1. 01 May, 2017 1 commit
  2. 23 Feb, 2017 2 commits
  3. 17 Aug, 2016 1 commit
    • Yorick Peterse's avatar
      Tracking of custom events · d345591f
      Yorick Peterse authored
      GitLab Performance Monitoring is now able to track custom events not
      directly related to application performance. These events include the
      number of tags pushed, repositories created, builds registered, etc.
      The use of these events is to get a better overview of how a GitLab
      instance is used and how that may affect performance. For example, a
      large number of Git pushes may have a negative impact on the underlying
      storage engine.
      Events are stored in the "events" measurement and are not prefixed with
      "rails_" or "sidekiq_", this makes it easier to query events with the
      same name triggered from different parts of the application. All events
      being stored in the same measurement also makes it easier to downsample
      Currently the following events are tracked:
      * Creating repositories
      * Removing repositories
      * Changing the default branch of a repository
      * Pushing a new tag
      * Removing an existing tag
      * Pushing a commit (along with the branch being pushed to)
      * Pushing a new branc...
  4. 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
      was reduced from around 19 seconds to around 15 seconds using these
  5. 20 Apr, 2016 1 commit
    • Yorick Peterse's avatar
      Fix setting of "action" for Grape transactions · a257d117
      Yorick Peterse authored
      Merely setting the "action" tag will only result in the transaction
      itself containing a value for this tag. To ensure other metrics also
      contain this tag we must set the action using Transaction#action=
  6. 13 Apr, 2016 1 commit
    • Yorick Peterse's avatar
      Added ability to add custom tags to transactions · 3240ecfb
      Yorick Peterse authored
      One use case for this is manually setting the "action" tag for Grape API
      calls. Due to Grape running blocks there are no human readable method
      names that can be used for the "action" tag, thus we have to set these
      manually on a case by case basis.
  7. 11 Apr, 2016 3 commits
  8. 06 Apr, 2016 2 commits
  9. 12 Jan, 2016 1 commit
    • Yorick Peterse's avatar
      Stop tracking call stacks for instrumented views · 355c341f
      Yorick Peterse authored
      Where a vew is called from doesn't matter as much. We already know what
      action they belong to and this is more than enough information. By
      removing the file/line number from the list of tags we should also be
      able to reduce the number of series stored in InfluxDB.
  10. 31 Dec, 2015 2 commits
  11. 29 Dec, 2015 1 commit
    • Yorick Peterse's avatar
      Write to InfluxDB directly via UDP · 620e7bb3
      Yorick Peterse authored
      This removes the need for Sidekiq and any overhead/problems introduced
      by TCP. There are a few things to take into account:
      1. When writing data to InfluxDB you may still get an error if the
         server becomes unavailable during the write. Because of this we're
         catching all exceptions and just ignore them (for now).
      2. Writing via UDP apparently requires the timestamp to be in
         nanoseconds. Without this data either isn't written properly.
      3. Due to the restrictions on UDP buffer sizes we're writing metrics one
         by one, instead of writing all of them at once.
  12. 28 Dec, 2015 1 commit
  13. 17 Dec, 2015 1 commit
    • 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
      == 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:
            instrument_method(User, :by_login)
      to instead instrument an instance method:
            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.