Tackling rate limiting for LLM apps

As AI models become integral to applications, managing API rate limits has become a crucial challenge, impacting scalability, latency, and costs. Rate limits are imposed by providers to ensure fair resource distribution, prevent misuse, and maintain service reliability, but they can introduce hurdles such as delayed requests and increased operational expenses, especially during peak usage. Portkey's AI Gateway offers solutions to these challenges by providing features like fallback to alternative LLMs, load balancing, retries, and caching, which help maintain application performance and scalability. These strategies reduce strain on resources, minimize service disruptions, and enhance user experience by allowing applications to handle more requests efficiently, even during high-traffic periods. Advanced observability features also enable real-time monitoring of API usage, helping teams optimize resource allocation and prevent bottlenecks before they affect service quality.

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