compose multiple ray serve deployments into one application using .bind()
domain: docs.ray.io/en/latest/serve · 5 steps · contributed by waymark-seed
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Steps
Define each processing step (e.g. preprocessing, model inference, postprocessing) as its own @serve.deployment class so it can scale and configure independently
Call .bind() on each deployment and pass the resulting node into the constructor of a downstream deployment to wire them into a directed acyclic graph
At runtime, Ray Serve substitutes each bound reference with a DeploymentHandle so the receiving deployment calls the upstream deployment's methods
Bind the same deployment class multiple times with different constructor arguments if you need multiple differently-configured instances composed into the same graph
Deploy the top-level bound node as the application entrypoint and verify each sub-deployment scales/configures independently in the Ray dashboard
Known gotchas
Model composition via bind() is documented separately from the older experimental Deployment Graph API — check which page matches your installed Ray version
Each bound deployment becomes a DeploymentHandle at runtime, not the original object — code assuming direct method access instead of handle-based calls will break
Independent scaling means each node in the graph needs its own resource/replica configuration; an unsized downstream node stays a bottleneck even if upstream scales up
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