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  1. 21 Jun, 2017 1 commit
  2. 23 Feb, 2017 3 commits
  3. 28 Jul, 2016 1 commit
    • Yorick Peterse's avatar
      Reduce instrumentation overhead · 905f8d76
      Yorick Peterse authored
      This reduces the overhead of the method instrumentation code primarily
      by reducing the number of method calls. There are also some other small
      optimisations such as not casting timing values to Floats (there's no
      particular need for this), using Symbols for method call metric names,
      and reducing the number of Hash lookups for instrumented methods.
      
      The exact impact depends on the code being executed. For example, for a
      method that's only called once the difference won't be very noticeable.
      However, for methods that are called many times the difference can be
      more significant.
      
      For example, the loading time of a large commit
      (nrclark/dummy_project@81ebdea5df2fb42e59257cb3eaad671a5c53ca36)
      was reduced from around 19 seconds to around 15 seconds using these
      changes.
      905f8d76
  4. 17 Jun, 2016 1 commit
    • Yorick Peterse's avatar
      Track method call times/counts as a single metric · be3b8784
      Yorick Peterse authored
      Previously we'd create a separate Metric instance for every method call
      that would exceed the method call threshold. This is problematic because
      it doesn't provide us with information to accurately get the _total_
      execution time of a particular method. For example, if the method
      "Foo#bar" was called 4 times with a runtime of ~10 milliseconds we'd end
      up with 4 different Metric instances. If we were to then get the
      average/95th percentile/etc of the timings this would be roughly 10
      milliseconds. However, the _actual_ total time spent in this method
      would be around 40 milliseconds.
      
      To solve this problem we now create a single Metric instance per method.
      This Metric instance contains the _total_ real/CPU time and the call
      count for every instrumented method.
      be3b8784
  5. 16 Jun, 2016 2 commits
  6. 14 Jun, 2016 2 commits
  7. 03 Jun, 2016 2 commits
  8. 24 May, 2016 1 commit
  9. 12 May, 2016 1 commit
    • Yorick Peterse's avatar
      Removed tracking of total method execution times · 945c5b3f
      Yorick Peterse authored
      Because method call timings are inclusive (that is, they include the
      time of any sub method calls) this would lead to the total method
      execution time often being far greater than the total transaction time.
      Because this is incredibly confusing it's best to simply _not_ track the
      total method execution time, after all it's not that useful to begin
      with.
      
      Fixes gitlab-org/gitlab-ce#17239
      945c5b3f
  10. 18 Apr, 2016 1 commit
    • Yorick Peterse's avatar
      Use Module#prepend for method instrumentation · 7b6785b3
      Yorick Peterse authored
      By using Module#prepend we can define a Module containing all proxy
      methods. This removes the need for setting up crazy method alias chains
      and in turn prevents us from having to deal with all that madness (e.g.
      methods calling each other recursively).
      
      Fixes gitlab-org/gitlab-ce#15281
      7b6785b3
  11. 25 Jan, 2016 1 commit
    • Yorick Peterse's avatar
      Correct arity for instrumented methods w/o args · b74308c0
      Yorick Peterse authored
      This ensures that an instrumented method that doesn't take arguments
      reports an arity of 0, instead of -1.
      
      If Ruby had a proper method for finding out the required arguments of a
      method (e.g. Method#required_arguments) this would not have been an
      issue. Sadly the only two methods we have are Method#parameters and
      Method#arity, and both are equally painful to use.
      
      Fixes gitlab-org/gitlab-ce#12450
      b74308c0
  12. 04 Jan, 2016 2 commits
  13. 31 Dec, 2015 1 commit
  14. 17 Dec, 2015 9 commits
    • Yorick Peterse's avatar
      Support for instrumenting class hierarchies · a93a32a2
      Yorick Peterse authored
      This will be used to (for example) instrument all ActiveRecord models.
      a93a32a2
    • Yorick Peterse's avatar
      Only track method calls above a certain threshold · a41287d8
      Yorick Peterse authored
      This ensures we don't end up wasting resources by tracking method calls
      that only take a few microseconds. By default the threshold is 10
      milliseconds but this can be changed using the gitlab.yml configuration
      file.
      a41287d8
    • Yorick Peterse's avatar
      Allow filtering of what methods to instrument · 13dbd663
      Yorick Peterse authored
      This makes it possible to determine if a method should be instrumented
      or not using a block.
      13dbd663
    • Yorick Peterse's avatar
      Only instrument methods defined directly · 641761f1
      Yorick Peterse authored
      When using instrument_methods/instrument_instance_methods we only want
      to instrument methods defined directly in a class, not those included
      via mixins (e.g. whatever RSpec throws in during development).
      
