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29 Jan 2014 Ruby 2.1's GC is better than ever, but ruby still uses a stop-the-world GC implementation. This means collections triggered during request processing will add latency to your response time. One way to mitigate this is by running GC in-between requests, i.e. "Out-of-Band". OOBGC is a popular technique, first introduced by Unicorn and later integrated into Passenger. Traditionally, these
Ruby 2.1: Out-of-Band GC 29 Jan 2014 Ruby 2.1’s GC is better than ever, but ruby still uses a stop-the-world GC implementation. This means collections triggered during request processing will add latency to your response time. One way to mitigate this is by running GC in-between requests, i.e. “Out-of-Band”. OOBGC is a popular technique, first introduced by Unicorn and later integrated into Passen
26 Dec 2013 ObjectSpace in ruby contains many useful heap debugging utilities. Since 1.9 ruby has included objspace.so which adds even more methods to the ObjectSpace module: ObjectSpace.each_object{ |o| ... } ObjectSpace.count_objects #=> {:TOTAL=>55298, :FREE=>10289, :T_OBJECT=>3371, ...} ObjectSpace.each_object.inject(Hash.new 0){ |h,o| h[o.class]+=1; h } #=> {Class=>416, ...} require 'objspace
30 Dec 2013 Ruby 2.1 adds a "restricted" generational collector, with minor mark phases that dramatically reduce the cost of GC. Let's take a look at the evolution of Ruby's GC. Ruby 1.8: simple mark and sweep Classic mark and sweep implementation. The entire world is stopped during both phases. Traverse object graph from roots and mark live objects, using a bit inside the object structure (FL_MAR
24 Dec 2013 Ruby 2.1 is shipping with rb_profile_frames(), a new C-api for fetching ruby backtraces. The api performs no allocations and adds minimal cpu overhead making it ideal for profiling, even in production environments. I've implemented a sampling callstack profiler for 2.1 called stackprof with this API, using techniques popularized by gperftools and @brendangregg. It works remarkably well
23 Dec 2013 Cpu vs idle time is one of the first things I look at when benchmarking rails requests. Cpu time consists of number crunching, template rendering, method invocation and any other time spent executing instructions on the CPU. Idle time is everything else- generally this is time spent waiting on disk or network I/O, and can be highly variable depending on disk activity, remote server loa
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