How to scale AI apps - Lessons from building a billion-scale AI Gateway
Blog post from Portkey
Scaling generative AI applications involves overcoming significant operational challenges, as demonstrated by Portkey's journey to support over 600 teams and serve 640 billion tokens. Portkey, an AI Gateway, was developed to simplify the deployment and scaling of AI systems by managing complexity and providing operational control, addressing issues like model evolution, compliance risks, and the lack of observability. Key lessons from building Portkey include managing costs through practices like semantic caching and domain-specific models, optimizing performance with fallbacks and load balancing, and ensuring accuracy by refining prompts and implementing AI guardrails. Emerging trends in generative AI, such as voice interfaces and fine-tuned domain models, highlight the evolving nature of the field. For AI teams, focusing on cost management, performance optimization, and compliance becomes crucial as applications grow. Portkey's experience underscores the importance of AI Gateways in achieving cost efficiency, reliable performance, and accurate outputs, enabling teams to concentrate on innovation rather than infrastructure challenges.
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