diff --git a/.gitignore b/.gitignore
index ece0ddaa..ec966b94 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,6 +6,9 @@
 # macOS
 .DS_Store
 
+# LiveShare cache files
+*.lscache
+
 # User-specific files
 *.rsuser
 *.suo
diff --git a/samples/python/external-agents/observability/.env.example b/samples/python/external-agents/observability/.env.example
new file mode 100644
index 00000000..c76ee217
--- /dev/null
+++ b/samples/python/external-agents/observability/.env.example
@@ -0,0 +1,11 @@
+AZURE_SUBSCRIPTION_ID=<subscription-id>
+FOUNDRY_PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>
+RESOURCE_GROUP=<resource-group>
+LOCATION=eastus2
+ACA_ENV=<container-apps-environment>
+ACR_NAME=<acr-name>
+APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=<key>;IngestionEndpoint=<endpoint>
+AZURE_OPENAI_ENDPOINT=https://<aoai-resource>.openai.azure.com
+AZURE_OPENAI_DEPLOYMENT=gpt-4o-mini
+AZURE_OPENAI_API_VERSION=2024-10-21
+AZURE_OPENAI_API_KEY=<optional-api-key>
diff --git a/samples/python/external-agents/observability/Dockerfile b/samples/python/external-agents/observability/Dockerfile
new file mode 100644
index 00000000..c5d3e3c4
--- /dev/null
+++ b/samples/python/external-agents/observability/Dockerfile
@@ -0,0 +1,16 @@
+FROM python:3.11-slim
+
+ENV PYTHONUNBUFFERED=1 \
+    PYTHONDONTWRITEBYTECODE=1 \
+    PORT=8000
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY weather_agent.py .
+
+EXPOSE 8000
+
+CMD ["python", "weather_agent.py"]
diff --git a/samples/python/external-agents/observability/README.md b/samples/python/external-agents/observability/README.md
new file mode 100644
index 00000000..72d53315
--- /dev/null
+++ b/samples/python/external-agents/observability/README.md
@@ -0,0 +1,169 @@
+# External Agent Observability — Weather Agent on ACA
+
+This sample shows the **end-to-end story for a Foundry "external" agent**:
+a third-party agent runtime that lives **outside** Foundry, registered
+into Foundry purely so its OpenTelemetry traces and Foundry-side
+evaluations light up in the portal.
+
+The runtime here is a tiny [LangChain](https://python.langchain.com/)
+weather agent (LangGraph ReAct), instrumented with the
+[Microsoft OpenTelemetry distro](https://github.com/microsoft/opentelemetry-distro-python)
+so its spans flow into the Application Insights connected to your
+Foundry project. We deploy it to **Azure Container Apps** to play the
+role of "agent hosted somewhere outside Foundry" (it could just as
+easily be GCP Cloud Run, AWS, or on-prem).
+
+> **Preview note.** External agents are gated behind
+> `Foundry-Features: ExternalAgents=V1Preview` while in public preview.
+> The SDK calls below opt in via `allow_preview=True`.
+
+> **Distro note.** The Microsoft OTel distro does not yet accept an
+> explicit `otel_agent_id` input
+> ([microsoft/opentelemetry-distro-python#148](https://github.com/microsoft/opentelemetry-distro-python/issues/148)).
+> Until that ships, this sample relies on the default `gen_ai.agent.id`
+> emitted by the LangChain instrumentation. The Foundry registration
+> uses the matching agent name so the Foundry trace view will resolve
+> once the distro fix is available.
