🚀 AutoFlow – Workflow Automation Platform

AutoFlow is a lightweight workflow automation platform that allows users to create, manage, and execute chained automation workflows such as:

HTTP → AI → Custom Steps

Inspired by tools like Zapier and n8n, AutoFlow focuses on simplicity, extensibility, and operational clarity.

Beyond its functional scope, the project is designed with a strong emphasis on production readiness, failure handling, and supportability.

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✨ Core Features

• User authentication and authorization (JWT)
• Workflow creation and management
• Multiple step types within a workflow:
  • HTTP requests
  • AI summarization
  • Custom processing steps
• Dynamic context passing between workflow steps
• Workflow execution with result inspection
• Dashboard-style user interface

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🧠 Production & Support Perspective

This project is built to simulate real-world application support and production operations:

• External dependency handling (HTTP services, AI integrations)
• Graceful failure handling for individual workflow steps
• Clear execution flow and error visibility per step
• Structured logging for troubleshooting failed executions
• Secure and isolated execution of user-defined workflows
• Environment-based configuration for development and production setups

The system is designed to allow operators to quickly identify where and why a workflow execution failed, reflecting realistic production incident scenarios.

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🧱 Technical Stack

Backend

• Java 17
• Spring Boot
• Spring Security + JWT
• JPA / Hibernate
• PostgreSQL (H2 for local development)
• Docker-ready architecture

Frontend

• React
• TypeScript
• Vite
• Axios

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⚙️ Architecture Overview

Client (React)
→ Spring Boot REST API
→ Workflow Execution Engine
→ PostgreSQL

This architecture enables clear separation of concerns and easier operational support when failures occur during workflow execution.

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🖥️ Screenshots

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🔧 Setup

Backend

cd autoflow-api
mvn spring-boot:run

Backend runs on:
http://localhost:8080

Frontend

cd autoflow-ui
npm install
npm run dev

Frontend runs on:
http://localhost:5173

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🔑 Example Workflow

1. HTTP step – fetch external content
2. AI step – summarize fetched data
3. Execute workflow
4. Inspect execution results and logs

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📌 Roadmap

• Drag & drop workflow builder
• Additional step types (email, webhook, database)
• Step editing and reordering
• Execution history and monitoring
• Docker Compose support

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👤 Author

Mustafa Kadak
Application / Production Support Engineer (Entry-level)