294 lines
12 KiB
Markdown
294 lines
12 KiB
Markdown
---
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stage: none
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group: unassigned
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info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#assignments
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---
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# Profiling
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To make it easier to track down performance problems GitLab comes with a set of
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profiling tools, some of these are available by default while others need to be
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explicitly enabled.
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## Profiling a URL
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There is a `Gitlab::Profiler.profile` method, and corresponding
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`bin/profile-url` script, that enable profiling a GET or POST request to a
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specific URL, either as an anonymous user (the default) or as a specific user.
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The first argument to the profiler is either a full URL
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(including the instance hostname) or an absolute path, including the
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leading slash.
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When using the script, command-line documentation is available by passing no
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arguments.
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When using the method in an interactive console session, any changes to the
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application code within that console session is reflected in the profiler
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output.
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For example:
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```ruby
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Gitlab::Profiler.profile('/my-user')
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# Returns a RubyProf::Profile for the regular operation of this request
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class UsersController; def show; sleep 100; end; end
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Gitlab::Profiler.profile('/my-user')
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# Returns a RubyProf::Profile where 100 seconds is spent in UsersController#show
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```
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For routes that require authorization you must provide a user to
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`Gitlab::Profiler`. You can do this like so:
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```ruby
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Gitlab::Profiler.profile('/gitlab-org/gitlab-test', user: User.first)
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```
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Passing a `logger:` keyword argument to `Gitlab::Profiler.profile` sends
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ActiveRecord and ActionController log output to that logger. Further options are
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documented with the method source.
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```ruby
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Gitlab::Profiler.profile('/gitlab-org/gitlab-test', user: User.first, logger: Logger.new($stdout))
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```
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There is also a RubyProf printer available:
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`Gitlab::Profiler::TotalTimeFlatPrinter`. This acts like
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`RubyProf::FlatPrinter`, but its `min_percent` option works on the method's
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total time, not its self time. (This is because we often spend most of our time
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in library code, but this comes from calls in our application.) It also offers a
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`max_percent` option to help filter out outer calls that aren't useful (like
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`ActionDispatch::Integration::Session#process`).
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There is a convenience method for using this,
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`Gitlab::Profiler.print_by_total_time`:
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```ruby
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result = Gitlab::Profiler.profile('/my-user')
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Gitlab::Profiler.print_by_total_time(result, max_percent: 60, min_percent: 2)
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# Measure Mode: wall_time
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# Thread ID: 70005223698240
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# Fiber ID: 70004894952580
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# Total: 1.768912
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# Sort by: total_time
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#
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# %self total self wait child calls name
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# 0.00 1.017 0.000 0.000 1.017 14 *ActionView::Helpers::RenderingHelper#render
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# 0.00 1.017 0.000 0.000 1.017 14 *ActionView::Renderer#render_partial
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# 0.00 1.017 0.000 0.000 1.017 14 *ActionView::PartialRenderer#render
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# 0.00 1.007 0.000 0.000 1.007 14 *ActionView::PartialRenderer#render_partial
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# 0.00 0.930 0.000 0.000 0.930 14 Hamlit::TemplateHandler#call
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# 0.00 0.928 0.000 0.000 0.928 14 Temple::Engine#call
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# 0.02 0.865 0.000 0.000 0.864 638 *Enumerable#inject
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```
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To print the profile in HTML format, use the following example:
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```ruby
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result = Gitlab::Profiler.profile('/my-user')
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printer = RubyProf::CallStackPrinter.new(result)
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printer.print(File.open('/tmp/profile.html', 'w'))
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```
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### Stackprof support
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By default, `Gitlab::Profiler.profile` uses a tracing profiler called [`ruby-prof`](https://ruby-prof.github.io/). However, sampling profilers
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[run faster and use less memory](https://jvns.ca/blog/2017/12/17/how-do-ruby---python-profilers-work-/), so they might be preferred.
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You can switch to [Stackprof](https://github.com/tmm1/stackprof) (a sampling profiler) to generate a profile by passing `sampling_mode: true`.
