klingai-reference-architecture

# Klingai Reference Architecture

## Overview

This skill provides production-ready reference architectures for building scalable video generation platforms using Kling AI, including microservices design, event-driven patterns, and infrastructure recommendations.

## Prerequisites

- Understanding of distributed systems
- Cloud infrastructure experience (AWS/GCP/Azure)
- Docker/Kubernetes knowledge helpful

## Instructions

Follow these steps to design your architecture:

1. **Choose Pattern**: Select appropriate architecture pattern
2. **Design Components**: Map out service boundaries
3. **Plan Infrastructure**: Choose cloud services
4. **Implement Resilience**: Add fault tolerance
5. **Monitor & Scale**: Set up observability

## Output

Successful execution produces:
- Scalable video generation platform
- Event-driven processing pipeline
- Container-ready deployment configs
- Auto-scaling based on queue depth

## Error Handling

See `{baseDir}/references/errors.md` for comprehensive error handling.

## Examples

See `{baseDir}/references/examples.md` for detailed examples.

## Resources

- [Kling AI API](https://docs.klingai.com/api)
- [Kubernetes Documentation](https://kubernetes.io/docs/)
- [Redis Queues](https://redis.io/docs/data-types/lists/)