3 ms·

Well, yeah, I noticed you guys' response to one of the comments on the blog post indicated that the problem machine had a different workload (additional tasks o

Well, yeah, I noticed you guys' response to one of the comments on the blog post indicated that the problem machine had a different workload (additional tasks or something). That caused the additional writes, which then caused the latency for the main app on the box. I think your point still stands about logging, being cautious about blocking I/O calls, etc. But, it seems the bigger point is one of how your overall system is architected, which proccesses run where, dedicating like nodes to their tasks vs. potential quality/consistency issues arising from having some pull double-duty, etc. Those seemed to be the source of the real issue here.

evan_miller 12y ago
Sort of. The catch is that even a very small write, say just a few megabytes, can drastically change the cost of an fsync(). On my test aws VM even writing just 4 megabytes one time is enough to trigger the problem. Even on an otherwise fully isolated system a few megs may be written from time to time, for example by a management agent like chef or puppet. Or by an application deploy copying out new binaries. For example, here I reproduce the problem on a completely isolated machine: https://news.ycombinator.com/item?id=8359556 https://news.ycombinator.com/item?id=8359556
- jamesaguilar 12y ago
  IMO the real issue is that a competent logging framework doesn't block app code to sync the log to disk. The buffer should be swapped out under lock, and then synced in a separate thread. Yuck.
  - shabble 12y ago
    The downside is of course that if you crash hard, the most valuable log entries are the ones least likely to be on-disk afterwards.
    - snuxoll 12y ago
      Which is why logging to disk on the server is BAD, have your log framework write to stdout and have upstart/systemd/whatever handle writing to a remote syslog server or whatever your fancy is.
- unclebucknasty 12y ago
  Good points. I got something out of it on both fronts.

evan_miller 12y ago

Sort of. The catch is that even a very small write, say just a few megabytes, can drastically change the cost of an fsync(). On my test aws VM even writing just 4 megabytes one time is enough to trigger the problem. Even on an otherwise fully isolated system a few megs may be written from time to time, for example by a management agent like chef or puppet. Or by an application deploy copying out new binaries. For example, here I reproduce the problem on a completely isolated machine: https://news.ycombinator.com/item?id=8359556 https://news.ycombinator.com/item?id=8359556

jamesaguilar 12y ago
IMO the real issue is that a competent logging framework doesn't block app code to sync the log to disk. The buffer should be swapped out under lock, and then synced in a separate thread. Yuck.
- shabble 12y ago
  The downside is of course that if you crash hard, the most valuable log entries are the ones least likely to be on-disk afterwards.
  - snuxoll 12y ago
    Which is why logging to disk on the server is BAD, have your log framework write to stdout and have upstart/systemd/whatever handle writing to a remote syslog server or whatever your fancy is.
unclebucknasty 12y ago
Good points. I got something out of it on both fronts.