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A step-by-step guide for migrating from Ollama to vLLM when shared inference becomes a bottleneck for teams of 3–15 engineers. Covers architectural differences (sequential vs. continuous batching, PagedAttention), five signals that indicate it's time to migrate, and a zero-downtime migration strategy using a Node.js proxy. The proxy supports shadow mode, canary traffic splitting (10%→50%→100%), and bidirectional request/response format translation between Ollama's custom REST API and vLLM's OpenAI-compatible API. Includes Docker Compose setup, full proxy and React hook code, parameter mapping edge cases (num_predict vs num_ctx, repeat_penalty vs frequency_penalty), post-migration tuning tips, and a Prometheus/Grafana monitoring setup.