# How are you handling rate limits and cost monitoring with the OpenAI SDK at scale?

The OpenAI SDK made it straightforward to integrate GPT models into a backend with clean client libraries, streaming responses, and function calling that connects outputs to real actions. As usage grows, rate limits and token-based pricing can become bigger considerations, and some advanced features like fine-tuning or extended context took more time to implement than basic calls. For those running this in production, what retry and backoff patterns, monitoring, or guardrails have worked best for you?

##### Post Metadata
- Posted at: 3 months ago
- Author title: Technical Project Manager 
- Net upvotes: 1



## Related Product
[OpenAI SDK](https://www.g2.com/products/openai-sdk/reviews)

## Related Category
[AI SDK](https://www.g2.com/categories/ai-sdk)

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