Maybe I’m dumb because I’m a backend dev, but if we can’t offload these tasks to Async tasks and we need to block the main thread, why can’t we just put up a loading screen?
That’s not the problem. These tasks can be offloaded to async. The underlying issue, and the reason why I think this is an outstanding article, is that running code on the UI thread straight from handlers is easy and more often than not it goes perfectly unnoticed. Only when the execution time of those handlers grow do these blocking calls become an issue.
There’s a gray area between “obviously we need to make these calls async” and “obviously we can run this on the main thread”, and here’s where the real-time mental model and techniques pay off.
“Don’t turn off the application we are saving” games have been doing this for a decade and you can’t convince me that your enterprise application is heavier than a AAA game.
You’re missing the whole point.
The point is that running handlers in the main thread leads to far simpler code and, depending on the usecases, is adopted in scenarios where the approach works well with 99.9% of the conceivable usecases. But then the software starts to be modified and get features added, and some of these code paths start to do more things and take more time to run. When this happens, the 99.9% starts to shrink and some main thread blockages start to become more and more noticeable.
The article does a very good job in underlying the mental model that needs to be in place to avoid this slippery slope to become a problem.
The problem with the article is that it’s confusing hard realtime and low latency requirements. Most UIs do not require hard realtime, even soft realtime is a nice to have and users will tolerate some latency.
I also think the author handwaves “too many blocking calls end up on the main thread.”
Hardly. This is like rule zero for building gui apps. Put any non-trivial or blocking work on a background thread. It was harder to do before mainstream languages got good green thread/async support, but it’s almost trivial now.
I agree that there are still calls that could have variable response times (such as virtual memory being paged in or out), but even low-end machines are RAM-rich and SSDs are damn fast. The kernel is likely also doing some optimization to page stuff in from disk for the foreground app.
It’s nice to think through the issue, but I don’t think it’s quite as dire as the author claims.
The problem with the article is that it’s confusing hard realtime and low latency requirements. Most UIs do not require hard realtime, even soft realtime is a nice to have and users will tolerate some latency.
I don’t think that’s a valid take from the article.
The whole point of the article is that if a handler from a GUI application runs for too long then the application will noticeably block and degrade the user experience.
The real time mindset is critical to be mindful of this failure mode: handlers should have a time budget (compute, waiting dor IO, etc), beyond which the user experience degrades.
The whole point is that GUI applications, just like real-time applications, must be designed with these execution budgets in mind, and once they are not met them the application needs to be redesigned avoid these issues.
Which is what putting most of this stuff on the background accomplishes. It necessitates designing the UX with appropriate feedback. Sometimes you can’t make things go faster than they go. For example, a web request, or pulling data from an ancient disk that a user is using - you as an author don’t have control over these, the OS doesn’t even have control over them.
Should software that depends on external resources refuse to run?
The author is talking about switching to some RTOS due to this, which is extreme. OS vendors have spent decades trying to sort out the “Beachball of Death” issue, that is exceedingly rare on modern systems, due to better multi-tasking support, and dramatically faster hardware.
Most GUI apps are not hard RT and trying to make them so would be incredibly costly and severely limit other aspects of systems that users regularly prefer (like keeping 100 apps and browser tabs open).
Which is what putting most of this stuff on the background accomplishes.
The part you’re missing entirely is the complexity that’s hidden behind the weasel word “most”.
The majority of event handlers from a GUI app do not do anything complex, computationally expensive, or blocking. They do things like setting flags, trigger changes in the UI state (i.e., show/hide/update widgets) bump counters, etc.
No one in their right mind would ever consider going through the trouble of doing this stuff in separate threads/processes. “Most” handlers run perfectly fine on the main thread.
Nevertheless software changes, and today’s onClick handler that sets a flag to true/false tomorrow is required to emit a metric event or switch a different treatment depending on the state of a feature flag or A/B test, or is required to write a setting to disk or something like that.
How do you draw the line in the sand that tells whether this handler should run on the main thread, should trigger a fire-and-forget background task, or should be covered by a dedicated userflow with a complete story board?
