Performance Monitoring

ActiveRabbit's performance monitoring helps you identify bottlenecks, slow queries, and optimize your Rails application's response times.

Enabling Performance Monitoring

# config/initializers/activerabbit.rb
ActiveRabbit.configure do |config|
  config.api_key = ENV['ACTIVERABBIT_API_KEY']
  
  # Enable performance monitoring
  config.performance_monitoring = true
  
  # Sample rate for performance data (0.0 to 1.0)
  # Start with 0.1 (10%) and adjust based on traffic
  config.performance_sample_rate = 0.1
end

Automatic Instrumentation

When enabled, ActiveRabbit automatically tracks:

• Controller actions - Total request time and breakdown
• Database queries - Query time, count, and N+1 detection
• View rendering - Template and partial render times
• External HTTP calls - API response times
• Cache operations - Redis/Memcached hit rates and latency

Transaction Tracking

Each HTTP request is tracked as a "transaction" with timing breakdown:

# Transactions are automatically created for each request
# Example breakdown:
# 
# GET /orders/123
# Total: 245ms
# ├─ Controller: 15ms
# ├─ Database: 180ms
# │  ├─ SELECT orders... 25ms
# │  ├─ SELECT line_items... 45ms (N+1 detected!)
# │  └─ SELECT products... 110ms
# ├─ View: 35ms
# └─ Redis: 15ms

Custom Spans

Track custom operations within your code:

# Manual span creation
def process_order(order)
  ActiveRabbit.with_span('process_order') do |span|
    span.set_tag('order_id', order.id)
    
    # Nested spans
    ActiveRabbit.with_span('validate_inventory') do
      check_inventory(order.line_items)
    end
    
    ActiveRabbit.with_span('charge_payment') do
      charge_customer(order)
    end
    
    ActiveRabbit.with_span('send_confirmation') do
      OrderMailer.confirmation(order).deliver_later
    end
  end
end

Slow Query Detection

ActiveRabbit.configure do |config|
  # Threshold in milliseconds
  config.slow_query_threshold = 100
  
  # Get alerted for queries over threshold
  # These appear in the dashboard with full query and explain plan
end

N+1 Query Detection

ActiveRabbit.configure do |config|
  # Enable N+1 detection
  config.detect_n_plus_one = true
  
  # Minimum duplicate queries to trigger detection
  config.n_plus_one_threshold = 3
end

# When N+1 is detected, ActiveRabbit captures:
# - The repeated query pattern
# - Stack trace showing where it originates
# - Suggested fix (e.g., add includes/preload)

Web Vitals

For frontend performance, add the JavaScript snippet to track Core Web Vitals:

<!-- Add to your layout head -->
<script src="https://cdn.activerabbit.ai/vitals.js" 
        data-api-key="<%= ENV['ACTIVERABBIT_API_KEY'] %>"
        async></script>

This tracks:

• LCP - Largest Contentful Paint
• FID - First Input Delay
• CLS - Cumulative Layout Shift
• TTFB - Time to First Byte

Apdex Score

ActiveRabbit calculates an Apdex score for your application:

ActiveRabbit.configure do |config|
  # Satisfied threshold (requests faster than this are "satisfied")
  config.apdex_satisfied = 500  # 500ms
  
  # Tolerating threshold (requests between satisfied and this are "tolerating")
  config.apdex_tolerating = 2000  # 2000ms
  
  # Requests slower than tolerating threshold are "frustrated"
end

# Apdex = (Satisfied + Tolerating/2) / Total
# Score ranges from 0 (worst) to 1 (best)

Performance Alerts

Configure alerts for performance degradation:

# In the ActiveRabbit dashboard, create alerts for:
# 
# - P95 latency > 1000ms
# - Apdex score < 0.85
# - Error rate > 1%
# - N+1 queries detected
# - Slow query threshold exceeded

Background Jobs

# Job performance is automatically tracked
class HeavyProcessingJob < ApplicationJob
  def perform(data)
    # Job duration and memory usage tracked automatically
    process_data(data)
  end
end

# You can add custom metrics
class ImportJob < ApplicationJob
  def perform(file_path)
    ActiveRabbit.with_span('import_job') do |span|
      records = import_records(file_path)
      span.set_data('records_imported', records.count)
    end
  end
end

Database Query Analysis

# ActiveRabbit captures and analyzes:
# 
# - Query duration
# - Rows examined vs returned
# - Index usage (EXPLAIN output)
# - Query frequency and patterns
# 
# For MySQL/PostgreSQL, it can suggest indexes:
# 
# Suggested index for frequent slow query:
# CREATE INDEX index_orders_on_user_id_and_status 
#   ON orders(user_id, status);

Memory Profiling

ActiveRabbit.configure do |config|
  # Track object allocations
  config.track_allocations = true
  
  # Memory growth threshold (MB) to flag
  config.memory_growth_threshold = 50
end

# Dashboard shows:
# - Memory usage over time
# - Object allocation hotspots
# - Potential memory leaks