httpster

🚀 HTTPster

🎯 About

HTTPster is like your Swiss Army knife for HTTP load testing - but cooler! Born out of frustration with traditional tools like ab and wrk that give you about as much detail as a weather forecast from a magic 8-ball.

🌟 Key Features

• Multi-threaded request execution
• Detailed timing metrics for each request
• CSV output for data nerds (we know you love spreadsheets!)
• Support for all HTTP methods (because POST isn't the only cool kid)
• Custom headers and body support

🏃‍♂️ Quick Start

# Clone and build your very own HTTPster
git clone https://github.com/axent-pl/httpster
cd httpster
make build

# Let's make some noise!
cat examples/example.json | bin/httpster -duration=60s -threads=2 1> data.csv 2> error.log

# If lost, just ask for help
bin/httpster --help

📝 Input stdin

Feed HTTPster with a JSON array of request definitions to the stdout. Here's a simple example:

[
    {
        "id": "my-awesome-request",
        "url": "http://api.example.com/unicorns",
        "method": "POST",
        "headers": {
            "Content-Type": "application/json",
            "X-Magic-Header": "🌈"
        },
        "body": "{\"wants\": \"rainbow\"}"
    }
]

Schema:

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "array",
  "items": [
    {
      "type": "object",
      "properties": {
        "id": {
          "type": "string"
        },
        "url": {
          "type": "string"
        },
        "method": {
          "type": "string"
        },
        "headers": {
          "type": "object"
        },
        "body": {
          "type": "string"
        }
      },
      "required": [
        "url",
        "method"
      ]
    }
  ]
}

📊 Output stdout and stderr

HTTPster spits out CSV data to stdout that looks like this:

Example output:

ID,StartTime,Duration_ns,ConnDuration_ns,DialDuration_ns,DNSDuration_ns,RequestDuration_ns,Status,StatusCode,Error
GET /,2025-05-08T10:48:04+02:00,243971334,123593959,119537375,2674750,1451209,200 OK,200,
GET /,2025-05-08T10:48:04+02:00,256501709,130761917,126730792,2680500,188042,200 OK,200,

Any errors goes to stderr

🔬 Analysis

Want to make sense of all those numbers? Here's a Python snippet to get you started:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# Load your data
df = pd.read_csv("data.csv")
df['StartTime'] = pd.to_datetime(df['StartTime'])

# Create a fancy plot
sns.kdeplot(data=df, x='Duration_ns',hue="ID")
plt.title('Request Duration Distribution')
plt.show()