Introducing canary deployments on Baseten
Oct 31, 2024

Summary
This post introduces canary deployments to the Baseten platform. It details how traffic is gradually shifted to new deployments in 10 equal steps over a user-defined timeframe, allowing for monitoring and rollback. The post contrasts this with manual workarounds and highlights benefits such as decreased latency, easier development loops, and a better end-user experience. Configuration can be done via the UI or REST API.
More from the Baseten AI Model Deployment and Serving Platform trail
- LangChain trains custom models for LangSmith Engine with Baseten Loops
- DeepSeek-V4.1-Flash: more efficient prefill for coding agents
- Blaxel is joining Baseten to build the future of agentic infrastructure
- How Baseten makes pyannote’s diarization models 9.6x faster
- Optimizing delta weight syncs for managed rollouts