Which is a very niche use case to begin with, isn't it? It doesn't really contradict what the parent comment stated about Go feeling like modern C (with a boehm gc included if you will). We're using it this way and it feels just fine. I'd be happy to see parts of our C codebase rewritten in Go, but since that code is security sensitive and has already been through a number of security reviews there's little motivation to do so.
My specific use case is yes, but there are a ton of microcontrollers running realtime tasks all around us: brakes in cars, washing machine controllers, PID loops to regulate fans in your computer, ...
Embedded systems in general are far more common than "normal" computers, and many of them have varying levels of realtime requirements. Don't believe me? Every classical computer or phone will contain multiple microcontrollers, such as an SSD controller, a fan controller, wifi module, cellular baseband processor, ethernet NIC, etc. Depending on the exact specs of your device of course. Each SOC, CPU or GPU will contain multiple hidden helper cores that effectively run as embedded systems (Intel ME, AMD PSP, thermal management, and more). Add to that all the appliances, cars, toys, IOT things, smartcards, etc all around us.
No, I don't think it is niche. Fewer people may work on these, but they run in far more places.
Some embedded use cases would be fine with a GC (MicroPython is also a thing after all). Some want deterministic deallocation. Some want no dynamic allocator at all. From what I have seen, far more products are in the latter two categories. While many hobby projects fall into the first two categories. That is of course a broad generalization, but there is sole truth to it.
Many products want to avoid allocation entirely either because of the realtime properties, or because they are cost sensitive and it is worth spending a little bit extra dev effort to be able to save an Euro or two and use a cheaper microcontroller where the allocator overhead won't fit (either the code in flash, or just the bookkeeping in RAM).
You can also see it differently: If the language dictates a 4x increase in memory or CPU usage, you have set a much closer deadline before you need to upgrade the machine or rearchitect your code to become a distributed system by a factor 4 as well.
Previously, delivering a system (likely in C++) that consumed factor 4 fewer resources was an effort that cost developer time at a much higher factor, especially if you had uptime requirements. With Rust and similar low-overhead languages, the ratio changes drastically. It is much cheaper to deliver high-performance solutions that scale to the full capabilities of the hardware.