BigW Consortium Gitlab

  1. 13 Jan, 2016 2 commits
    • Randomize metrics sample intervals · 057eb824
      Yorick Peterse authored
      Sampling data at a fixed interval means we can potentially miss data
      from events occurring between sampling intervals. For example, say we
      sample data every 15 seconds but Unicorn workers get killed after 10
      seconds. In this particular case it's possible to miss interesting data
      as the sampler will never get to actually submitting data.
      
      To work around this (at least for the most part) the sampling interval
      is randomized as following:
      
      1. Take the user specified sampling interval (15 seconds by default)
      2. Divide it by 2 (referred to as "half" below)
      3. Generate a range (using a step of 0.1) from -"half" to "half"
      4. Every time the sampler goes to sleep we'll grab the user provided
         interval and add a randomly chosen "adjustment" to it while making
         sure we don't pick the same value twice in a row.
      
      For a specified timeout of 15 this means the actual intervals can be
      anywhere between 7.5 and 22.5, but never can the same interval be used
      twice in a row.
      
      The rationale behind this change is that on dev.gitlab.org I'm sometimes
      seeing certain Gitlab::Git/Rugged objects being retained, but only for a
      few minutes every 24 hours. Knowing the code of Gitlab and how much
      memory it uses/leaks I suspect we're missing data due to workers getting
      terminated before the sampler can write its data to InfluxDB.
  2. 04 Jan, 2016 1 commit
  3. 29 Dec, 2015 1 commit
    • 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.
  4. 17 Dec, 2015 3 commits
    • Track object counts using the "allocations" Gem · f181f05e
      Yorick Peterse authored
      This allows us to track the counts of actual classes instead of "T_XXX"
      nodes. This is only enabled on CRuby as it uses CRuby specific APIs.
    • Track object count types as tags · 09a31156
      Yorick Peterse authored
    • 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.