+
+## Microsoft OpenTelemetry distro — references
+
+To learn more about the distro or to find samples in another language,
+start here:
+
+- **Docs:** [Microsoft OpenTelemetry overview](https://learn.microsoft.com/en-us/azure/microsoft-opentelemetry/overview)
+- **Samples by language:**
+  - .NET — [microsoft/opentelemetry-distro-dotnet](https://github.com/microsoft/opentelemetry-distro-dotnet)
+  - Python — [microsoft/opentelemetry-distro-python](https://github.com/microsoft/opentelemetry-distro-python)
+  - JavaScript — [microsoft/opentelemetry-distro-javascript](https://github.com/microsoft/opentelemetry-distro-javascript)
+
+## What's in this folder
+
+| File | Purpose |
+| --- | --- |
+| [weather_agent.py](weather_agent.py) | LangChain weather agent + Microsoft OTel distro, exposed as a FastAPI HTTP service. This is the "external runtime". |
+| [.env.example](.env.example) | Placeholder environment template for local configuration. |
+| [Dockerfile](Dockerfile) | Container image for the weather agent. |
+| [deploy.sh](deploy.sh) / [deploy.ps1](deploy.ps1) | Build, push to ACR, deploy to ACA, and generate traffic. |
+| [generate_traffic.py](generate_traffic.py) | Hits the deployed agent with a handful of weather questions. |
+| [register_external_agent.py](register_external_agent.py) | Registers the runtime in Foundry as `kind=external` via the `azure-ai-projects` SDK. |
+| [run_trace_eval.py](run_trace_eval.py) | Runs a one-off trace-based eval over the registered agent and prints scores. |
+| [requirements.txt](requirements.txt) | Python deps for both the runtime and the helper scripts. |
+
+## Architecture
+
+```
+   ┌────────────────────────┐         OTel spans          ┌─────────────────────┐
+   │  Weather agent (ACA)   │ ─────────────────────────▶  │ Application Insights │
+   │  LangChain + MS distro │   gen_ai.agent.id =         │ (linked to project) │
+   └────────────────────────┘   "weather-agent"           └─────────┬───────────┘
+                                                                    │
+                              register_external_agent.py            │ trace view
+                                       │                            ▼
+                                       ▼                     ┌─────────────────────┐
+                              ┌─────────────────────┐        │   Foundry Portal    │
+                              │  Foundry Project    │ ◀────  │  Agents → traces    │
+                              │  agent kind=external│        │  Evaluations        │
+                              └─────────────────────┘        └─────────────────────┘
+```
+
+## Prerequisites
+
+1. **Azure resources**
+   - A Foundry project with an Application Insights connection.
+   - An Azure Container Apps environment + ACR in the same subscription.
+   - An Azure OpenAI deployment (e.g. `gpt-4o-mini`) for both the agent
+     LLM and the eval judge. (You can split them with the
+     `EVAL_MODEL_DEPLOYMENT` env var.)
+2. **Permissions** — `Contributor` (or equivalent) on the RG, plus
+   permission to create agents in the Foundry project (e.g.
+   `Azure AI User`).
+3. **Tooling** — Azure CLI, Docker is *not* required (we use
+   `az acr build`), Python 3.11+.
+
+## Step 1 — Configure environment
+
+Start from [.env.example](.env.example), create a local `.env`, and
+load those values into your shell before running the scripts. The local
+`.env` file is ignored by git.
+
+```bash
+export AZURE_SUBSCRIPTION_ID="<subscription-id>"
+export FOUNDRY_PROJECT_ENDPOINT="https://<resource>.services.ai.azure.com/api/projects/<project>"
+export RESOURCE_GROUP="..."
+export LOCATION="eastus2"
+export ACA_ENV="..."
+export ACR_NAME="..."
+export APPLICATIONINSIGHTS_CONNECTION_STRING="InstrumentationKey=...;IngestionEndpoint=..."
+export AZURE_OPENAI_ENDPOINT="https://<aoai>.openai.azure.com"
+export AZURE_OPENAI_DEPLOYMENT="gpt-4o-mini"
+export AZURE_OPENAI_API_VERSION="2024-10-21"
+export AZURE_OPENAI_API_KEY="..."
+```
+
+PowerShell users: set the same names with `$env:NAME = "..."`.
+
+## Step 2 — Deploy the external runtime to ACA and generate traffic
+
+```bash
+cd samples/python/external-agents/observability
+./deploy.sh           # or .\deploy.ps1 on Windows
+```
+
+The script will:
+
+1. `az acr build` the image.
+2. Create or update the Container App.
+3. Wait for `/healthz`.
+4. Run [generate_traffic.py](generate_traffic.py) to ask several weather
+   questions.
+5. Wait for OTel export and ingestion. Override the default 90 seconds
+   with `TRACE_INGEST_WAIT_SECS` if needed.
