4 ms·

I do perf work at Facebook, and over time I've become more and more convinced that the most crucial metric is the width of the latency histogram. Narrowing your

by aristus 14y ago

I do perf work at Facebook, and over time I've become more and more convinced that the most crucial metric is the width of the latency histogram. Narrowing your latency band --even if it makes the average case worse-- makes so many systems problems better (top of the list: load balancing) it's not even funny.

jhspaybar 14y ago
I can chime in here that I have had similar experiences at another large scale place :). Some requests would take a second or more to complete with the vast majority finishing in under 100MS. A solution was put in place that added about 5 MS to the average request, but also crushed the long tail(it just doesn't even exist anymore) and everything is hugely more stable and responsive.
- genwin 14y ago
  How was 5 ms added? Multiple sleep states per request? I imagine the long tail disappears in a similar way that a traffic jam is prevented by lowering the speed limit.
  - mixedbit 14y ago
    I think you misunderstood: they optimized the long running requests and the optimization incurred 5ms performance loss for short requests. It is not that the additional 5ms solved the problem.
    - deleted 14y ago
      [deleted]
- bshanks 14y ago
  Let's assume that it is unacceptable to have each dyno tell the router each time it finishes a request ( http://news.ycombinator.com/item?id=5217157 http://news.ycombinator.com/item?id=5217157 ). And also that the goal is to reduce worst-case latency. And also that we don't know a priori how many requests each dyno should queue before it is 'full' and rejects further requests ( http://news.ycombinator.com/item?id=5216771 http://news.ycombinator.com/item?id=5216771 ). Proposal: 1) Once per minute (or less often if you have a zillion dynos), each dyno tells the router the maximum number of requests it had queued at any time over the past minute. 2) Using that information, the router recalculates a threshold once a minute that defines how many queued requests is "too many" (e.g. maybe if you have n dynos, you take the log(n)th-busiest-dyno's load as the threshold -- you want the threshold to only catch the tail). 3) When each request is sent to a dyno, a header fields is added that tells the dyno the current 'too many' threshold. 4) If the receiving dyno has too many, it passes the request back to the router, telling the router that it's busy ( http://news.ycombinator.com/item?id=5217157 http://news.ycombinator.com/item?id=5217157 ). The 'busy' dyno remembers that the router thinks it is 'busy'. The next time its queue is empty, it tells the router "i'm not busy anymore" (and repeats this message once per minute until it receives another request, at which point it assumes the router 'heard'). 5) When a receiving dyno tells the router that it is busy, the router remembers this and stops giving requests to that dyno until the dyno tells it that it is not busy anymore. I haven't worked on stuff like this myself, do you think that would work?
harshreality 14y ago
I seem to recall Google mentioning on some blog several years ago that high variance in response latency degrades user experience much more than slightly higher average request times. I can't find the link though; if anyone has it, I'd be grateful.
- mvgoogler 14y ago
  Sounds like Jeff Dean :-) http://cacm.acm.org/magazines/2013/2/160173-the-tail-at-scale/fulltext http://cacm.acm.org/magazines/2013/2/160173-the-tail-at-scal...
- nostrademons 14y ago
  Jeff Dean wrote a paper on it for CACM: http://cacm.acm.org/magazines/2013/2/160173-the-tail-at-scale/fulltext http://cacm.acm.org/magazines/2013/2/160173-the-tail-at-scal... There's a relatively easy fix for Heroku. They should do random routing with a backup second request sent if the first request times fails to respond after a relatively short period of time (say, 95th percentile latency), killing any outstanding requests when the first response comes back in. The amount of bookkeeping required for this is a lot less than full-on intelligent routing, but it can reduce tail latency dramatically since it's very unlikely that the second request will hit the same overloaded server.
  - gojomo 14y ago
    A relatively easy fix, for read-only or idempotent requests. Also, if long-tail latency requests wind up being run twice, this technique might accelerate tip-over saturation. Still, this 'hedged request' idea is good to keep in mind, thanks for the pointer. The 'tied request' idea from the Dean paper is neat, too, and Heroku could possibly implement that, and give dyno request-handlers the ability to check, "did I win the race to handle this, or can this request be dropped?"
  - deleted 14y ago
    [deleted]
  - badgar 14y ago
    > There's a relatively easy fix for Heroku. They should do random routing with a backup second request sent if the first request times fails to respond after a relatively short period of time (say, 95th percentile latency), killing any outstanding requests when the first response comes back in. The amount of bookkeeping required for this is a lot less than full-on intelligent routing, but it can reduce tail latency dramatically since it's very unlikely that the second request will hit the same overloaded server. Your solution doesn't work if requests aren't idempotent.
bmohlenhoff 14y ago
Correct, this matches my observations as well. I'd trade an increase in mean latency for a decrease in worst-case latency anytime. It makes it so much easier to reason about how many resources are needed for a given workload when your latency is bounded.
dbpatterson 14y ago
That's probably true, but the value that Heroku is selling (and they charge a lot for it!) is that you _don't_ need to deal with this - that they will balance that out for you.
cmccabe 14y ago
> Narrowing your latency band --even if it makes the average case worse-- makes so many systems problems better (top of the list: load balancing) it's not even funny. Yeah, it's a lot more practical than implementing QoS, isn't it?

