feat: add datacenter selection example and update volume examples

04_scaling_performance/02_datacenters/README.md

@@ -0,0 +1,76 @@
+# 02_datacenters
+
+Pin endpoints to specific RunPod data centers for latency, compliance, or availability reasons.
+
+## Overview
+
+By default, endpoints deploy across all available data centers. The `datacenter` parameter restricts placement to one or more specific DCs. CPU endpoints are limited to a subset of DCs that support CPU serverless (see `CPU_DATACENTERS`).
+
+## Quick Start
+
+```bash
+pip install -r requirements.txt
+flash run
+```
+
+## What You'll Learn
+
+- How to pin a GPU endpoint to a single datacenter
+- How to deploy across multiple datacenters
+- How CPU datacenter restrictions work
+
+## Available Data Centers
+
+| ID | Location |
+|----|----------|
+| `US-GA-1` | US - Georgia |
+| `US-KS-1` | US - Kansas |
+| `US-TX-1` | US - Texas |
+| `US-OR-1` | US - Oregon |
+| `CA-MTL-1` | Canada - Montreal |
+| `EU-NL-1` | Europe - Netherlands |
+| `EU-CZ-1` | Europe - Czech Republic |
+| `EU-RO-1` | Europe - Romania |
+| `EU-NO-1` | Europe - Norway |
+| `EU-SE-1` | Europe - Sweden |
+
+CPU endpoints support: `EU-RO-1`, `US-TX-1`, `EU-SE-1`.
+
+## Examples
+
+**Single datacenter:**
+
+```python
+@Endpoint(name="us-worker", gpu=GpuGroup.ANY, datacenter=DataCenter.US_GA_1)
+async def inference(data: dict) -> dict:
+    ...
+```
+
+**Multiple datacenters:**
+
+```python
+@Endpoint(
+    name="global-worker",
+    gpu=GpuGroup.ANY,
+    datacenter=[DataCenter.US_GA_1, DataCenter.EU_RO_1],
+)
+async def inference(data: dict) -> dict:
+    ...
+```
+
+**No datacenter (default, all DCs):**
+
+```python
+@Endpoint(name="anywhere", gpu=GpuGroup.ANY)
+async def inference(data: dict) -> dict:
+    ...
+```
+
+## Project Structure
+
+```
+02_datacenters/
+├── gpu_worker.py    # single-DC and multi-DC GPU endpoints
+├── cpu_worker.py    # CPU endpoint in a supported DC
+└── README.md
+```

04_scaling_performance/02_datacenters/cpu_worker.py

@@ -0,0 +1,29 @@
+# cpu worker pinned to a cpu-supported datacenter.
+# cpu endpoints are only available in a subset of datacenters
+# (see CPU_DATACENTERS). selecting an unsupported DC raises an error.
+# run with: flash run
+from runpod_flash import Endpoint, DataCenter
+
+api = Endpoint(
+    name="04_02_cpu_eu",
+    cpu="cpu3c-2-4",
+    workers=(0, 2),
+    datacenter=DataCenter.EU_RO_1,
+)
+
+
+@api.post("/process")
+async def process(data: dict) -> dict:
+    """CPU processing pinned to EU-RO-1."""
+    return {"datacenter": "EU-RO-1", "result": data}
+
+
+@api.get("/health")
+async def health():
+    return {"status": "ok"}
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    print(asyncio.run(process({"text": "hello"})))

04_scaling_performance/02_datacenters/gpu_worker.py

@@ -0,0 +1,39 @@
+# gpu workers pinned to specific datacenters.
+# run with: flash run
+from runpod_flash import Endpoint, GpuGroup, DataCenter
+
+
+# pin to a single datacenter
+@Endpoint(
+    name="04_02_gpu_us",
+    gpu=GpuGroup.ANY,
+    workers=(0, 3),
+    datacenter=DataCenter.US_GA_1,
+)
+async def us_inference(payload: dict) -> dict:
+    """GPU inference pinned to US-GA-1."""
+    return {"datacenter": "US-GA-1", "result": payload}
+
+
+# deploy across multiple datacenters for broader availability
+@Endpoint(
+    name="04_02_gpu_multi",
+    gpu=GpuGroup.ANY,
+    workers=(0, 3),
+    datacenter=[DataCenter.US_GA_1, DataCenter.EU_RO_1],
+)
+async def multi_dc_inference(payload: dict) -> dict:
+    """GPU inference available in US-GA-1 and EU-RO-1."""
+    return {"result": payload}
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    async def test():
+        print("=== US datacenter ===")
+        print(await us_inference({"prompt": "hello"}))
+        print("\n=== Multi-DC ===")
+        print(await multi_dc_inference({"prompt": "hello"}))
+
+    asyncio.run(test())

05_data_workflows/01_network_volumes/cpu_worker.py

@@ -1,18 +1,21 @@
 # cpu worker with network volume for listing and serving generated images.
 # run with: flash run
 # test directly: python cpu_worker.py
-from runpod_flash import Endpoint, NetworkVolume
+from runpod_flash import Endpoint, DataCenter, NetworkVolume
 
+# same volume as gpu_worker.py -- must match name and datacenter
 volume = NetworkVolume(
     name="flash-05-volume",
     size=50,
+    datacenter=DataCenter.EU_RO_1,
 )
 
 api = Endpoint(
     name="05_01_cpu_worker",
     cpu="cpu3c-1-2",
     workers=(1, 3),
     idle_timeout=120,
+    datacenter=DataCenter.EU_RO_1,
     volume=volume,
 )
 

05_data_workflows/01_network_volumes/gpu_worker.py

@@ -3,7 +3,7 @@
 # test directly: python gpu_worker.py
 import logging
 
-from runpod_flash import Endpoint, GpuType, NetworkVolume
+from runpod_flash import Endpoint, GpuType, DataCenter, NetworkVolume
 
 logger = logging.getLogger(__name__)
 
@@ -12,6 +12,7 @@
 volume = NetworkVolume(
     name="flash-05-volume",
     size=50,
+    datacenter=DataCenter.EU_RO_1,
 )
 
 
@@ -20,6 +21,7 @@
     gpu=GpuType.NVIDIA_GEFORCE_RTX_5090,
     workers=(0, 3),
     idle_timeout=300,
+    datacenter=DataCenter.EU_RO_1,
     volume=volume,
     env={"HF_HUB_CACHE": MODEL_PATH, "MODEL_PATH": MODEL_PATH},
     dependencies=["torch", "diffusers", "transformers", "accelerate"],