Best Practices for Integrating the Genny API in Production

I’m looking to learn from developers and teams who have integrated the Genny API into real-world, production-level applications. Since Genny provides AI voice generation, video creation, script writing, and job-based processing, a solid API integration strategy is crucial for reliability, speed, and cost efficiency.

Specifically, I’d like to hear about:

How you structure your API integration for scalability (batch generation, queuing, asynchronous jobs, error handling).

Your best practices for managing long-running jobs like voice generation, video rendering, or subtitle generation.

Techniques for handling API rate limits, retries, and robust error-handling patterns.

How you secure API keys and manage authentication in production environments.

Caching strategies you use for generated voice/audio files or repeated script requests.

How you manage cost optimization when using Genny at scale.

Any DevOps workflows—CI/CD or monitoring—that help ensure your Genny-powered features run smoothly.

Real examples of issues you encountered (timeouts, job failures, network spikes) and how you solved them.

Tools, frameworks, or architectural patterns that pair well with the Genny API (serverless, background workers, message queues, etc.).

Whether you're using Genny for voice generation, automated video creation, or powering a content production pipeline, your insights can help others build more reliable and efficient integrations.

Looking forward to hearing your experiences and recommendations!