Partner Integration Onboarding Simulator

A REST API platform that validates publisher API integrations against Google Ad Manager configuration standards - simulating real-world Product Solutions Engineer workflows at Google.

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Overview

When a publisher partner onboards onto Google Ad Manager, a PSE validates their technical integration setup, identifies misconfigurations, and provides actionable fix recommendations. This project simulates that exact workflow as a full-stack application.

Partner submits integration details
        ↓
System validates their API configuration
        ↓
Pandas generates a health report with scores
        ↓
Dashboard surfaces issues and recommended fixes

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Features

• Partner Registration — onboard publisher partners with their API and ad platform details
• Automated Validation Engine — runs 4 checks against partner API integrations
  • Endpoint Reachability
  • Response Latency
  • HTTPS Security
  • Authentication Method Validity
• Pandas Health Reports — aggregates validation results into a scored health report
• Real-time Dashboard — Streamlit UI for visualizing integration health across partners
• JWT Authentication — secured endpoints
• Auto-generated API Docs — Swagger UI at /docs

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Tech Stack

Layer	Technology
Backend	Python, FastAPI
Database	OracleDB, SQLAlchemy
Data Processing	Pandas
Frontend	Streamlit
Authentication	JWT
Validation	Pydantic
HTTP Client	httpx (async)
Deployment	GCP Cloud Run

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Project Structure

partner-onboarding-simulator/
│
├── main.py                  # FastAPI app entry point
├── requirements.txt         # Dependencies
├── .env.example             # Environment variable template
│
├── database/
│   ├── connection.py        # OracleDB connection + session
│   └── models.py            # SQLAlchemy table models
│
├── schemas/
│   └── partner.py           # Pydantic validation schemas
│
├── services/
│   ├── validator.py         # Async validation engine
│   └── report_generator.py  # Pandas health report generator
│
└── dashboard/
    └── app.py               # Streamlit dashboard

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API Endpoints

Method	Endpoint	Description
GET	/	Health check
GET	/status	Server uptime and version
GET	/info	Project information
POST	/partners	Register new partner
GET	/partners	List all partners
GET	/partners/{id}	Get partner by ID
POST	/validate/{id}	Run validation + generate health report
POST	/auth/register	Register new user
POST	/auth/login	Login and get JWT token

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Validation Checks

Check	Severity	What it Tests
Endpoint Reachability	Critical	Is the partner API accessible?
Response Latency	Warning	Does it respond under 2000ms?
HTTPS Security	Critical	Is the connection encrypted?
Auth Method Validity	Critical	Is the auth method valid for the ad platform?

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Sample Health Report Response

{
  "health_score": 75.0,
  "status": "Not bad",
  "total_checks": 4,
  "passed_checks": 3,
  "failed_checks": 1,
  "critical_issues": [
    {
      "check_type": "HTTPS Security",
      "message": "Endpoint is not using HTTPS",
      "fix": "Use HTTPS instead of HTTP"
    }
  ],
  "warnings": []
}

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Local Setup

Prerequisites

• Python 3.10+
• Oracle XE (local) or any Oracle DB instance
• Oracle Instant Client (for thick mode)

Installation

# Clone the repository
git clone https://github.com/yourusername/partner-onboarding-simulator.git
cd partner-onboarding-simulator

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Environment Variables

Create a .env file in the root directory:

ORACLE_USER=your_username
ORACLE_PASSWORD=your_password
ORACLE_HOST=localhost
ORACLE_PORT=1521
ORACLE_SERVICE=XE

Run the Application

# Terminal 1 — Start FastAPI backend
uvicorn main:app --reload

# Terminal 2 — Start Streamlit dashboard
streamlit run dashboard/app.py

• API: http://localhost:8000
• Swagger Docs: http://localhost:8000/docs
• Dashboard: http://localhost:8501

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Requirements

fastapi
uvicorn
sqlalchemy
oracledb
pandas
pydantic
python-jose[cryptography]
passlib[bcrypt]
python-dotenv
streamlit
requests
httpx

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PSE Relevance

This project directly mirrors Product Solutions Engineer responsibilities at Google:

PSE Responsibility	How This Project Covers It
Delivering solutions to partner problems	Automated validation engine flags partner issues
Troubleshooting implementation issues	Health reports with root cause and fix recommendations
Providing technical guidance	Actionable fix suggestions per failed check
Ensuring client satisfaction	Health scoring system with pass/fail per check
Advocating for product features	Ad platform-specific validation rules

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Author

Sathwik K

• GitHub: Sathwik464
• LinkedIn: linkedin.com/in/sathwik46
• Blog: https://sathwikk.hashnode.dev/