path: root/doc/development/profiling.md

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---

# Profiling

To make it easier to track down performance problems GitLab comes with a set of
profiling tools, some of these are available by default while others need to be
explicitly enabled.

## Profiling a URL

There is a `Gitlab::Profiler.profile` method, and corresponding
`bin/profile-url` script, that enable profiling a GET or POST request to a
specific URL, either as an anonymous user (the default) or as a specific user.

The first argument to the profiler is either a full URL
(including the instance hostname) or an absolute path, including the
leading slash.

When using the script, command-line documentation is available by passing no
arguments.

When using the method in an interactive console session, any changes to the
application code within that console session is reflected in the profiler
output.

For example:

```ruby
Gitlab::Profiler.profile('/my-user')
# Returns a RubyProf::Profile for the regular operation of this request
class UsersController; def show; sleep 100; end; end
Gitlab::Profiler.profile('/my-user')
# Returns a RubyProf::Profile where 100 seconds is spent in UsersController#show
```

For routes that require authorization you must provide a user to
`Gitlab::Profiler`. You can do this like so:

```ruby
Gitlab::Profiler.profile('/gitlab-org/gitlab-test', user: User.first)
```

Passing a `logger:` keyword argument to `Gitlab::Profiler.profile` sends
ActiveRecord and ActionController log output to that logger. Further options are
documented with the method source.

```ruby
Gitlab::Profiler.profile('/gitlab-org/gitlab-test', user: User.first, logger: Logger.new($stdout))
```

There is also a RubyProf printer available:
`Gitlab::Profiler::TotalTimeFlatPrinter`. This acts like
`RubyProf::FlatPrinter`, but its `min_percent` option works on the method's
total time, not its self time. (This is because we often spend most of our time
in library code, but this comes from calls in our application.) It also offers a
`max_percent` option to help filter out outer calls that aren't useful (like
`ActionDispatch::Integration::Session#process`).

There is a convenience method for using this,
`Gitlab::Profiler.print_by_total_time`:

```ruby
result = Gitlab::Profiler.profile('/my-user')
Gitlab::Profiler.print_by_total_time(result, max_percent: 60, min_percent: 2)
# Measure Mode: wall_time
# Thread ID: 70005223698240
# Fiber ID: 70004894952580
# Total: 1.768912
# Sort by: total_time
#
#  %self      total      self      wait     child     calls  name
#   0.00      1.017     0.000     0.000     1.017       14  *ActionView::Helpers::RenderingHelper#render
#   0.00      1.017     0.000     0.000     1.017       14  *ActionView::Renderer#render_partial
#   0.00      1.017     0.000     0.000     1.017       14  *ActionView::PartialRenderer#render
#   0.00      1.007     0.000     0.000     1.007       14  *ActionView::PartialRenderer#render_partial
#   0.00      0.930     0.000     0.000     0.930       14   Hamlit::TemplateHandler#call
#   0.00      0.928     0.000     0.000     0.928       14   Temple::Engine#call
#   0.02      0.865     0.000     0.000     0.864      638  *Enumerable#inject
```

To print the profile in HTML format, use the following example:

```ruby
result = Gitlab::Profiler.profile('/my-user')

printer = RubyProf::CallStackPrinter.new(result)
printer.print(File.open('/tmp/profile.html', 'w'))
```

### Stackprof support

By default, `Gitlab::Profiler.profile` uses a tracing profiler called [`ruby-prof`](https://ruby-prof.github.io/). However, sampling profilers
[run faster and use less memory](https://jvns.ca/blog/2017/12/17/how-do-ruby---python-profilers-work-/), so they might be preferred.

You can switch to [Stackprof](https://github.com/tmm1/stackprof) (a sampling profiler) to generate a profile by passing `sampling_mode: true`.
Pass in a `profiler_options` hash to configure the output file (`out`) of the sampling data. For example:

```ruby
Gitlab::Profiler.profile('/gitlab-org/gitlab-test', user: User.first, sampling_mode: true, profiler_options: { out: 'tmp/profile.dump' })
```

You can get a summary of where time was spent by running Stackprof against the sampling data. For example:

```shell
stackprof tmp/profile.dump
```