+
+## Step 3 — Register the external agent in Foundry
+
+```bash
+python register_external_agent.py
+```
+
+This calls `project_client.agents.create_version(...)` with an
+`ExternalAgentDefinition`, which atomically creates the Foundry agent
+record on first call (per the spec, external agents are versionless
+from the user's perspective). After registration succeeds, open the
+Foundry portal:
+
+> **Project → Agents → `weather-agent` → Traces**
+
+You should see the spans you just generated, attributed to the new
+`external` agent.
+
+## Step 4 — Run a one-off trace evaluation
+
+```bash
+python run_trace_eval.py
+```
+
+This:
+
+1. Resolves the registered agent's `otel_agent_id`.
+2. Creates an OpenAI-compatible eval group with two built-in trace
+   evaluators (`intent_resolution`, `task_adherence`).
+3. Creates an `azure_ai_traces_preview` run scoped to that
+   `agent_id` over the last 24 hours.
+4. Polls until completion and prints per-criterion pass/fail counts.
+
+> The trace-eval surface is currently only on the OpenAI-compatible
+> `evals` API (`project_client.get_openai_client().evals`). When the
+> native `project_client.evaluations` surface adds trace-eval support,
+> this sample will move there.
+
+## Cleanup
+
+```bash
+az containerapp delete -n "$AGENT_NAME" -g "$RESOURCE_GROUP" --yes
+# Optional: delete the Foundry registration (does not affect the runtime)
+python -c "import os; from azure.identity import DefaultAzureCredential; \
+from azure.ai.projects import AIProjectClient; \
+AIProjectClient(endpoint=os.environ['FOUNDRY_PROJECT_ENDPOINT'], \
+credential=DefaultAzureCredential(), allow_preview=True) \
+.agents.delete(agent_name=os.environ.get('AGENT_NAME','weather-agent'))"
+```
diff --git a/samples/python/external-agents/observability/deploy.ps1 b/samples/python/external-agents/observability/deploy.ps1
new file mode 100644
index 00000000..a20cb73d
--- /dev/null
+++ b/samples/python/external-agents/observability/deploy.ps1
@@ -0,0 +1,105 @@
+<#
+.SYNOPSIS
+  Deploy the weather agent to Azure Container Apps and generate traffic.
+
+.DESCRIPTION
+  Mirrors deploy.sh for Windows / PowerShell users. Requires the
+  Azure CLI (`az`) and Python on PATH.
+
+.NOTES
+  Required env vars:
+    AZURE_SUBSCRIPTION_ID,
+    RESOURCE_GROUP, LOCATION, ACA_ENV, ACR_NAME,
+    APPLICATIONINSIGHTS_CONNECTION_STRING,
+    AZURE_OPENAI_ENDPOINT, AZURE_OPENAI_DEPLOYMENT
+  Optional:
+    AZURE_OPENAI_API_KEY, AGENT_NAME (default weather-agent), IMAGE_TAG (default current timestamp),
+    TRACE_INGEST_WAIT_SECS (default 90)
+#>
+
+$ErrorActionPreference = "Stop"
+
+function Require-Env($name) {
+  if (-not (Get-Item "Env:$name" -ErrorAction SilentlyContinue)) {
+    throw "Missing required env var: $name"
+  }
+}
+
+foreach ($v in @(
+  "AZURE_SUBSCRIPTION_ID",
+  "RESOURCE_GROUP","LOCATION","ACA_ENV","ACR_NAME",
+  "APPLICATIONINSIGHTS_CONNECTION_STRING",
+  "AZURE_OPENAI_ENDPOINT","AZURE_OPENAI_DEPLOYMENT"
+)) { Require-Env $v }
+
+Write-Host "==> Selecting Azure subscription"
+az account set --subscription $env:AZURE_SUBSCRIPTION_ID --only-show-errors
+
+$AgentName  = if ($env:AGENT_NAME)    { $env:AGENT_NAME }    else { "weather-agent" }
+$OtelAgentId = if ($env:OTEL_AGENT_ID) { $env:OTEL_AGENT_ID } else { $AgentName }