      In case an externally included method _has_ to be instrumented we can
      still use the regular instrument_method/instrument_instance_method
      methods.
      641761f1
    • Yorick Peterse's avatar
      Added Instrumentation.configure · f43f3b89
      Yorick Peterse authored
      This makes it easier to instrument multiple modules without having to
      type the full namespace over and over again.
      f43f3b89
    • Yorick Peterse's avatar
      Methods for instrumenting multiple methods · 5dbcb635
      Yorick Peterse authored
      The methods Instrumentation.instrument_methods and
      Instrumentation.instrument_instance_methods can be used to instrument
      all methods of a module at once.
      5dbcb635
    • Yorick Peterse's avatar
      Use custom code for instrumenting method calls · 1b077d2d
      Yorick Peterse authored
      The use of ActiveSupport would slow down instrumented method calls by
      about 180x due to:
      
      1. ActiveSupport itself not being the fastest thing on the planet
      2. caller_locations() having quite some overhead
      
      The use of caller_locations() has been removed because it's not _that_
      useful since we already know the full namespace of receivers and the
      names of the called methods.
      
      The use of ActiveSupport has been replaced with some custom code that's
      generated using eval() (which can be quite a bit faster than using
      define_method).
      
      This new setup results in instrumented methods only being about 35-40x
      slower (compared to non instrumented methods).
      1b077d2d
    • Yorick Peterse's avatar
      Use string evaluation for method instrumentation · b66a16c8
      Yorick Peterse authored
      This is faster than using define_method since we don't have to keep
      block bindings around.
      b66a16c8
    • Yorick Peterse's avatar
      Storing of application metrics in InfluxDB · 141e946c
      Yorick Peterse authored
      This adds the ability to write application metrics (e.g. SQL timings) to
      InfluxDB. These metrics can in turn be visualized using Grafana, or
      really anything else that can read from InfluxDB. These metrics can be
      used to track application performance over time, between different Ruby
      versions, different GitLab versions, etc.
      
      == Transaction Metrics
      
      Currently the following is tracked on a per transaction basis (a
      transaction is a Rails request or a single Sidekiq job):
      
      * Timings per query along with the raw (obfuscated) SQL and information
        about what file the query originated from.
      * Timings per view along with the path of the view and information about
        what file triggered the rendering process.
      * The duration of a request itself along with the controller/worker
        class and method name.
      * The duration of any instrumented method calls (more below).
      
      == Sampled Metrics
      
      Certain metrics can't be directly associated with a transaction. For
      example, a process' total memory usage is unrelated to any running
      transactions. While a transaction can result in the memory usage going
      up there's no accurate way to determine what transaction is to blame,
      this becomes especially problematic in multi-threaded environments.
      
      To solve this problem there's a separate thread that takes samples at a
      fixed interval. This thread (using the class Gitlab::Metrics::Sampler)
      currently tracks the following:
      
      * The process' total memory usage.
      * The number of file descriptors opened by the process.
      * The amount of Ruby objects (using ObjectSpace.count_objects).
      * GC statistics such as timings, heap slots, etc.
      
      The default/current interval is 15 seconds, any smaller interval might
      put too much pressure on InfluxDB (especially when running dozens of
      processes).
      
      == Method Instrumentation
      
      While currently not yet used methods can be instrumented to track how
      long they take to run. Unlike the likes of New Relic this doesn't
      require modifying the source code (e.g. including modules), it all
      happens from the outside. For example, to track `User.by_login` we'd add
      the following code somewhere in an initializer:
      
          Gitlab::Metrics::Instrumentation.
            instrument_method(User, :by_login)
      
      to instead instrument an instance method:
      
          Gitlab::Metrics::Instrumentation.
            instrument_instance_method(User, :save)
      
      Instrumentation for either all public model methods or a few crucial
      ones will be added in the near future, I simply haven't gotten to doing
      so just yet.
      
      == Configuration
      
      By default metrics are disabled. This means users don't have to bother
      setting anything up if they don't want to. Metrics can be enabled by
      editing one's gitlab.yml configuration file (see
      config/gitlab.yml.example for example settings).
      
      == Writing Data To InfluxDB
      
      Because InfluxDB is still a fairly young product I expect the worse.
      Data loss, unexpected reboots, the database not responding, you name it.
      Because of this data is _not_ written to InfluxDB directly, instead it's
      queued and processed by Sidekiq. This ensures that users won't notice
      anything when InfluxDB is giving trouble.
      
      The metrics worker can be started in a standalone manner as following:
      
          bundle exec sidekiq -q metrics
      
      The corresponding class is called MetricsWorker.
      141e946c