Real-Time ML

Low-Latency Predictions

Serve predictions in real-time.

Requirements

Low latency: <100ms. High throughput: many requests. Reliability: 99.9%+.

Architecture

Model serving: TorchServe, TensorFlow Serving. Feature computation: online, precomputed.

Caching: frequently accessed features. Model ensembles: split traffic.

Challenges

Cold starts. Model updates. Monitoring latency.

Key Takeaways

1. Real-time needs low latency
2. Caching, precompute for speed
3. Handle model updates carefully