FAQ

How we collect metrics

Scout is engineered to monitor the performance of mission-critical production applications. Here’s a short overview of how this happens:

Data Retention

Scout stores 30 days of metrics and seven days of transaction traces.

Performance Overhead

Our agent is designed to run in production environments and is extensively benchmarked to ensure it performs on high-traffic applications.

Our most recent benchmarks (lower is better):

overhead

We’ve open-sourced our benchmarks so you can test on our own. If your results differ, reach out to us at support@scoutapm.com.

Call Aggregation

During a transaction, the Scout agent records each database call, each external HTTP request, each rendering of a view, and several other instrumented libraries. While each individual pieces of this overall trace has a tiny memory footprint, large transactions can sometimes build up thousands and thousands of them.

To limit our agent’s memory usage, we stop recording the details of every instrument after a relatively high limit. Detailed metrics and backtraces are collected for all calls up to the limit and aggregated metrics are collected for calls over the limit.

Security

We take the security of your code metrics extremely seriously. Keeping your data secure is fundamental to our business. Scout is nearing a decade storing critical metrics and those same fundamentals are applied here:

Information sent to our servers

The following data is sent to our servers from the agent:

Git Integration

Scout only needs read-only access to your repository, but unfortunately, Github doesn’t currently allow this - they only offer read-write permissions through their OAuth API.

We have asked Github to offer read-only permissions, and they’ve said that the feature coming soon. In the mean time, we’re limited to the permissions structure Github offers. Our current Git security practices:

All that said, we suggest the following:

Workaround for read-only Github Access

With a few extra steps, you can grant Scout read-only access. Here’s how:

AutoInstruments

What files within a Rails app does AutoInstruments attempt to instrument?

AutoInstruments applies instrumentation to file names that match RAILS_ROOT/app/controllers/*_controller.rb.

Why is Autoinstruments limited to controllers?

Adding instrumentation induces a small amount of overhead to each instrumented code expression. If we added instrumentation to every line of code within a Rails app, the overhead would be too significant on a production deployment. By limiting Autoinstruments to controllers, we’re striking a balance between visibility and overhead.

What are some examples of code expressions that are instrumented?

Below are some examples of how autoinstrumented spans appear in traces.

# RAILS_ROOT/app/controllers/users_controller.rb
# This file will be instrumented as its name matches `app/controllers/*_controller.rb`.
class UsersController < ApplicationController

  def index
    fetch_users # <- Appears as `fetch_users` in traces.
    if rss? || xml? # <- This is broken into 2 spans within traces: (`rss?` and `xml?`)
      formatter = proc do |row| # <- The entire block will appear under "proc do |row|..."
        row.to_json
      end
      return render_xml # <- Appears as `return render_xml`
    end
  end

  private

  def fetch_users
    return unless authorized? # <- Appears as `return unless authorized?` in traces.
    source ||= params[:source].present? # <- Appears as `params[:source].present?`
    @users = User.all(limit: 10) # <- ActiveRecord queries are instrumented w/our AR instrumentation
  end

Is every method call to an autoinstrumented code expression recorded?

Prior to storing a span, our agent checks if the span’s total execution time is at least 5 ms. If the time spent is under this threshold, the span is thrown away and the time is allocated to the parent span. This decreases the amount of noise that appears in traces (spans consuming < 5ms are unlikely optimization candidates) and decreases the memory usage of the agent. Only autoinstrumented spans are thrown away - spans that are explicity instrumented are retained.

What do charts look like when autoinstruments is enabled?

When autoinstruments is enabled, a large portion of controller time will shift to autoinstruments:

autoinstruments before after

This is expected.

How much overhead does autoinstruments add?

When When autoinstruments is enabled, you can estimate the additional overhead by inspecting your overview chart. Measure the mean controller time before the deploy then controller + autoinstruments after. The difference between these numbers is the additional overhead.

How can the overhead of autoinstruments be reduced?

By default, the Scout agent adds autoinstruments to every controller in your Rails app. You can exclude controllers from instrumentation, which will reduce overhead via the autoinstruments_ignore option. To determine which controllers should be ignored:

  1. Ensure you are running version 2.6.1 of scout_apm or later.
  2. Adjust the Scout agent log level to DEBUG.
  3. Restart your app.
  4. After about 10 minutes run the following command inside your RAILS_ROOT:
grep -A20 "AutoInstrument Significant Layer Histograms" log/scout_apm.log

For each controller file, this will display the total number of spans recorded and the ratio of significant to total spans. Look for controllers that have a large total and a small percentage of significant spans. In the output below, it makes sense to ignore application_controller as only 10% of those spans are significant:

[09/23/19 07:27:52 -0600 Dereks-MacBook-Pro.local (87116)] DEBUG : AutoInstrument Significant Layer Histograms: {"/Users/dlite/projects/scout/apm/app/controllers/application_controller.rb"=>
  {:total=>545, :significant=>0.1},
 "/Users/dlite/projects/scout/apm/app/controllers/apps_controller.rb"=>
  {:total=>25, :significant=>0.56},
 "/Users/dlite/projects/scout/apm/app/controllers/checkin_controller.rb"=>
  {:total=>31, :significant=>0.39},
 "/Users/dlite/projects/scout/apm/app/controllers/status_pages_controller.rb"=>
  {:total=>2, :significant=>0.5},
 "/Users/dlite/projects/scout/apm/app/controllers/errors_controller.rb"=>
  {:total=>2, :significant=>1.0},
 "/Users/dlite/projects/scout/apm/app/controllers/insights_controller.rb"=>
  {:total=>2, :significant=>1.0}}

Add the following to the common: &defaults section of the config/scout_apm.yml file to avoid instrumenting application_controller.rb:

common: &defaults
  auto_instruments_ignore: ['application_controller']

ScoutProf

ScoutProf has been deprecate and succeeded by Auto Instruments. ScoutProf is no longer supported.

Billing

Free Trial

We offer a no risk, fully featured, free trial. Enter a credit or debit card anytime to continue using Scout APM after the end of your trial.

Billing Date

Your first bill is 30 days after your signup date.

Subscription Style

We offer both monthly and anunal subscriptions with varying transaction levels and capabilities. Contact support@scoutapm.com for pricing options.

Replacing New Relic

Scout is an attractive alternative to New Relic for modern dev teams. We provide a laser-focus on getting to slow custom application code fast vs. wide breadth as debugging slow custom application code is typically the most time-intensive performance optimization work.

In many cases, Scout is able to replace New Relic as-is. However, there are cases where your app has specific needs we currently don’t provide. Don’t fret - here’s some of the more common scenarios and our suggestions for building a monitoring stack you’ll love:

Our Monitoring Stack

Curious about what a company that lives-and-breathes monitoring (us!) uses to monitor our apps? We shared our complete monitoring stack on our blog.

Talk to us about your monitoring stack

Don’t hesitate to email us if you need to talk through your monitoring stack. Monitoring is something we know and love.