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Latency Profiler

Discover how latency profilers measure and analyze AI pipeline performance, enhance interoperability, and boost productivity across healthcare, e-commerce, and more.

About Latency Profiler

Profile the latency of different components in an AI application.

Categories

AI Observability
Testing & Debugging

Tags

Observability
Testing

Try It Out

Features:

  • Test API endpoint latency with configurable parameters
  • Support for all HTTP methods and custom headers/body
  • Concurrent request execution
  • Configurable request intervals
  • Real-time progress tracking
  • Detailed latency statistics (min, max, mean, percentiles)
  • Success rate monitoring
  • Visual latency distribution chart
  • JSON validation for headers and body

Latency Profiler

The Latency Profiler is a powerful tool for testing and analyzing API endpoint latency. It helps developers understand the performance characteristics of their APIs by providing detailed statistics and visualizations.

Features

  • Test API endpoint latency with configurable parameters
  • Support for all HTTP methods (GET, POST, PUT, DELETE, HEAD, OPTIONS)
  • Custom headers and request body support
  • Concurrent request execution
  • Configurable request intervals
  • Real-time progress tracking
  • Detailed latency statistics:
    • Minimum latency
    • Maximum latency
    • Mean latency
    • Median latency
    • 95th percentile
    • 99th percentile
  • Success rate monitoring
  • Visual latency distribution chart
  • JSON validation for headers and body

Usage

  1. Enter the API endpoint URL you want to test
  2. Select the HTTP method (default: GET)
  3. Add any required headers in JSON format (optional)
  4. Add request body in JSON format (optional, for POST/PUT methods)
  5. Configure test parameters:
    • Number of requests (1-10000)
    • Concurrency level (1-100)
    • Interval between batches in milliseconds (0-10000)
  6. Click "Run Test" to start the latency profiling
  7. View real-time progress and results:
    • Latency statistics
    • Success rate
    • Visual distribution chart

Example

Testing a REST API endpoint:

// Headers
{
  "Content-Type": "application/json",
  "Authorization": "Bearer your-token"
}

// Body (for POST/PUT)
{
  "key": "value",
  "data": {
    "field1": "test",
    "field2": 123
  }
}

Use Cases

  • API performance testing
  • Load testing
  • Latency monitoring
  • Service level agreement (SLA) verification
  • Performance optimization
  • Network latency analysis
  • API reliability testing

Tips

  1. Start with a small number of requests to verify the endpoint works
  2. Increase concurrency gradually to find optimal performance
  3. Use intervals to prevent overwhelming the server
  4. Monitor success rate alongside latency metrics
  5. Pay attention to 95th and 99th percentiles for outliers
  6. Compare results across different environments or configurations

Notes

  • Maximum file size: None (client-side only)
  • Rate limiting: Depends on the target API
  • Supported protocols: HTTP/HTTPS
  • Data privacy: All testing is done client-side
  • Browser limitations may apply for certain endpoints (CORS)