center. A virtual private server at a place like Hetzner or DigitalOcean is running on redundant power, with backup generators, professional cooling, and enterprise-grade N-V-Me storage that is designed for millions of write cycles. It is never going to suffer from a corrupted file system because a power flicker happened at the wrong time. In the cloud, "hardware failure" is someone else's problem, and they usually solve it by migrating your instance to a new node before you even notice.
Right, and if the local proxy fails—the little device that actually talks to the Zigbee or Z-Wave radios—you can just swap that one component out. You do not have to rebuild your entire automation logic, re-configure your dashboards, or try to remember how you set up that complex Node-Red flow three years ago. You just point the new proxy at the cloud brain and you are back online. But I am curious about the projects that already do this. Are there people actually running Home Assistant in the cloud and just piping the sensor data up from their houses in twenty-twenty-six?
There are definitely people doing it, though it remains a bit of a "power user" configuration. One of the most common ways people achieve this right now is through a custom component called Remote Home Assistant. It is available through the Home Assistant Community Store, or H-A-C-S. It allows one instance of Home Assistant to connect to another over a secure link. So, you could have a very lean, "dumb" instance running locally that just handles the hardware radios, and then a beefy instance on a V-P-S that does all the heavy lifting.
So, in that scenario, the local instance is basically just a sensor and switch aggregator? It is not making any decisions; it is just saying, "hey, the motion sensor in the hallway was triggered," and then the cloud instance says, "okay, I see that, now turn on the light bulb."
Precisely. And that leads us to the other major way people do this, which Daniel mentioned: Zigbee-two-M-Q-T-T. This is really the secret sauce for a decoupled design. For those who might not be familiar, Zigbee-two-M-Q-T-T takes the signals from your Zigbee devices—your Hue bulbs, your Ikea sensors, your Aqara buttons—and translates them into M-Q-T-T messages. M-Q-T-T is a very lightweight messaging protocol that has been the backbone of the Internet of Things for years.
And because it is just a stream of messages, it does not really care where the broker—the post office for those messages—is located. It could be in the next room, or it could be in a data center in Frankfurt or New York.
Exactly. You can have your local Zigbee coordinator—maybe a tiny little device like a Sonoff bridge or a dedicated network-attached coordinator like the Tubes-Z or the S-L-Z-zero-six—sending those M-Q-T-T messages over a secure tunnel to your cloud server. The cloud server runs the M-Q-T-T broker and the Home Assistant core. To Home Assistant, it looks like the devices are right there on the local network, even though they are hundreds or thousands of miles away.
Okay, but we have to talk about the elephant in the room here, which is the latency. This is the part that always makes me nervous. If I walk into a room and a motion sensor triggers, that signal has to travel from my house, across the public internet to a data center, get processed by the automation engine, and then a command has to travel all the way back to the light bulb in my ceiling. Herman, is that going to feel like a delay? Are we talking about a noticeable lag between the motion and the light?
This is where the physics and the networking get really interesting, and it is where a lot of people’s intuition fails them. Most people assume that the internet is "slow," but for small packets of data like a sensor trigger, the latency can be surprisingly low. We are talking about the speed of light through fiber optics. If you are in London and your V-P-S is in a London data center, your round-trip time might be five to ten milliseconds. Even if you are in Jerusalem and your V-P-S is in a European data center, your round-trip time might be sixty to eighty milliseconds.
For context, what is the threshold for human perception? At what point does a light turning on feel "slow" or "broken"?
Generally, in the world of user interface design, anything under one hundred milliseconds feels instantaneous to a human being. It feels like a physical connection. Between one hundred and two hundred milliseconds, you might notice a very slight hesitation—a sort of "softness" to the interaction—but it still feels acceptable. Once you get over two hundred and fifty or three hundred milliseconds, that is when the "uncanny valley" of home automation starts. You walk into the room, you wait a beat, you start to wonder if the sensor missed you, and then the light comes on. That is the frustration point.
So, if your internet connection is solid and you choose a data center that is geographically close to you, you are actually well within that window of perceived instantaneity. But what happens when the internet goes out? That seems like the biggest downside to Daniel's proposal. If my fiber line gets cut by a construction crew down the street, I cannot even turn my kitchen lights on?