by aristus 14y ago

jhspaybar 14y ago

I can chime in here that I have had similar experiences at another large scale place :). Some requests would take a second or more to complete with the vast majority finishing in under 100MS. A solution was put in place that added about 5 MS to the average request, but also crushed the long tail(it just doesn't even exist anymore) and everything is hugely more stable and responsive.

genwin 14y ago
How was 5 ms added? Multiple sleep states per request? I imagine the long tail disappears in a similar way that a traffic jam is prevented by lowering the speed limit.
- mixedbit 14y ago
  I think you misunderstood: they optimized the long running requests and the optimization incurred 5ms performance loss for short requests. It is not that the additional 5ms solved the problem.
  - deleted 14y ago
    [deleted]
bshanks 14y ago
Let's assume that it is unacceptable to have each dyno tell the router each time it finishes a request ( http://news.ycombinator.com/item?id=5217157 http://news.ycombinator.com/item?id=5217157 ). And also that the goal is to reduce worst-case latency. And also that we don't know a priori how many requests each dyno should queue before it is 'full' and rejects further requests ( http://news.ycombinator.com/item?id=5216771 http://news.ycombinator.com/item?id=5216771 ). Proposal: 1) Once per minute (or less often if you have a zillion dynos), each dyno tells the router the maximum number of requests it had queued at any time over the past minute. 2) Using that information, the router recalculates a threshold once a minute that defines how many queued requests is "too many" (e.g. maybe if you have n dynos, you take the log(n)th-busiest-dyno's load as the threshold -- you want the threshold to only catch the tail). 3) When each request is sent to a dyno, a header fields is added that tells the dyno the current 'too many' threshold. 4) If the receiving dyno has too many, it passes the request back to the router, telling the router that it's busy ( http://news.ycombinator.com/item?id=5217157 http://news.ycombinator.com/item?id=5217157 ). The 'busy' dyno remembers that the router thinks it is 'busy'. The next time its queue is empty, it tells the router "i'm not busy anymore" (and repeats this message once per minute until it receives another request, at which point it assumes the router 'heard'). 5) When a receiving dyno tells the router that it is busy, the router remembers this and stops giving requests to that dyno until the dyno tells it that it is not busy anymore. I haven't worked on stuff like this myself, do you think that would work?

harshreality 14y ago

I seem to recall Google mentioning on some blog several years ago that high variance in response latency degrades user experience much more than slightly higher average request times. I can't find the link though; if anyone has it, I'd be grateful.

mvgoogler 14y ago
Sounds like Jeff Dean :-) http://cacm.acm.org/magazines/2013/2/160173-the-tail-at-scale/fulltext http://cacm.acm.org/magazines/2013/2/160173-the-tail-at-scal...
nostrademons 14y ago
Jeff Dean wrote a paper on it for CACM: http://cacm.acm.org/magazines/2013/2/160173-the-tail-at-scale/fulltext http://cacm.acm.org/magazines/2013/2/160173-the-tail-at-scal... There's a relatively easy fix for Heroku. They should do random routing with a backup second request sent if the first request times fails to respond after a relatively short period of time (say, 95th percentile latency), killing any outstanding requests when the first response comes back in. The amount of bookkeeping required for this is a lot less than full-on intelligent routing, but it can reduce tail latency dramatically since it's very unlikely that the second request will hit the same overloaded server.
- gojomo 14y ago
  A relatively easy fix, for read-only or idempotent requests. Also, if long-tail latency requests wind up being run twice, this technique might accelerate tip-over saturation. Still, this 'hedged request' idea is good to keep in mind, thanks for the pointer. The 'tied request' idea from the Dean paper is neat, too, and Heroku could possibly implement that, and give dyno request-handlers the ability to check, "did I win the race to handle this, or can this request be dropped?"
- deleted 14y ago
  [deleted]
- badgar 14y ago
  > There's a relatively easy fix for Heroku. They should do random routing with a backup second request sent if the first request times fails to respond after a relatively short period of time (say, 95th percentile latency), killing any outstanding requests when the first response comes back in. The amount of bookkeeping required for this is a lot less than full-on intelligent routing, but it can reduce tail latency dramatically since it's very unlikely that the second request will hit the same overloaded server. Your solution doesn't work if requests aren't idempotent.

bmohlenhoff 14y ago

Correct, this matches my observations as well. I'd trade an increase in mean latency for a decrease in worst-case latency anytime. It makes it so much easier to reason about how many resources are needed for a given workload when your latency is bounded.

dbpatterson 14y ago

That's probably true, but the value that Heroku is selling (and they charge a lot for it!) is that you _don't_ need to deal with this - that they will balance that out for you.

cmccabe 14y ago

> Narrowing your latency band --even if it makes the average case worse-- makes so many systems problems better (top of the list: load balancing) it's not even funny. Yeah, it's a lot more practical than implementing QoS, isn't it?