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Pass in a `profiler_options` hash to configure the output file (`out`) of the sampling data. For example:
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```ruby
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Gitlab::Profiler.profile('/gitlab-org/gitlab-test', user: User.first, sampling_mode: true, profiler_options: { out: 'tmp/profile.dump' })
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```
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You can get a summary of where time was spent by running Stackprof against the sampling data. For example:
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```shell
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stackprof tmp/profile.dump
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```
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Example sampling data:
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```plaintext
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==================================
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Mode: wall(1000)
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Samples: 8745 (6.92% miss rate)
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GC: 1399 (16.00%)
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==================================
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TOTAL (pct) SAMPLES (pct) FRAME
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1022 (11.7%) 1022 (11.7%) Sprockets::PathUtils#stat
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957 (10.9%) 957 (10.9%) (marking)
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493 (5.6%) 493 (5.6%) Sprockets::PathUtils#entries
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576 (6.6%) 471 (5.4%) Mustermann::AST::Translator#decorator_for
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439 (5.0%) 439 (5.0%) (sweeping)
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630 (7.2%) 241 (2.8%) Sprockets::Cache::FileStore#get
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208 (2.4%) 208 (2.4%) ActiveSupport::FileUpdateChecker#watched
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206 (2.4%) 206 (2.4%) Digest::Instance#file
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544 (6.2%) 176 (2.0%) Sprockets::Cache::FileStore#safe_open
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176 (2.0%) 176 (2.0%) ActiveSupport::FileUpdateChecker#max_mtime
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268 (3.1%) 147 (1.7%) ActiveRecord::ConnectionAdapters::PostgreSQLAdapter#exec_no_cache
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140 (1.6%) 140 (1.6%) ActiveSupport::BacktraceCleaner#add_gem_filter
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116 (1.3%) 116 (1.3%) Bootsnap::CompileCache::ISeq.storage_to_output
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160 (1.8%) 113 (1.3%) Gem::Version#<=>
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109 (1.2%) 109 (1.2%) block in <main>
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108 (1.2%) 108 (1.2%) Gem::Version.new
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131 (1.5%) 105 (1.2%) Sprockets::EncodingUtils#unmarshaled_deflated
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1166 (13.3%) 82 (0.9%) Mustermann::RegexpBased#initialize
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82 (0.9%) 78 (0.9%) FileUtils.touch
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72 (0.8%) 72 (0.8%) Sprockets::Manifest.compile_match_filter
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71 (0.8%) 70 (0.8%) Grape::Router#compile!
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91 (1.0%) 65 (0.7%) ActiveRecord::ConnectionAdapters::PostgreSQL::DatabaseStatements#query
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93 (1.1%) 64 (0.7%) ActionDispatch::Journey::Path::Pattern::AnchoredRegexp#accept
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59 (0.7%) 59 (0.7%) Mustermann::AST::Translator.dispatch_table
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62 (0.7%) 59 (0.7%) Rails::BacktraceCleaner#initialize
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2492 (28.5%) 49 (0.6%) Sprockets::PathUtils#stat_directory
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242 (2.8%) 49 (0.6%) Gitlab::Instrumentation::RedisBase.add_call_details
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47 (0.5%) 47 (0.5%) URI::RFC2396_Parser#escape
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46 (0.5%) 46 (0.5%) #<Class:0x00000001090c2e70>#__setobj__
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44 (0.5%) 44 (0.5%) Sprockets::Base#normalize_logical_path
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```
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You can also generate flamegraphs:
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```shell
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stackprof --d3-flamegraph tmp/profile.dump > flamegraph.html
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```
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See [the Stackprof documentation](https://github.com/tmm1/stackprof) for more details.
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## Speedscope flamegraphs
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You can generate a flamegraph for a particular URL by selecting a flamegraph sampling mode button in the performance bar or by adding the `performance_bar=flamegraph` parameter to the request.
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Find more information about the views in the [Speedscope docs](https://github.com/jlfwong/speedscope#views).
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Find more information about different sampling modes in the [Stackprof docs](https://github.com/tmm1/stackprof#sampling).
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This is enabled for all users that can access the performance bar.
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## Bullet
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Bullet is a Gem that can be used to track down N+1 query problems. Bullet section is
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displayed on the [performance-bar](../administration/monitoring/performance/performance_bar.md).
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Because Bullet adds quite a bit of logging noise the logging is disabled by default.
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To enable the logging, set the environment variable `ENABLE_BULLET` to a non-empty value before
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starting GitLab. For example:
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```shell
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ENABLE_BULLET=true bundle exec rails s
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```
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Bullet logs query problems to both the Rails log as well as the browser
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console.
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As a follow up to finding `N+1` queries with Bullet, consider writing a [QueryRecoder test](query_recorder.md) to prevent a regression.
