107. Design an ML Model Serving and Deployment Platform
From registry to traffic for hundreds of models: gates, shadow and canary with automatic rollback, packed CPU and GPU pools, LLM serving, cells and audit.
ClassicMedium
Guided practice
Start with a template. Work through each step. Ask Coach when you need a second opinion.
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112. Design ML Model Monitoring and Drift Detection
Know within hours when hundreds of production models see broken inputs, drift or falling quality, before the labels arrive.
ClassicMedium121. Design an LLM Evaluation Platform
GPU batch generation behind a shared cache, sandboxed pass@k, calibrated judges, paired statistics, release gates, contamination checks.
ClassicMedium122. Design an Experiment Tracking and Model Registry Service
Experiment tracking and a model registry: non-blocking logging, chunked metric curves, content-addressed artifacts, lineage and a promotion gate. One-hour boards for junior, senior and staff, with the theory behind them.
ClassicMedium123. Design a Hyperparameter Tuning Service
A tuning service like Vizier: random and Bayesian search, ASHA and population-based training, trials on a shared GPU cluster.
ClassicMedium