Example sampling data:

```plaintext
==================================
  Mode: wall(1000)
  Samples: 8745 (6.92% miss rate)
  GC: 1399 (16.00%)
==================================
     TOTAL    (pct)     SAMPLES    (pct)     FRAME
      1022  (11.7%)        1022  (11.7%)     Sprockets::PathUtils#stat
       957  (10.9%)         957  (10.9%)     (marking)
       493   (5.6%)         493   (5.6%)     Sprockets::PathUtils#entries
       576   (6.6%)         471   (5.4%)     Mustermann::AST::Translator#decorator_for
       439   (5.0%)         439   (5.0%)     (sweeping)
       630   (7.2%)         241   (2.8%)     Sprockets::Cache::FileStore#get
       208   (2.4%)         208   (2.4%)     ActiveSupport::FileUpdateChecker#watched
       206   (2.4%)         206   (2.4%)     Digest::Instance#file
       544   (6.2%)         176   (2.0%)     Sprockets::Cache::FileStore#safe_open
       176   (2.0%)         176   (2.0%)     ActiveSupport::FileUpdateChecker#max_mtime
       268   (3.1%)         147   (1.7%)     ActiveRecord::ConnectionAdapters::PostgreSQLAdapter#exec_no_cache
       140   (1.6%)         140   (1.6%)     ActiveSupport::BacktraceCleaner#add_gem_filter
       116   (1.3%)         116   (1.3%)     Bootsnap::CompileCache::ISeq.storage_to_output
       160   (1.8%)         113   (1.3%)     Gem::Version#<=>
       109   (1.2%)         109   (1.2%)     block in <main>
       108   (1.2%)         108   (1.2%)     Gem::Version.new
       131   (1.5%)         105   (1.2%)     Sprockets::EncodingUtils#unmarshaled_deflated
      1166  (13.3%)          82   (0.9%)     Mustermann::RegexpBased#initialize
        82   (0.9%)          78   (0.9%)     FileUtils.touch
        72   (0.8%)          72   (0.8%)     Sprockets::Manifest.compile_match_filter
        71   (0.8%)          70   (0.8%)     Grape::Router#compile!
        91   (1.0%)          65   (0.7%)     ActiveRecord::ConnectionAdapters::PostgreSQL::DatabaseStatements#query
        93   (1.1%)          64   (0.7%)     ActionDispatch::Journey::Path::Pattern::AnchoredRegexp#accept
        59   (0.7%)          59   (0.7%)     Mustermann::AST::Translator.dispatch_table
        62   (0.7%)          59   (0.7%)     Rails::BacktraceCleaner#initialize
      2492  (28.5%)          49   (0.6%)     Sprockets::PathUtils#stat_directory
       242   (2.8%)          49   (0.6%)     Gitlab::Instrumentation::RedisBase.add_call_details
        47   (0.5%)          47   (0.5%)     URI::RFC2396_Parser#escape
        46   (0.5%)          46   (0.5%)     #<Class:0x00000001090c2e70>#__setobj__
        44   (0.5%)          44   (0.5%)     Sprockets::Base#normalize_logical_path
```

You can also generate flamegraphs:

```shell
stackprof --d3-flamegraph tmp/profile.dump > flamegraph.html
```

See [the Stackprof documentation](https://github.com/tmm1/stackprof) for more details.

## Speedscope flamegraphs

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.

![Speedscope](img/speedscope_v13_12.png)

Find more information about the views in the [Speedscope docs](https://github.com/jlfwong/speedscope#views).

Find more information about different sampling modes in the [Stackprof docs](https://github.com/tmm1/stackprof#sampling).

This is enabled for all users that can access the performance bar.

## Bullet

Bullet is a Gem that can be used to track down N+1 query problems. Bullet section is
displayed on the [performance-bar](../administration/monitoring/performance/performance_bar.md).

![Bullet](img/bullet_v13_0.png)

Because Bullet adds quite a bit of logging noise the logging is disabled by default.
To enable the logging, set the environment variable `ENABLE_BULLET` to a non-empty value before
starting GitLab. For example:

```shell
ENABLE_BULLET=true bundle exec rails s
```

Bullet logs query problems to both the Rails log as well as the browser
console.

As a follow up to finding `N+1` queries with Bullet, consider writing a [QueryRecoder test](query_recorder.md) to prevent a regression.