That’s the stuff that’s hand-waved away with weasel words like “most”.
This blog post delivers a crisp mental model to tell which approach is suitable: follow the real time computing rulebook, acknowledge that each and every handler has a time budget, and if a handler overspends it’s budget them it needs to be refactored.
That’s not the problem. These tasks can be offloaded to async. The underlying issue, and the reason why I think this is an outstanding article, is that running code on the UI thread straight from handlers is easy and more often than not it goes perfectly unnoticed. Only when the execution time of those handlers grow do these blocking calls become an issue.
There’s a gray area between “obviously we need to make these calls async” and “obviously we can run this on the main thread”, and here’s where the real-time mental model and techniques pay off.
You’re missing the whole point.
The point is that running handlers in the main thread leads to far simpler code and, depending on the usecases, is adopted in scenarios where the approach works well with 99.9% of the conceivable usecases. But then the software starts to be modified and get features added, and some of these code paths start to do more things and take more time to run. When this happens, the 99.9% starts to shrink and some main thread blockages start to become more and more noticeable.
The article does a very good job in underlying the mental model that needs to be in place to avoid this slippery slope to become a problem.
The problem with the article is that it’s confusing hard realtime and low latency requirements. Most UIs do not require hard realtime, even soft realtime is a nice to have and users will tolerate some latency.
I also think the author handwaves “too many blocking calls end up on the main thread.”
Hardly. This is like rule zero for building gui apps. Put any non-trivial or blocking work on a background thread. It was harder to do before mainstream languages got good green thread/async support, but it’s almost trivial now.
I agree that there are still calls that could have variable response times (such as virtual memory being paged in or out), but even low-end machines are RAM-rich and SSDs are damn fast. The kernel is likely also doing some optimization to page stuff in from disk for the foreground app.
It’s nice to think through the issue, but I don’t think it’s quite as dire as the author claims.
I don’t think that’s a valid take from the article.
The whole point of the article is that if a handler from a GUI application runs for too long then the application will noticeably block and degrade the user experience.
The real time mindset is critical to be mindful of this failure mode: handlers should have a time budget (compute, waiting dor IO, etc), beyond which the user experience degrades.
The whole point is that GUI applications, just like real-time applications, must be designed with these execution budgets in mind, and once they are not met them the application needs to be redesigned avoid these issues.
Which is what putting most of this stuff on the background accomplishes. It necessitates designing the UX with appropriate feedback. Sometimes you can’t make things go faster than they go. For example, a web request, or pulling data from an ancient disk that a user is using - you as an author don’t have control over these, the OS doesn’t even have control over them.
Should software that depends on external resources refuse to run?
The author is talking about switching to some RTOS due to this, which is extreme. OS vendors have spent decades trying to sort out the “Beachball of Death” issue, that is exceedingly rare on modern systems, due to better multi-tasking support, and dramatically faster hardware.
Most GUI apps are not hard RT and trying to make them so would be incredibly costly and severely limit other aspects of systems that users regularly prefer (like keeping 100 apps and browser tabs open).
The part you’re missing entirely is the complexity that’s hidden behind the weasel word “most”.
The majority of event handlers from a GUI app do not do anything complex, computationally expensive, or blocking. They do things like setting flags, trigger changes in the UI state (i.e., show/hide/update widgets) bump counters, etc.
No one in their right mind would ever consider going through the trouble of doing this stuff in separate threads/processes. “Most” handlers run perfectly fine on the main thread.
Nevertheless software changes, and today’s onClick handler that sets a flag to true/false tomorrow is required to emit a metric event or switch a different treatment depending on the state of a feature flag or A/B test, or is required to write a setting to disk or something like that.
How do you draw the line in the sand that tells whether this handler should run on the main thread, should trigger a fire-and-forget background task, or should be covered by a dedicated userflow with a complete story board?
That’s the stuff that’s hand-waved away with weasel words like “most”.
This blog post delivers a crisp mental model to tell which approach is suitable: follow the real time computing rulebook, acknowledge that each and every handler has a time budget, and if a handler overspends it’s budget them it needs to be refactored.
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