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## System stats
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During or after profiling, you may want to get detailed information about the Ruby virtual machine process,
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such as memory consumption, time spent on CPU, or garbage collector statistics. These are easy to produce individually
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through various tools, but for convenience, a summary endpoint has been added that exports this data as a JSON payload:
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```shell
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curl localhost:3000/-/metrics/system | jq
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```
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Example output:
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```json
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{
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"version": "ruby 2.7.2p137 (2020-10-01 revision a8323b79eb) [x86_64-linux-gnu]",
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"gc_stat": {
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"count": 118,
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"heap_allocated_pages": 11503,
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"heap_sorted_length": 11503,
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"heap_allocatable_pages": 0,
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"heap_available_slots": 4688580,
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"heap_live_slots": 3451712,
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"heap_free_slots": 1236868,
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"heap_final_slots": 0,
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"heap_marked_slots": 3451450,
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"heap_eden_pages": 11503,
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"heap_tomb_pages": 0,
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"total_allocated_pages": 11503,
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"total_freed_pages": 0,
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"total_allocated_objects": 32679478,
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"total_freed_objects": 29227766,
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"malloc_increase_bytes": 84760,
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"malloc_increase_bytes_limit": 32883343,
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"minor_gc_count": 88,
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"major_gc_count": 30,
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"compact_count": 0,
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"remembered_wb_unprotected_objects": 114228,
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"remembered_wb_unprotected_objects_limit": 228456,
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"old_objects": 3185330,
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"old_objects_limit": 6370660,
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"oldmalloc_increase_bytes": 21838024,
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"oldmalloc_increase_bytes_limit": 119181499
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},
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"memory_rss": 1326501888,
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"memory_uss": 1048563712,
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"memory_pss": 1139554304,
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"time_cputime": 82.885264633,
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"time_realtime": 1610459445.5579069,
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"time_monotonic": 24001.23145713,
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"worker_id": "puma_0"
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}
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```
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NOTE:
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This endpoint is only available for Rails web workers. Sidekiq workers can not be inspected this way.
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## Settings that impact performance
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### Application settings
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1. `development` environment by default works with hot-reloading enabled, this makes Rails to check file changes every request, and create a potential contention lock, as hot reload is single threaded.
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1. `development` environment can load code lazily once the request is fired which results in first request to always be slow.
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To disable those features for profiling/benchmarking set the `RAILS_PROFILE` environment variable to `true` before starting GitLab. For example when using GDK:
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- create a file [`env.runit`](https://gitlab.com/gitlab-org/gitlab-development-kit/-/blob/main/doc/runit.md#modifying-environment-configuration-for-services) in the root GDK directory
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- add `export RAILS_PROFILE=true` to your `env.runit` file
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- restart GDK with `gdk restart`
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*This environment variable is only applicable for the development mode.*
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### GC settings
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Ruby's garbage collector (GC) can be tuned via a variety of environment variables that will directly impact application performance.
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The following table lists these variables along with their default values.
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| Environment variable | Default value |
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|--|--|
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| `RUBY_GC_HEAP_INIT_SLOTS` | `10000` |
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| `RUBY_GC_HEAP_FREE_SLOTS` | `4096` |
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| `RUBY_GC_HEAP_FREE_SLOTS_MIN_RATIO` | `0.20` |
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| `RUBY_GC_HEAP_FREE_SLOTS_GOAL_RATIO` | `0.40` |
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| `RUBY_GC_HEAP_FREE_SLOTS_MAX_RATIO` | `0.65` |
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| `RUBY_GC_HEAP_GROWTH_FACTOR` | `1.8` |
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| `RUBY_GC_HEAP_GROWTH_MAX_SLOTS` | `0 (disable)` |
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| `RUBY_GC_HEAP_OLDOBJECT_LIMIT_FACTOR` | `2.0` |
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| `RUBY_GC_MALLOC_LIMIT(_MIN)` | `(16 * 1024 * 1024 /* 16MB */)` |
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| `RUBY_GC_MALLOC_LIMIT_MAX` | `(32 * 1024 * 1024 /* 32MB */)` |
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| `RUBY_GC_MALLOC_LIMIT_GROWTH_FACTOR` | `1.4` |
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| `RUBY_GC_OLDMALLOC_LIMIT(_MIN)` | `(16 * 1024 * 1024 /* 16MB */)` |
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| `RUBY_GC_OLDMALLOC_LIMIT_MAX` | `(128 * 1024 * 1024 /* 128MB */)` |
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| `RUBY_GC_OLDMALLOC_LIMIT_GROWTH_FACTOR` | `1.2` |
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([Source](https://github.com/ruby/ruby/blob/45b29754cfba8435bc4980a87cd0d32c648f8a2e/gc.c#L254-L308))
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GitLab may decide to change these settings in order to speed up application performance, lower memory requirements, or both.
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You can see how each of these settings affect GC performance, memory use and application start-up time for an idle instance of
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GitLab by running the `scripts/perf/gc/collect_gc_stats.rb` script. It will output GC stats and general timing data to standard
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out as CSV.
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