Install Autotuner for GC recommendations

Gemfile

@@ -48,6 +48,7 @@ gem "yabeda-puma-plugin"
 gem "yabeda-rails"
 gem "webrick" # required for yabeda-prometheus metrics server
 gem "prometheus-client-mmap", "~> 1.1"
+gem "autotuner"
 
 # AI
 gem "ruby_llm", git: "https://github.com/crmne/ruby_llm.git"

Gemfile.lock

@@ -170,6 +170,7 @@ GEM
     anyway_config (2.7.2)
       ruby-next-core (~> 1.0)
     ast (2.4.3)
+    autotuner (1.0.2)
     aws-eventstream (1.4.0)
     aws-partitions (1.1170.0)
     aws-sdk-core (3.233.0)
@@ -606,6 +607,7 @@ PLATFORMS
 DEPENDENCIES
   activerecord-tenanted
   activeresource
+  autotuner
   aws-sdk-s3
   bcrypt (~> 3.1.7)
   bootsnap

config.ru

@@ -2,5 +2,7 @@
 
 require_relative 'config/environment'
 
+use Autotuner::RackPlugin
+
 run Rails.application
 Rails.application.load_server

config/initializers/autotuner.rb

@@ -0,0 +1,24 @@
+# Enable autotuner. Alternatively, call Autotuner.sample_ratio= with a value
+# between 0 and 1.0 to sample on a portion of instances.
+Autotuner.enabled = true
+
+# This callback is called whenever a suggestion is provided by this gem.
+# You can output this report to your logging pipeline, stdout, a file,
+# or somewhere else!
+Autotuner.reporter = proc do |report|
+  Rails.logger.info "GCAUTOTUNE: #{report}"
+  Sentry.capture_message "Autotuner suggestion", level: :info, extra: { report: report.to_s }
+end
+
+# # This (optional) callback is called to provide metrics that can give you
+# # insights about the performance of your app. It's recommended to send this
+# # data to your observability service (e.g. Datadog, Prometheus, New Relic, etc).
+# # Use a metric type that would allow you to calculate the average and percentiles.
+# # On Datadog this would be the distribution type. On Prometheus this would be
+# # the histogram type.
+# Autotuner.metrics_reporter = proc do |metrics|
+#   # stats is a hash of metric name (string) to integer value.
+#   metrics.each do |key, val|
+#     StatsD.gauge(key, val)
+#   end
+# end