API Metrics Scalability

April 10, 2026#ontic#corefwk#scalability#api

Key API metrics to track for scalability planning, infrastructure sizing, and reliability decisions.

Key API metrics to track for scalability planning, infrastructure sizing, and reliability decisions.

API Metrics for Scalability Planning

Performance Metrics

  • Your core latency and throughput measurements
Metric Description Why It Matters
Average RPS Average requests per second over a time period Baseline load understanding and initial infrastructure sizing
Peak RPS Maximum requests per second observed Critical for capacity planning and determining infrastructure ceiling needs
P50 Latency 50th percentile response time, median Typical user experience, half of requests are faster than this
P90 Latency 90th percentile response time Representative of most users, 90 percent of requests are faster than this
P95 Latency 95th percentile response time Catches outliers that affect user satisfaction
P99 Latency 99th percentile response time Worst-case tail latency and critical for SLA definitions

Volume and Growth Metrics

  • Request counts and trends for capacity planning
Metric Description Why It Matters
Total Request Count Total number of requests over a period, for example last 3 months Overall scale understanding and baseline for capacity planning
Monthly Growth Rate Month-over-month percentage increase in requests Projection of future capacity needs and scaling timeline
Requests per Provider Distribution of requests across different research providers Identifies high-traffic versus low-traffic providers and helps prioritize optimization
Daily/Weekly Patterns Request volume trends by time of day or day of week Useful for autoscaling configuration and identifying peak usage windows

Reliability Metrics

  • Error rates and availability
Metric Description Why It Matters
Error Rate Percentage of requests returning errors like 4xx or 5xx Service health indicator and SLA impact
Success Rate Percentage of successful requests, inverse of error rate Overall reliability metric and target for SLA definitions
Timeout Rate Percentage of requests exceeding timeout threshold Indicates performance issues or resource constraints
Availability Uptime percentage over a period Core SLA metric and microservice dependency input

Resource Utilization Metrics

  • Bandwidth, connections, and sizing data
Metric Description Why It Matters
Average Response Size Mean size of API responses in KB or MB Bandwidth planning and memory allocation for response buffers
Average Request Size Mean size of API requests in KB or MB Network capacity planning and request buffer sizing
Peak Concurrent Connections Maximum simultaneous active connections Connection pool sizing and load balancer configuration
Data Transfer Volume Total bandwidth consumed, ingress plus egress Network cost planning and bandwidth provisioning

Operational Metrics

  • Cache, dependencies, and usage patterns
Metric Description Why It Matters
Cache Hit Rate Percentage of requests served from cache Reduces backend load and improves latency
External API Call Rate Frequency of calls to third-party or downstream services Helps understand dependencies and manage rate limits
Usage by Endpoint Request distribution across API operations Identifies hot paths for optimization and refactoring
Usage by Client/Tenant Request distribution by consumer Useful for multi-tenancy planning and identifying noisy neighbors

High Priority

  • Peak RPS
  • P99 Latency
  • Error Rate
  • Total Request Count
  • Monthly Growth Rate

Medium Priority

  • P90/P95 Latency
  • Requests per Provider
  • Peak Concurrent Connections
  • Usage by Endpoint

Nice to Have

  • Cache Hit Rate
  • Daily/Weekly Patterns
  • Response and Request Sizes