That is the fundamental trade-off. You are trading hardware reliability for network reliability. In a traditional local-only setup, if your internet goes down, your house still works, but if your Pi fails, you are dead in the water. In Daniel’s decoupled setup, if the internet goes down, the brain is severed from the body. Now, in twenty-twenty-six, many people would argue that their fiber internet connection is actually more reliable than a Raspberry Pi’s S-D card. In many urban areas, internet uptime is "four nines"—ninety-nine point nine nine percent. But it is definitely a risk you have to accept.
I wonder if there is a hybrid approach. Could you have a local fail-safe? Maybe a very basic set of rules that live on the local proxy, so that even if the connection to the cloud is lost, the most important things still work?
You absolutely could, and this is where the design goes from "good" to "great." If you use something like E-S-P-Home or even certain features of Zigbee-two-M-Q-T-T, you can set up what we call "direct binding." Zigbee binding allows a switch to talk directly to a bulb at the radio level, without even needing a hub or a brain to mediate the conversation. So, if the cloud goes dark, or the V-P-S is undergoing maintenance, the physical switches on your wall still work because they are talking directly to the lights. That would be the gold standard for this kind of architecture.
I love that. It is like having a reflex system in your body that works even if the brain is busy or disconnected. You pull your hand away from a hot stove before you even consciously realize it is hot because the signal only had to go to your spinal cord and back. So, the local proxy handles the reflexes—the critical "must-work" lights—and the cloud handles the complex logic, like the high-level automations, the energy monitoring, and the user interface.
That is a perfect analogy. And it addresses the "Wife Approval Factor" or "Partner Approval Factor" that is so critical in smart home design. If the internet goes out and the "Good Morning" routine doesn't run, it's a minor annoyance. If the internet goes out and the bathroom light doesn't turn on at three in the morning, it's a household crisis. Direct binding solves the crisis.
Daniel also asked about the mechanics of setting this up. If someone wanted to follow this implementation pathway today, where do they even start? It sounds like there are a lot of moving parts.
It is definitely a project for a Saturday afternoon, but the pathway is clearer than it used to be. Step one is the cloud side. You need a virtual private server. You do not need a monster machine; a basic instance with two gigabytes of R-A-M and two C-P-U cores is plenty for Home Assistant. You can get these for five or ten dollars a month from providers like Hetzner, DigitalOcean, or even the Oracle Cloud free tier if you can snag an instance.
And I assume you would want to run everything in Docker to keep it clean?
Absolutely. Use Docker Compose. You would want a container for your M-Q-T-T broker—Mosquitto is the industry standard—and a container for Home Assistant itself. But the most crucial part, the part that most people trip over, is the secure tunnel. You definitely do not want to just open up your M-Q-T-T broker to the entire public internet. That is a massive security risk. You are essentially leaving a door open for anyone to control your house.
Right, you need a private pipe.
Exactly. You would want to use an overlay network like Tailscale or a WireGuard V-P-N. Tailscale is particularly brilliant for this because it handles all the N-A-T traversal and the messy networking stuff for you. You install Tailscale on your V-P-S and on your local proxy device. Now, they both have a private I-P address that only they can see. To the local proxy, the cloud broker looks like it is just another device on the local network. It is encrypted, it is secure, and it is very robust.
So, on the local side at your house, what do you actually need? If we are trying to avoid the "single point of failure" of a Raspberry Pi, what are we putting in its place?
You want a very thin, very stable client. You could still use a Raspberry Pi, but because it is doing so little work—just running Zigbee-two-M-Q-T-T and a Tailscale client—it is much less likely to overheat or crash. Even better, you could use a dedicated network coordinator. These are devices that have an Ethernet port and a Zigbee radio built-in. They don't run a full operating system; they just bridge the Zigbee radio to your network. You point that coordinator at the Tailscale I-P of your V-P-S, and you are done. No local computer required at all.
That is a game-changer. That eliminates the S-D card issue entirely because there is no S-D card in a dedicated network coordinator. It is just firmware.
Precisely. And that brings us to the database. Home Assistant is very write-heavy. Every time a temperature sensor changes by zero point one degrees, Home Assistant writes that to its database. On a Raspberry Pi, those constant writes are what eventually kill the S-D card. By moving the database to the cloud V-P-S, which uses enterprise S-S-Ds and proper file systems like Z-F-S or X-F-S, you have basically eliminated the number one cause of local smart home failure.
I am curious about the user interface aspect of this. Daniel mentioned hosting the U-I in the cloud. Does that make the app or the web interface feel snappier because it is running on faster hardware, or does the latency make it feel sluggish when you are trying to toggle a switch manually?
