The corresponding concept in gears is to avoid meshing two gears unless the number of teeth are co-prime, because this will cause uneven wear patterns. If the tooth counts are coprime, then each tooth will contact every tooth on the other gear the same number of times, effectively "wear leveling" the teeth.
In this instance, one fix is to fire the timer every 59.XXX seconds, so it will naturally drift out of phase with the minute hand of the clock.
If work needs to be done exactly every 60 seconds, this is fixed by having a WAIT(RAND(60e6)) microseconds during the first timer initialization, so if 10,000 units start simultaneously they don't try all at once. This is good practice in most (all?) systems. Hint: test power and infra outage/reconnect, which can unintentionally sync timers.
This is why many software will do automated updates every 17 hours: 17 is coprime with 24.
Classic "thundering herd" mitigation tactics.
Edit: Tempting to blame IoT, but (since this is news) I don't think anyone knew there was something to fix here. We have the tools however.
It depends on a lot of factors, but even second granularity gives you a 60x reduction in the thundering herd. Whether more is needed or even possible often depends on the specific problem domain. For example, if your task takes 20ms, us granularity doesn’t help. Indeed it makes it worse if you’re using randomization because there’s a lot more microseconds than seconds so you can end up with a lot of work that ends up in practice still getting scheduled together due to other delays.
You want your jitter to be significantly >> than the time your task takes as otherwise you get non intuitive degradation that can reintroduce the problem you’re trying to solve. It’s a balancing act picking the jitter that drops off the thundering herd enough and one that is still greater than the time your work takes.
Small nit: Wait(50+rand(10)) is probably closer to what you want to get about a minute between executions. As stated your proposed execution has an average about 30s execution interval with a variance of about 17s. If you’re talking about a random sleep on a 1 minute interval, this actually results in a possibility of 120s between tasks, also not what you want.
But yeah, as soon as you start using Rand most people make all sorts of mistakes. And if you’re using C Rand, don’t. It has other statistical problems.
He’s still allowing for exactly 60s between executions. He’s saying stagger the startup by a random amount up to 60s. Then we get what we want every 60s, but they’re all just staggered a random amount.
My bad. I misread it. Delaying the start like that does divide the thundering herd peak by 60. The point about c Rand stands.
The other thing to watch out for is you’ve still got 1/60 of the thundering herd at the second level. If the tasks are <1s and you have enough of them (as you probably do at grid scale), then doing it finer grained is warranted like offsetting the timer by a millisecond sleep of 10 * uniform_distribution<int> between 0 and 6000. That then gives you 10ms granularity, distributing the workload by two more orders of magnitude.
I almost wrote 59.999 seconds too, but I figured someone would nitpick that the timing often won't be that accurate or will get coalesced. ;)
I should have said, you almost always want to use the randomly staggered timers on initialization, not just when the exact timer interval matters! It's also important to test electricity or backend outages, which can unintentionally synchronize all the timers.
You have good advice and I missed the “on startup” for the wait.
A common aggregation is about 10ms although most OSes can give you finer granularity accuracy if you ask for it and have permissions. It really depends on how long the task takes and whether there’s any non-uniformity in its processing to make finer granularity helpful or harmful.
Unfortunately some people do read advice like it’s mana from the gods instead of thinking through the implication on their specific problem.
I know my older APC UPSes do weekly self tests, but I guess newer equipment does more frequent self testing? And of course they're all internet-connected meaning clocks are within a few hundred ms of each other.
It also made me think about how many GitHub Actions I have that kick off on Sunday morning at a specific time. I try to vary the time/day for those jobs but I'm guessing there are enough things that kick off at specific time intervals to make an impact at the top of an hour, or at :15, :30, :45...
This is why systemd gives you the RandomizedDelaySec option. (Other cron-like facilities may have similar features, I'm not discussing them here). Set that to N and each time the timer reaches its trigger (say, once per day), its actual start will be up to N seconds after the trigger. E.g. if a once-per-day trigger is at midnight but you have RandomizedDelaySec=300 set, then it will run sometime between 0:00:00 and 0:05:00, with a different actual start time each day.
