Regional environments

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How regional environments work

1. Replicas are constrained to workload planes within the designated region. Deployments promoted to that environment only run in the allowed region.
2. A regional inference endpoint becomes available that routes requests directly to the region-specific workload plane.

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Compare regional and standard endpoints

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Set up regional environments

1. Create environments with region-specific names (for example, prod-us, prod-eu, staging-eu). Use restricted environments to control access.
2. Contact Baseten support to configure the required region and endpoint restrictions for your environments.
3. Update your calling code to use the regional endpoint format: https://model-{model_id}-{env_name}.api.baseten.co/predict.

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Environment naming requirements

• Lowercase alphanumeric characters and hyphens only.
• Can’t start or end with a hyphen.
• Maximum 40 characters.
• Baseten reserves development and region.
• Baseten reserves names that start with region-.

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Deploy to regional environments

baseten model push --environment prod-us --region <region-slug>

truss push --environment prod-us

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Promotion behavior

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Regional endpoint formats

https://model-{model_id}-{env_name}.api.baseten.co/predict

https://chain-{chain_id}-{env_name}.api.baseten.co/run_remote

wss://model-{model_id}-{env_name}.api.baseten.co/websocket
wss://chain-{chain_id}-{env_name}.api.baseten.co/websocket

model-{model_id}-{env_name}.grpc.api.baseten.co:443

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Request restrictions

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Call a regional endpoint

import httpx
import os

model_id = "<your-model-id>"
env_name = "prod-us"

client = httpx.Client(
    base_url=f"https://model-{model_id}-{env_name}.api.baseten.co",
    headers={"Authorization": f"Bearer {os.environ['BASETEN_API_KEY']}"},
)

response = client.post("/predict", json={"prompt": "Hello, world!"})
print(response.json())

curl -X POST https://model-{model_id}-{env_name}.api.baseten.co/predict \
  -H "Authorization: Bearer $BASETEN_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"prompt": "Hello, world!"}'

const modelId = "<your-model-id>";
const envName = "prod-us";

const resp = await fetch(
  `https://model-${modelId}-${envName}.api.baseten.co/predict`,
  {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env.BASETEN_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({ prompt: "Hello, world!" }),
  }
);

const data = await resp.json();
console.log(data);