It is a bit of both, but mostly it is a massive upgrade. If you have ever tried to load a complex Home Assistant dashboard with twenty or thirty history graphs on a Raspberry Pi, you know it can be painful. The Pi’s processor just struggles to pull all that data from the database and render it. On a V-P-S, that same dashboard will load almost instantly because the C-P-U and the disk I-O are so much faster.
So the "snappiness" of the interface actually improves, even if there is a tiny delay in the physical light turning on.
Exactly. Navigating through your logs, looking at your energy usage from last month, or configuring a new automation—all of that becomes a much smoother experience. And the latency for a manual toggle? If you are on a good connection, sixty milliseconds is less than the time it takes for the physical relay in the wall switch to click. You won't notice it.
It is interesting that we are seeing a shift back toward the cloud, but in a way that preserves user agency. We spent years telling people to get off the cloud because of privacy and reliability, and now we are saying, "well, maybe your own personal cloud is actually the answer."
It is the evolution of the self-hosting movement. We started with "host it in your house," and now we are moving toward "host it on infrastructure you control, wherever that may be." It is about ownership of the data and the logic, not necessarily the physical location of the server. This is what some people call "Sovereign Cloud." You are using the tools of the giants—data centers, high-speed fiber, virtualization—but you are the one who holds the encryption keys.
Let's talk about the specific projects again. You mentioned Remote Home Assistant and Zigbee-two-M-Q-T-T. Are there any other emerging projects in twenty-twenty-six that are designed with this decoupled architecture in mind?
We are starting to see more movement in the Matter and Thread space. Matter is designed to be "local first," but the way it uses I-P-v-six means that, theoretically, a Matter-enabled device could communicate with a controller anywhere, as long as there is a secure route. We are also seeing the rise of "Satellite" projects. For example, the Home Assistant Voice Assistant—the Year of the Voice stuff they did—is built on this idea. You have a tiny, cheap device with a microphone that does no processing; it just streams the audio to a beefier server that handles the speech-to-text. It is the same philosophy: put the "dumb" hardware where you need it, and put the "smart" logic where it can be powerful and reliable.
I wonder if this approach would also make it easier to manage multiple properties. If you have a main house and maybe a small apartment or a vacation home, could you run both of them from a single cloud instance?
Absolutely. That is one of the biggest advantages. You could have one master Home Assistant instance in the cloud with two different Zigbee-two-M-Q-T-T proxies—one in each location. You could have a single dashboard that shows you the temperature in both houses, and you could even have automations that span both locations. For example, if you leave your main house, it could automatically turn down the heat in your vacation home if it knows you are not heading there. Or, if the security alarm goes off at the vacation home, all the lights in your main house could flash red.
That is a really powerful use case. But I have to ask about the cost. A Raspberry Pi is a one-time fifty-dollar investment. A V-P-S is a recurring monthly cost. Over five years, you are looking at three hundred to six hundred dollars. Does the reliability justify the price tag for the average user?
For the average user who just wants their lights to turn on when they walk in the room, probably not. A well-maintained local Pi with a high-end endurance S-D card or an external S-S-D is usually "good enough." But for the power user—the person Daniel seems to be—the person who has hundreds of devices and complex automations that their family relies on every single day, that five or ten dollars a month is basically an insurance policy. It is the price of knowing that you will never have to spend a Saturday afternoon reflashing an operating system or trying to recover a corrupted database from a backup that might be three weeks old.
I think there is also a psychological component to it. There is a certain peace of mind that comes with knowing your system is running on professional infrastructure. It feels less like a hobbyist project and more like a utility, like your water or your electricity.
Exactly. And let's be honest, we have all had that moment where a guest is staying over and the smart home fails, and you feel like you have to apologize for your own house. "Oh, sorry, the guest room light isn't working because the M-Q-T-T broker crashed." Moving to a more robust architecture reduces those moments of friction. It makes the technology invisible again, which is what a smart home should be.
So, if we were to map out a clear implementation pathway for Daniel or anyone else listening who wants to try this, what are the steps? Let's summarize.
