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Getting Started

Get up and running with the Anosys Platform in minutes. This guide walks you through creating your account, setting up your first pixel, and sending your first data.

Step 1 — Create Your Account

Sign up at console.anosys.ai and create your workspace. No credit card is required for the 7-day free trial.

Step 2 — Create a Pixel

A pixel is your data ingestion endpoint. Each pixel has a unique path and API key that you use to send data to Anosys.

  1. In the Anosys Console, navigate to Pixels.
  2. Click Create Pixel and choose your integration type:
Pixel Type Use Case
Agentic AI OpenAI agents, Claude Code, and other AI workflows
OpenTelemetry Any OTEL-instrumented service
API Backend services, scripts, and custom integrations
Web Website tracking via JavaScript or image pixels
  1. Copy your API key and ingestion path — you'll need them in the next step.

Step 3 — Send Your First Data

Choose the integration that fits your workflow:

Quick Start — REST API

The fastest way to verify your setup. Send a simple HTTP request with custom parameters:

Python:

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import requests

# Your unique Anosys ingestion path
url = "https://api.anosys.ai/ingestion/YOUR_UNIQUE_PATH"

# Custom parameters — s for strings, n for numbers
params = {
    "s1": "hello_world",
    "n1": 42.0
}

try:
    response = requests.get(url, params=params, timeout=10)
    response.raise_for_status()
    print("Success:", response.text)
except requests.exceptions.RequestException as e:
    print("Error:", e)

cURL:

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curl -G "https://api.anosys.ai/ingestion/YOUR_UNIQUE_PATH" \
  --data-urlencode "s1=hello_world" \
  --data-urlencode "n1=42.0"

If you receive a success response, your data is flowing and will appear in the Anosys dashboards within seconds.

AI Agent Workflows

For AI-specific observability with richer tracing:

Other Integrations

For OpenTelemetry, JavaScript, image pixels, decorators, and bulk ingestion, see the full Data Ingestion Options.

Step 4 — Explore Your Data

Once data is flowing, head to the Anosys Console to:

  • View traces — drill into individual requests and agent sessions
  • Build dashboards — create charts and tables for any ingested metric
  • Set up alerts — get notified in Slack or email when anomalies are detected
  • Run analysis — use built-in ML models for anomaly detection and root cause analysis

What's Next