## System stats

During or after profiling, you may want to get detailed information about the Ruby virtual machine process,
such as memory consumption, time spent on CPU, or garbage collector statistics. These are easy to produce individually
through various tools, but for convenience, a summary endpoint has been added that exports this data as a JSON payload:

```shell
curl localhost:3000/-/metrics/system | jq
```

Example output:

```json
{
  "version": "ruby 2.7.2p137 (2020-10-01 revision a8323b79eb) [x86_64-linux-gnu]",
  "gc_stat": {
    "count": 118,
    "heap_allocated_pages": 11503,
    "heap_sorted_length": 11503,
    "heap_allocatable_pages": 0,
    "heap_available_slots": 4688580,
    "heap_live_slots": 3451712,
    "heap_free_slots": 1236868,
    "heap_final_slots": 0,
    "heap_marked_slots": 3451450,
    "heap_eden_pages": 11503,
    "heap_tomb_pages": 0,
    "total_allocated_pages": 11503,
    "total_freed_pages": 0,
    "total_allocated_objects": 32679478,
    "total_freed_objects": 29227766,
    "malloc_increase_bytes": 84760,
    "malloc_increase_bytes_limit": 32883343,
    "minor_gc_count": 88,
    "major_gc_count": 30,
    "compact_count": 0,
    "remembered_wb_unprotected_objects": 114228,
    "remembered_wb_unprotected_objects_limit": 228456,
    "old_objects": 3185330,
    "old_objects_limit": 6370660,
    "oldmalloc_increase_bytes": 21838024,
    "oldmalloc_increase_bytes_limit": 119181499
  },
  "memory_rss": 1326501888,
  "memory_uss": 1048563712,
  "memory_pss": 1139554304,
  "time_cputime": 82.885264633,
  "time_realtime": 1610459445.5579069,
  "time_monotonic": 24001.23145713,
  "worker_id": "puma_0"
}
```

NOTE:
This endpoint is only available for Rails web workers. Sidekiq workers can not be inspected this way.

## Settings that impact performance

### Application settings

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.
1. `development` environment can load code lazily once the request is fired which results in first request to always be slow.

To disable those features for profiling/benchmarking set the `RAILS_PROFILE` environment variable to `true` before starting GitLab. For example when using GDK:

- 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
- add `export RAILS_PROFILE=true` to your `env.runit` file
- restart GDK with `gdk restart`

*This environment variable is only applicable for the development mode.*

### GC settings

Ruby's garbage collector (GC) can be tuned via a variety of environment variables that will directly impact application performance.

The following table lists these variables along with their default values.

| Environment variable | Default value |
|--|--|
| `RUBY_GC_HEAP_INIT_SLOTS` | `10000` |
| `RUBY_GC_HEAP_FREE_SLOTS` | `4096` |
| `RUBY_GC_HEAP_FREE_SLOTS_MIN_RATIO` | `0.20` |
| `RUBY_GC_HEAP_FREE_SLOTS_GOAL_RATIO` | `0.40` |
| `RUBY_GC_HEAP_FREE_SLOTS_MAX_RATIO` | `0.65` |
| `RUBY_GC_HEAP_GROWTH_FACTOR` | `1.8` |
| `RUBY_GC_HEAP_GROWTH_MAX_SLOTS` | `0 (disable)` |
| `RUBY_GC_HEAP_OLDOBJECT_LIMIT_FACTOR` | `2.0` |
| `RUBY_GC_MALLOC_LIMIT(_MIN)` | `(16 * 1024 * 1024 /* 16MB */)` |
| `RUBY_GC_MALLOC_LIMIT_MAX` | `(32 * 1024 * 1024 /* 32MB */)` |
| `RUBY_GC_MALLOC_LIMIT_GROWTH_FACTOR` | `1.4` |
| `RUBY_GC_OLDMALLOC_LIMIT(_MIN)` | `(16 * 1024 * 1024 /* 16MB */)` |
| `RUBY_GC_OLDMALLOC_LIMIT_MAX` | `(128 * 1024 * 1024 /* 128MB */)` |
| `RUBY_GC_OLDMALLOC_LIMIT_GROWTH_FACTOR` | `1.2` |

([Source](https://github.com/ruby/ruby/blob/45b29754cfba8435bc4980a87cd0d32c648f8a2e/gc.c#L254-L308))

GitLab may decide to change these settings in order to speed up application performance, lower memory requirements, or both.

You can see how each of these settings affect GC performance, memory use and application start-up time for an idle instance of
GitLab by running the `scripts/perf/gc/collect_gc_stats.rb` script. It will output GC stats and general timing data to standard
out as CSV.