If enough people used that, with a high enough value of N (say 1800 for jobs that really don't have to start at any particular time), it would greatly spread out the spikes in accidentally-coordinated usage.
Cool, I thought grid stability attacks would rely on large numbers of IoT devices but it looks like computing infrastructure is the better target.
Whether it's by buying and using a trillion tokens strategically or by inserting synchronized malicious jobs it should be possible to find some resonant frequencies in the line frequency control system. By loading and unloading multi-megawatts of draw you could get the local supply throttling up and down enough desynchronize from the larger grid. If you could get real time measurements of the line frequency you could use that to tune your malicious load and do the whole 'pushing a kid at the peak of their swing' thing.
To mitigate you would have to put dummy loads or some kind of minute-scale power storage onsite or nearby to compute loads.
Multiple MW is noise level, even to a single moderately sized power production facility, let alone the whole grid region. This is not a viable attack. I can have an entire aluminum smelter trip off or start up and it won't phase my supply, a data center is going to be trivial unless you can spend enough to control all the data centers in which case youve just made the least efficient grid attack in history.
Further, there is no single resonant frequency, only the particular resonance of that exact moment in time. The grid is composed of many generating units, many transmission lines, many transformers. The resonant frequency of the grid is changing moment to moment as those things come online, get loaded partially, go offline, heat up, etc.
Ones and twos of MW are indeed tiny loads, there is a 1MW motor where I work that gets flicked on and off like a light switch, but hyperscale canters are in the >100MW range, that's >1% of even the largest generating stations in the USA.
And you're not aiming for some physical resonant frequency of the entire grid, just the controller on your local generator, getting it to ramp up and down chasing just behind your changing load.
I live in Ontario and in the past week the difference between our highest and lowest demand was ~4.5GW, but those changes take place over hours. If you can ramp up and down a 0.1GW load over minutes there is going to be a point where some control loop can't keep up. Generators have physical inertia but compute loads do not.
I agree that it's not trivial, not cheap, and not efficient but with the state of the world it would not be a surprise if some nation thought it would be useful to burn resources in order to disrupt an important event, maybe elections?
I'm not sure I agree with the conclusion that this is merely caused by UPS system control logic. That is an extreme amount of coordination across a lot of makes, models and configurations.
The FFT indicates this is a periodic signal, not a once a day or week thing. It's happening continuously all day every day. I don't know of any UPS systems that perform tests with this kind of regularity.
In any case, I refuse to believe an external sync signal is causing this. The more likely explanation is that the active elements are pulling each other to a common mode due to being physically coupled on the same grid. This is like how clocks on the same beam will synchronize.
The external sync here is NTP. Synchronized clocks + timer-scheduled actions → globally synchronized behavior
From the article:
> The origin of these current peaks was independently confirmed by the manufacturer to be periodic self-tests executed by the battery EMS, confirming our interpretation. Similar minute-scale diagnostic routines are also documented for other commercial UPS systems (cf. Supplementary Note 8).
A very interesting article, but it is disappointingly vague about what these UPS self tests are, and exactly how they cause disruption to the power grid. Figure 5b shows that their building's UPS has 20-amp spikes exactly every minute, which is a pretty big spike. My guess is that a UPS performs a self test by switching from line power to battery power. If most of the UPS units in a country do that exactly every minute, synchronized by NNTP, yeah I can see that it would mess up the grid having all that load dumped at once. (Although the observed frequency disturbance of 1.5 mHz is extremely small, 3/1000 of a percent.) Now that the problem is identified, it should be trivial for UPS manufacturers to eliminate it.
(By the way, the article is in Nature Energy, not Nature which the URL suggests.)
The corresponding concept in gears is to avoid meshing two gears unless the number of teeth are co-prime, because this will cause uneven wear patterns. If the tooth counts are coprime, then each tooth will contact every tooth on the other gear the same number of times, effectively "wear leveling" the teeth.
In this instance, one fix is to fire the timer every 59.XXX seconds, so it will naturally drift out of phase with the minute hand of the clock.