Step one: Choose your V-P-S provider and spin up a basic Linux server—Ubuntu or Debian are usually the easiest paths. Step two: Set up Tailscale on both the V-P-S and your local hardware to create that secure, private tunnel. Step three: Use Docker Compose to install Mosquitto and Home Assistant on the V-P-S. Step four: Set up your local Zigbee-two-M-Q-T-T instance—either on a small Pi or a dedicated network coordinator—and point it at the Tailscale I-P of your cloud broker.
And step five would be the most important for reliability: configure those local fail-safes. Use Zigbee binding for your most critical lights and switches so that the "nervous system" can still function if the "brain" is temporarily unreachable.
Precisely. It is a more complex setup initially, but the long-term stability is arguably much higher. You are essentially building a private, secure version of the commercial smart home clouds, but you hold the keys, you own the data, and you decide when the updates happen.
I think it's also worth mentioning that this architecture makes it much easier to experiment. If you want to try out a different automation engine, like Node-Red or AppDaemon, you can just spin them up on your V-P-S alongside Home Assistant. You don't have to worry about running out of memory or C-P-U cycles on a tiny Raspberry Pi. You have the overhead to grow.
That is a great point. The scalability of a V-P-S is a huge advantage. If your system grows from fifty devices to five hundred, you don't have to buy new hardware and migrate everything. You just click a button in your cloud console to add more R-A-M or more C-P-U cores. It is a future-proof way to build.
You know, Herman, I think this really addresses a fundamental tension in the smart home community. We want the convenience and power of the cloud but the privacy and control of local hosting. This decoupled approach feels like a very elegant way to have our cake and eat it too.
It really does. It is about taking the best parts of both worlds. You get the professional-grade reliability and ease of management of the cloud, but you maintain the data privacy and the open-source flexibility of a local system. It is a sophisticated way to manage what is becoming a very sophisticated part of our lives. Our homes are no longer just four walls and a roof; they are complex digital environments.
I'm curious if you think we'll see more official support for this. Could you imagine a future version of Home Assistant that has a "Cloud-Core" mode built-in, where it guides you through this process?
I would love to see that. Right now, it requires a fair bit of command-line knowledge and an understanding of networking and V-P-Ns. If the Home Assistant team or another project could productize this—maybe a "Home Assistant Cloud-Core" that you can deploy with one click on a V-P-S—I think a lot of people would jump on it. The Nabu Casa team is already doing great work with their cloud remote access, so this feels like a natural extension of that philosophy.
It certainly feels like the logical next step as the ecosystem matures. We've moved past the "can we make it work" phase and into the "how do we make it indestructible" phase.
And that is exactly where we should be. Our homes are our most important spaces, and the technology that runs them should be as reliable as the plumbing or the electricity. You don't expect your toilet to stop flushing because a server in Virginia went down, and you shouldn't expect your lights to stop working because an S-D card wore out.
Well, I think we have given Daniel a lot to chew on. It is a bold design, but with the right networking and some local fail-safes, it seems like a very viable way to build a more resilient smart home in twenty-twenty-six.
I agree. It is a classic engineering trade-off, but for the right person, it is a very compelling one. I am actually tempted to move some of my own more critical automations to a V-P-S after this discussion. I've had one too many S-D card failures in my time.
Oh no, here we go. Another weekend project for Herman Poppleberry. I can already hear the mechanical keyboard clicking from here.
Guilty as charged. But hey, if it means I never have to troubleshoot a corrupted database at ten o'clock on a Tuesday night again, it is time well spent.
Fair enough. Well, this has been a fascinating look into the future of smart home architecture. Before we wrap up, I want to remind everyone that if you are enjoying these deep dives, please leave us a review on your favorite podcast app. It really does help other people discover the show and join the conversation.
It truly does. And if you have your own weird prompts or architectural ideas you want us to explore, you can always reach out. We love hearing how you all are pushing the boundaries of what this technology can do. Whether it is decoupled brains or local-only A-I, we want to hear about it.
You can find us at myweirdprompts.com, where we have our full episode archive and a contact form. You can also email us directly at show at myweirdprompts.com. We are available on Spotify, Apple Podcasts, and pretty much everywhere else you get your audio fix.
And a big thanks to Daniel for sending in this prompt. It really forced us to think about the fundamental trade-offs we make when we build these systems. It is easy to get stuck in the "local is always better" mindset without considering the risks.
Absolutely. Thanks for listening to My Weird Prompts. We will be back soon with another exploration of the strange, the technical, and the fascinating.
Until next time, stay curious and keep building. Goodbye!
Goodbye!
