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Rate Analytics

Rate Analytics provides insights into traffic distribution patterns and connection rates over time, helping you identify usage patterns, potential abuse, and optimize rate limiting configurations.

Rate Distribution Analysis

Percentile-Based Rate Metrics

Rate analytics displays traffic patterns across different percentile bands:

  • 50th Percentile (Median): Typical traffic rates experienced by half of your users
  • 75th Percentile: Higher traffic rates affecting a quarter of requests
  • 99th Percentile: Peak rates experienced by the busiest 1% of traffic
  • 99.9th Percentile: Extreme peak rates for the highest traffic periods

Why percentiles matter: - Percentiles reveal traffic distribution patterns beyond simple averages - High percentile values indicate burst traffic or potential abuse - Different percentiles help set appropriate rate limiting thresholds

Rate Pattern Recognition

Analyzing rate distributions helps identify:

  • Normal traffic patterns vs. unusual spikes
  • Gradual load increases vs. sudden burst events
  • Legitimate high-usage vs. potential abuse patterns

Traffic Source Analysis

Top IP Hit Patterns

Time series showing request patterns from individual IP addresses:

  • High-frequency requesters that may need rate limiting
  • Legitimate high-volume users requiring special consideration
  • Potential abuse sources generating excessive requests

Analysis insights:

  • Consistent high rates may indicate API users or crawlers
  • Sudden spikes could suggest abuse or automated attacks
  • Geographic correlation with legitimate business patterns

ASN (Autonomous System Number) Patterns

Traffic analysis by network provider reveals:

  • Network-level traffic patterns from ISPs and hosting providers
  • Data center traffic that may indicate bot activity
  • Residential vs. commercial traffic characteristics

Strategic applications: - Identify hosting providers commonly used for abuse - Recognize legitimate traffic from major ISPs - Adjust rate limiting based on network characteristics

Connection Rate Analysis

Tracking connection patterns over time shows:

  • New connection establishment rates
  • Connection reuse efficiency
  • Keep-alive optimization effectiveness

Rate Limiting Optimization

Threshold Setting

Use rate analytics to establish appropriate limits:

  • Baseline normal rates from percentile analysis
  • Burst allowances for legitimate high-activity periods
  • Progressive limiting strategies for different severity levels

Abuse Detection

Identify patterns requiring intervention:

  • Sustained high rates from individual sources
  • Coordinated activity across multiple IPs or ASNs
  • Unusual traffic patterns that deviate from historical norms

Legitimate User Protection

Ensure rate limits don't impact legitimate users:

  • User behavior analysis to understand normal usage patterns
  • Geographic considerations for users in different regions
  • Time-based patterns that account for business hours and usage cycles

Performance Impact Analysis

Rate vs. Performance Correlation

Understand how traffic rates affect system performance:

  • Response time degradation under high-rate conditions
  • Cache effectiveness during traffic bursts
  • Infrastructure capacity limits revealed through rate analysis

Capacity Planning

Use rate data for infrastructure planning:

  • Peak rate capacity requirements for infrastructure scaling
  • Burst handling capabilities needed for traffic spikes
  • Geographic distribution of rate limiting infrastructure

Advanced Rate Analysis

Pattern Classification

Differentiate between traffic types:

  • Human browsing patterns with natural variability
  • Bot traffic patterns with mechanical consistency
  • API usage patterns with predictable request frequencies

Seasonal and Event Analysis

Understand rate patterns in context:

  • Seasonal variations in traffic intensity
  • Event-driven spikes from marketing campaigns or news events
  • Time zone patterns affecting global traffic distribution

Predictive Analysis

Use historical rate data for forecasting:

  • Growth trend projection for capacity planning
  • Abuse pattern prediction for proactive security measures
  • Performance optimization based on predicted rate patterns

Rate Limiting Strategy

Dynamic Rate Limiting

Adjust limits based on current conditions:

  • Traffic-aware limits that scale with overall site activity
  • Source reputation influencing individual rate limits
  • Performance-based adjustment when system load increases

Graduated Response

Implement progressive rate limiting:

  • Warning thresholds for unusual but not abusive activity
  • Soft limits with delayed responses before hard blocking
  • Escalating restrictions for persistent high-rate sources

Rate analytics provide the data foundation for effective rate limiting strategies that protect your infrastructure while maintaining excellent user experience for legitimate traffic.