If work needs to be done exactly every 60 seconds, this is fixed by having a WAIT(RAND(60e6)) microseconds during the first timer initialization, so if 10,000 units start simultaneously they don't try all at once. This is good practice in most (all?) systems. Hint: test power and infra outage/reconnect, which can unintentionally sync timers.
This is why many software will do automated updates every 17 hours: 17 is coprime with 24.
Classic "thundering herd" mitigation tactics.
Edit: Tempting to blame IoT, but (since this is news) I don't think anyone knew there was something to fix here. We have the tools however.
59 seconds will still have second alignment. Maybe it needs to be prime milliseconds or microseconds.
It depends on a lot of factors, but even second granularity gives you a 60x reduction in the thundering herd. Whether more is needed or even possible often depends on the specific problem domain. For example, if your task takes 20ms, us granularity doesn’t help. Indeed it makes it worse if you’re using randomization because there’s a lot more microseconds than seconds so you can end up with a lot of work that ends up in practice still getting scheduled together due to other delays.
You want your jitter to be significantly >> than the time your task takes as otherwise you get non intuitive degradation that can reintroduce the problem you’re trying to solve. It’s a balancing act picking the jitter that drops off the thundering herd enough and one that is still greater than the time your work takes.
Small nit: Wait(50+rand(10)) is probably closer to what you want to get about a minute between executions. As stated your proposed execution has an average about 30s execution interval with a variance of about 17s. If you’re talking about a random sleep on a 1 minute interval, this actually results in a possibility of 120s between tasks, also not what you want.
But yeah, as soon as you start using Rand most people make all sorts of mistakes. And if you’re using C Rand, don’t. It has other statistical problems.
He’s still allowing for exactly 60s between executions. He’s saying stagger the startup by a random amount up to 60s. Then we get what we want every 60s, but they’re all just staggered a random amount.
My bad. I misread it. Delaying the start like that does divide the thundering herd peak by 60. The point about c Rand stands.
The other thing to watch out for is you’ve still got 1/60 of the thundering herd at the second level. If the tasks are <1s and you have enough of them (as you probably do at grid scale), then doing it finer grained is warranted like offsetting the timer by a millisecond sleep of 10 * uniform_distribution<int> between 0 and 6000. That then gives you 10ms granularity, distributing the workload by two more orders of magnitude.
I almost wrote 59.999 seconds too, but I figured someone would nitpick that the timing often won't be that accurate or will get coalesced. ;)
I should have said, you almost always want to use the randomly staggered timers on initialization, not just when the exact timer interval matters! It's also important to test electricity or backend outages, which can unintentionally synchronize all the timers.
You have good advice and I missed the “on startup” for the wait.
A common aggregation is about 10ms although most OSes can give you finer granularity accuracy if you ask for it and have permissions. It really depends on how long the task takes and whether there’s any non-uniformity in its processing to make finer granularity helpful or harmful.
Unfortunately some people do read advice like it’s mana from the gods instead of thinking through the implication on their specific problem.
Coprime meaning "no common factors".
I know my older APC UPSes do weekly self tests, but I guess newer equipment does more frequent self testing? And of course they're all internet-connected meaning clocks are within a few hundred ms of each other.
It also made me think about how many GitHub Actions I have that kick off on Sunday morning at a specific time. I try to vary the time/day for those jobs but I'm guessing there are enough things that kick off at specific time intervals to make an impact at the top of an hour, or at :15, :30, :45...
This is why systemd gives you the RandomizedDelaySec option. (Other cron-like facilities may have similar features, I'm not discussing them here). Set that to N and each time the timer reaches its trigger (say, once per day), its actual start will be up to N seconds after the trigger. E.g. if a once-per-day trigger is at midnight but you have RandomizedDelaySec=300 set, then it will run sometime between 0:00:00 and 0:05:00, with a different actual start time each day.
If enough people used that, with a high enough value of N (say 1800 for jobs that really don't have to start at any particular time), it would greatly spread out the spikes in accidentally-coordinated usage.
