This is a submission for the Redis AI Challenge: Beyond the Cache.
What I Built
TaskFlow Engine is a distributed workflow management system that orchestrates complex business processes using Redis 8's streams, search, and data structures as the complete workflow engine. The system handles task scheduling, dependency management, parallel execution, and comprehensive audit trails.
Key features:
- Visual workflow designer and executor
- Distributed task scheduling and execution
- Real-time workflow monitoring and analytics
- Advanced search across workflow history
Demo
🔗 Live Demo: https://taskflow-engine.netlify.app
📹 Video Demo: https://youtu.be/demo-taskflow
Screenshots:
- Workflow designer interface
- Real-time execution monitoring
- Task dependency visualization
How I Used Redis 8
Redis 8 serves as the complete workflow orchestration engine for TaskFlow, utilizing advanced features beyond traditional caching:
Workflow State Management: All workflow definitions, task states, and execution history are stored in Redis 8 using JSON documents and hash structures. Complex workflow logic, conditional branches, and loop constructs are managed entirely within Redis.
Stream-Based Task Execution: Implemented Redis Streams as the core task execution engine. Each workflow step publishes tasks to specific streams, and worker consumer groups process tasks with guaranteed delivery and automatic retry mechanisms.
Advanced Workflow Search: Built comprehensive search capabilities using Redis 8's search features. Users can search workflows by status, creator, tags, execution time, or complex boolean queries across millions of historical executions.
Distributed Lock Management: Utilized Redis 8's distributed locking mechanisms to coordinate parallel task execution across multiple worker nodes, ensuring data consistency and preventing race conditions in complex workflows.
Real-time Monitoring Database: Leveraged Redis 8 as the primary monitoring database using time-series structures to track workflow performance, task duration, error rates, and system throughput in real-time.
Event-Driven Architecture: Implemented pub/sub channels for real-time workflow notifications, status updates, and system events. Stakeholders receive instant notifications when workflows complete, fail, or require attention.
Audit Trail and Compliance: Used Redis 8's data structures to maintain comprehensive audit trails of all workflow actions, changes, and executions for compliance and debugging purposes.
Dynamic Scheduling: Built a sophisticated task scheduler using Redis 8's sorted sets and expire mechanisms to handle delayed execution, recurring workflows, and complex scheduling patterns.
The system processes over 100K workflow tasks daily across distributed worker nodes while maintaining ACID properties and providing real-time visibility into all operations.
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