Earlier quoted context omitted.
I get the sense that applications with true realtime requirements generally have hard enough requirements that they cannot allow even the remote possibility of failure. Think avionics, medical devices, automotive, military applications. If you really need realtime, then you really need it and "close enough" doesn't really exist. This is just my perception as an outsider though.
Unless its just music
The real realtime preemption end game
61–70 of 281 posts
Re: The real realtime preemption end game
#62What does this mean for the common user? Is this something you would only enable in very specific circumstances or can it also bring a more responsive system to the general public?
Re: The real realtime preemption end game
#63Re: The real realtime preemption end game
#64I wonder if this being fixed will result in it displacing some notable amount of made-for-realtime hardware/software combos. Especially since there's now lots of cheap, relatively low power, and high clock rate ARM and x86 chips to choose from. With the clock rates so high, perfect real-time becomes less important as you would often have many cycles to spare for misses. I understand it's less elegant, efficient, etc.…
But it all depends on what your application is. There are a lot of applications that are "almost real-time" in need. For those, this might be useful.
Re: The real realtime preemption end game
#65Synchronous logging strikes again! We ran into this some at work with GLOG (Google's logging library), which can, e.g., block on disk IO if stdout is a file or whatever. GLOG was like, 90-99% of culprits when our service stalled for over 100ms.
I have discussions with cow-orkers around logging; "We have Best-Effort and Guaranteed-Delivery APIs" "I want Guaranteed Delivery!!!" "If the GD logging interface is offline or slow, you'll take downtime; is that okay?" "NO NO Must not take downtime!" "If you need it logged, and can't log it, what do you do?" These days I just point to the CAP theorem and suggest that logging is the same as any other distributed syst…
Promtail[1] can do this if you're using Loki for logging.
[1] https://grafana.com/docs/loki/latest/send-data/promtail/
Re: The real realtime preemption end game
#66Earlier quoted context omitted.
Yes, there are parts of the space that can't be displaced with this. I'm unclear on why you put "many cycles to spare for misses" in quotes, as if it's unimportant. If a linux/arm (or x86) solution is displacing a much lower speed "real real time" solution, that's the situation...the extra cycles mean you can tolerate some misses while still being as granular as what you're replacing. Not for every use case, but for…
You won't be saved from two tasks deadlocking with cycles/second. this is what hard realtime systems are about. However, I do agree that not all systems have a real hard realtime requirements. But those usually can handle a non-rt kernel. As for the quotes, it was a direct citation, not a way to dismiss what you said.
Actual realtime systems are about workload scheduling that takes into account processing deadlines. Hard realtime systems can make guarantees about processing latencies, and can preemptively kill or skip tasks if the result would arrive too late. But this is not something that the Linux kernel can provide, because it is a system property rather than about just the kernel: you can't provide any hard guarantees if you have no time bounds for your data processing workload. So any discussion about -rt in the context of the Linux kernel will always be about soft realtime only.
Re: The real realtime preemption end game
#67Earlier quoted context omitted.
Unless its just music
Unless that music is being played through a multi kW amplifier into a stadium and an xrun causes damage to the drivers and/or audience (although, they should have hearing protection anyway).
Re: The real realtime preemption end game
#68Earlier quoted context omitted.
I have discussions with cow-orkers around logging; "We have Best-Effort and Guaranteed-Delivery APIs" "I want Guaranteed Delivery!!!" "If the GD logging interface is offline or slow, you'll take downtime; is that okay?" "NO NO Must not take downtime!" "If you need it logged, and can't log it, what do you do?" These days I just point to the CAP theorem and suggest that logging is the same as any other distributed syst…
The better way to do this is to write the logs to a file or an in-memory ring buffer and have a separate thread/process push logs from the file/ring-buffer to the logging service, allowing for retries if the logging service is down or slow (for moderately short values of down/slow). Promtail[1] can do this if you're using Loki for logging. [1] https://grafana.com/docs/loki/latest/send-data/promtail/
a) If your service crashes and it's in-memory, you lose logs
b) If your service can't push logs off (upstream service is down or slow) you either drop logs, run out of memory, or block
Re: The real realtime preemption end game
#69Earlier quoted context omitted.
I have discussions with cow-orkers around logging; "We have Best-Effort and Guaranteed-Delivery APIs" "I want Guaranteed Delivery!!!" "If the GD logging interface is offline or slow, you'll take downtime; is that okay?" "NO NO Must not take downtime!" "If you need it logged, and can't log it, what do you do?" These days I just point to the CAP theorem and suggest that logging is the same as any other distributed syst…
Interesting, I'd think logging is one of the clearest situations when you want best effort. Logging is, almost by definition, not the "core" of your application, so failure to log properly should not prevent the core of the program from working. Killing the whole program because logging server is clearly throwing the baby out with the bathwater. What people probably mean is "logging is important, let's avoid losing l…
Re: The real realtime preemption end game
#70Earlier quoted context omitted.
I have discussions with cow-orkers around logging; "We have Best-Effort and Guaranteed-Delivery APIs" "I want Guaranteed Delivery!!!" "If the GD logging interface is offline or slow, you'll take downtime; is that okay?" "NO NO Must not take downtime!" "If you need it logged, and can't log it, what do you do?" These days I just point to the CAP theorem and suggest that logging is the same as any other distributed syst…
The better way to do this is to write the logs to a file or an in-memory ring buffer and have a separate thread/process push logs from the file/ring-buffer to the logging service, allowing for retries if the logging service is down or slow (for moderately short values of down/slow). Promtail[1] can do this if you're using Loki for logging. [1] https://grafana.com/docs/loki/latest/send-data/promtail/