Cool, I thought grid stability attacks would rely on large numbers of IoT devices but it looks like computing infrastructure is the better target.
Whether it's by buying and using a trillion tokens strategically or by inserting synchronized malicious jobs it should be possible to find some resonant frequencies in the line frequency control system. By loading and unloading multi-megawatts of draw you could get the local supply throttling up and down enough desynchronize from the larger grid. If you could get real time measurements of the line frequency you could use that to tune your malicious load and do the whole 'pushing a kid at the peak of their swing' thing.
To mitigate you would have to put dummy loads or some kind of minute-scale power storage onsite or nearby to compute loads.
Multiple MW is noise level, even to a single moderately sized power production facility, let alone the whole grid region. This is not a viable attack. I can have an entire aluminum smelter trip off or start up and it won't phase my supply, a data center is going to be trivial unless you can spend enough to control all the data centers in which case youve just made the least efficient grid attack in history.
Further, there is no single resonant frequency, only the particular resonance of that exact moment in time. The grid is composed of many generating units, many transmission lines, many transformers. The resonant frequency of the grid is changing moment to moment as those things come online, get loaded partially, go offline, heat up, etc.
This is not a child on a swing set problem.
Ones and twos of MW are indeed tiny loads, there is a 1MW motor where I work that gets flicked on and off like a light switch, but hyperscale canters are in the >100MW range, that's >1% of even the largest generating stations in the USA.
And you're not aiming for some physical resonant frequency of the entire grid, just the controller on your local generator, getting it to ramp up and down chasing just behind your changing load.
I live in Ontario and in the past week the difference between our highest and lowest demand was ~4.5GW, but those changes take place over hours. If you can ramp up and down a 0.1GW load over minutes there is going to be a point where some control loop can't keep up. Generators have physical inertia but compute loads do not.
I agree that it's not trivial, not cheap, and not efficient but with the state of the world it would not be a surprise if some nation thought it would be useful to burn resources in order to disrupt an important event, maybe elections?
I'm not sure I agree with the conclusion that this is merely caused by UPS system control logic. That is an extreme amount of coordination across a lot of makes, models and configurations.
The FFT indicates this is a periodic signal, not a once a day or week thing. It's happening continuously all day every day. I don't know of any UPS systems that perform tests with this kind of regularity.
In any case, I refuse to believe an external sync signal is causing this. The more likely explanation is that the active elements are pulling each other to a common mode due to being physically coupled on the same grid. This is like how clocks on the same beam will synchronize.
https://en.wikipedia.org/wiki/Injection_locking
The external sync here is NTP. Synchronized clocks + timer-scheduled actions → globally synchronized behavior
From the article:
> The origin of these current peaks was independently confirmed by the manufacturer to be periodic self-tests executed by the battery EMS, confirming our interpretation. Similar minute-scale diagnostic routines are also documented for other commercial UPS systems (cf. Supplementary Note 8).
https://www.snaptec.com.au/akkutec-4801-din-user-manual.pdf
> battery circuit testing 1 x per minute for 1 sec
https://adelsystem.com/hubfs/PDF%20DC-UPS/Instruction%20Manu...
> The battery testing is carried out automatically every 60 sec.
A very interesting article, but it is disappointingly vague about what these UPS self tests are, and exactly how they cause disruption to the power grid. Figure 5b shows that their building's UPS has 20-amp spikes exactly every minute, which is a pretty big spike. My guess is that a UPS performs a self test by switching from line power to battery power. If most of the UPS units in a country do that exactly every minute, synchronized by NNTP, yeah I can see that it would mess up the grid having all that load dumped at once. (Although the observed frequency disturbance of 1.5 mHz is extremely small, 3/1000 of a percent.) Now that the problem is identified, it should be trivial for UPS manufacturers to eliminate it.
(By the way, the article is in Nature Energy, not Nature which the URL suggests.)
> If most of the UPS units in a country do that exactly every minute, synchronized by NNTP,
Thankfully, usenet usage is way down, so we won't need to worry about this. ;p