Http Load Profiler

HTTP Load Profiler — Stepped Concurrency Load Test + Inflection Point Analysis

Run stepped concurrency load tests against HTTP services, automatically collect latency percentiles, and detect performance inflection points.

Features

• Dual engine support: Auto-detects wrk (preferred) or ab (Apache Bench); manual override available
• Stepped concurrency: Ramps up through user-defined concurrency levels (default: 1 → 10 → 50 → 100 → 200 → 500)
• Latency percentiles: Collects p50 / p90 / p99 latency at each level
• Inflection point detection: Automatically identifies four types of performance inflection points
• p99 latency accelerating (increase exceeds 2x the previous step's increase)
• Throughput efficiency dropping significantly (RPS per connection drops > 40%)
• Throughput saturated while latency spikes (RPS growth 50%)
• Error rate surging (exceeds 1% and doubles from previous step)
• Optimal concurrency recommendation: Automatically suggests the best concurrency level based on inflection points
• Zero Python dependencies: Pure standard library implementation

Quick Start

# Basic usage — run default stepped load test against target URL
python3 scripts/http_benchmark.py https://example.com/api/health

# Custom concurrency steps and duration per step
python3 scripts/http_benchmark.py https://example.com/api/health -s 5,20,50,100,300 -d 15

# Specify ab as the engine
python3 scripts/http_benchmark.py https://example.com/ -t ab

# JSON-only output (for programmatic parsing)
python3 scripts/http_benchmark.py https://example.com/api/health --json

# Use ab with a specific number of requests per step
python3 scripts/http_benchmark.py https://example.com/ -t ab -n 5000

# Save JSON report to a file
python3 scripts/http_benchmark.py https://example.com/api/health --json > report.json

Parameters

| Parameter | Short | Default | Description | |-----------|-------|---------|-------------| | url | — | (required) | Target URL (http:// or https://) | | --steps | -s | 1,10,50,100,200,500 | Concurrency steps (comma-separated positive integers) | | --duration | -d | 10 | Duration per step in seconds (used directly by wrk; ab estimates request count from this) | | --requests | -n | concurrency×100 | Total requests per step when using ab | | --tool | -t | auto-detect | Specify load testing tool: wrk or ab | | --threads | — | min(concurrency, CPU cores) | Thread count for wrk | | --json | — | false | Output JSON only |

Output Format

Human-readable (default)

Tool: wrk
Target URL: https://example.com/api/health
Concurrency steps: [1, 10, 50, 100, 200, 500]
Duration per step: 10s

----------------------------------------------------------------------------------
  Conc. |        RPS |  Avg(ms) |  P50(ms) |  P90(ms) |  P99(ms) |   Errors | Inflection
----------------------------------------------------------------------------------
     1 |      245.3 |      4.1 |      3.8 |      5.2 |      8.1 |   0.00% |
    10 |     2301.5 |      4.3 |      4.0 |      5.8 |      9.3 |   0.00% |
    50 |     9876.2 |      5.1 |      4.6 |      7.2 |     12.5 |   0.00% |
   100 |    14523.1 |      6.9 |      5.8 |     10.3 |     22.7 |   0.00% |
   200 |    15102.3 |     13.2 |     10.1 |     22.5 |     58.3 |   0.12% |  ◀
   500 |    14890.5 |     33.6 |     28.3 |     55.2 |    132.1 |   1.35% |  ◀
----------------------------------------------------------------------------------

Inflection point analysis:
  ▶ Concurrency 200:
    - p99 latency accelerating: 22.7ms → 58.3ms (increase 35.6ms, previous step increase 10.2ms)
    - Throughput saturated with latency spike: RPS grew only 3.9% while p99 latency grew 156.8%
  ▶ Concurrency 500:
    - Error rate surging: 0.12% → 1.35%

Recommended optimal concurrency: 100

JSON format (--json)

{
  "url": "https://example.com/api/health",
  "tool": "wrk",
  "duration_per_step": 10,
  "steps": [
    {
      "concurrency": 1,
      "rps": 245.3,
      "avg_latency_ms": 4.1,
      "p50_ms": 3.8,
      "p90_ms": 5.2,
      "p99_ms": 8.1,
      "total_requests": 2453,
      "errors": 0
    }
  ],
  "inflection_points": [
    {
      "concurrency": 200,
      "step_index": 4,
      "reasons": ["p99 latency accelerating: ..."]
    }
  ],
  "recommended_concurrency": 100
}

Prerequisites

At least one of wrk or ab must be installed:

# Ubuntu / Debian
sudo apt-get install wrk          # recommended
sudo apt-get install apache2-utils # ab

# macOS
brew install wrk
# ab is pre-installed on macOS

Inflection Point Detection Algorithm

For each concurrency level, the following metrics are compared against the two preceding levels:

1. p99 latency acceleration: Triggers when the current p99 increase exceeds 2x the previous step's increase
2. Throughput efficiency: Triggers when RPS per connection drops > 40% from the previous step
3. Saturation detection: Triggers when RPS growth 50%
4. Error rate: Triggers when rate exceeds 1% and doubles from the previous step

Recommended optimal concurrency: The concurrency level one step before the first inflection point. If no inflection point is found, the level with the highest RPS is selected.

Important Notes

• Load testing generates real traffic against the target service — do not run against production services without authorization
• wrk provides more accurate latency percentiles than ab (wrk uses HdrHistogram)
• ab does not support a duration parameter; the script approximates timing via total request count
• A minimum of 10 seconds per step is recommended for stable results

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: zebbern
• Source: zebbern/claude-code-guide
• License: MIT

Install and usage instructions live in the source repository linked above.