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What are best practices for Scaling ML Infrastructure

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When working with Scaling ML Infrastructure, start with a clear goal, test on real data early, keep the approach as simple as possible at first, and follow established practices from the AI community rather than guessing.
Real-world example A growing app scales its ML infrastructure by moving from a single server to a distributed cloud setup to handle millions of daily predictions.

Common follow-ups: What is AI Model Deployment & MLOps, How is Scaling ML Infrastructure evaluated in practice, What tools are commonly used for Scaling ML Infrastructure

AI Model Deployment & MLOps topics: Introduction to MLOps Model Versioning CI/CD for Machine Learning
All 7 Scaling ML Infrastructure questions