+$ImageTag   = if ($env:IMAGE_TAG)     { $env:IMAGE_TAG }     else { Get-Date -Format "yyyyMMddHHmmss" }
+$TraceIngestWaitSecs = if ($env:TRACE_INGEST_WAIT_SECS) { [int]$env:TRACE_INGEST_WAIT_SECS } else { 90 }
+$Image     = "$($env:ACR_NAME).azurecr.io/${AgentName}:${ImageTag}"
+
+Write-Host "==> Building and pushing image to ACR"
+az acr build --registry $env:ACR_NAME --image "${AgentName}:${ImageTag}" --no-logs --only-show-errors . | Out-Null
+
+Write-Host "==> Deploying to Azure Container Apps"
+$envVars = @(
+  "AGENT_NAME=$AgentName",
+  "OTEL_AGENT_ID=$OtelAgentId",
+  "APPLICATIONINSIGHTS_CONNECTION_STRING=$($env:APPLICATIONINSIGHTS_CONNECTION_STRING)",
+  "AZURE_OPENAI_ENDPOINT=$($env:AZURE_OPENAI_ENDPOINT)",
+  "AZURE_OPENAI_DEPLOYMENT=$($env:AZURE_OPENAI_DEPLOYMENT)",
+  "AZURE_OPENAI_API_VERSION=$(if ($env:AZURE_OPENAI_API_VERSION) { $env:AZURE_OPENAI_API_VERSION } else { '2024-10-21' })",
+  "AZURE_OPENAI_API_KEY=$($env:AZURE_OPENAI_API_KEY)"
+)
+
+$exists = az containerapp show -n $AgentName -g $env:RESOURCE_GROUP --only-show-errors 2>$null
+if ($LASTEXITCODE -eq 0 -and $exists) {
+  az containerapp update `
+    -n $AgentName `
+    -g $env:RESOURCE_GROUP `
+    --image $Image `
+    --set-env-vars $envVars `
+    --only-show-errors | Out-Null
+} else {
+  az containerapp create `
+    --name $AgentName `
+    --resource-group $env:RESOURCE_GROUP `
+    --environment $env:ACA_ENV `
+    --image $Image `
+    --target-port 8000 `
+    --ingress external `
+    --min-replicas 1 --max-replicas 2 `
+    --registry-server "$($env:ACR_NAME).azurecr.io" `
+    --system-assigned `
+    --registry-identity system `
+    --env-vars $envVars `
+    --only-show-errors | Out-Null
+}
+
+$Fqdn = az containerapp show -n $AgentName -g $env:RESOURCE_GROUP `
+        --query properties.configuration.ingress.fqdn -o tsv --only-show-errors
+$AgentUrl = "https://$Fqdn"
+Write-Host "==> Agent URL: $AgentUrl"
+
+Write-Host "==> Waiting for /healthz"
+for ($i = 0; $i -lt 30; $i++) {
+  try { Invoke-WebRequest -UseBasicParsing -Uri "$AgentUrl/healthz" -TimeoutSec 10 | Out-Null; break }
+  catch { Start-Sleep -Seconds 5 }
+}
+
+Write-Host "==> Generating traffic"
+$env:AGENT_URL = $AgentUrl
+$env:AGENT_NAME = $AgentName
+$env:OTEL_AGENT_ID = $OtelAgentId
+python generate_traffic.py
+
+if ($TraceIngestWaitSecs -gt 0) {
+  Write-Host "==> Waiting ${TraceIngestWaitSecs}s for OTel export and ingestion"
+  Start-Sleep -Seconds $TraceIngestWaitSecs
+}
+
+Write-Host "==> Done. Agent URL: $AgentUrl"
+Write-Host "==> Then run: python register_external_agent.py; python run_trace_eval.py"
diff --git a/samples/python/external-agents/observability/deploy.sh b/samples/python/external-agents/observability/deploy.sh
new file mode 100644
index 00000000..bdb99e10
--- /dev/null
+++ b/samples/python/external-agents/observability/deploy.sh
@@ -0,0 +1,101 @@
+#!/usr/bin/env bash
+# Deploy the weather agent to Azure Container Apps and generate traffic.
+#
+# Required env vars:
+#   AZURE_SUBSCRIPTION_ID              - Azure subscription to deploy into
+#   RESOURCE_GROUP                     - existing RG
+#   LOCATION                           - e.g. eastus2
+#   ACA_ENV                            - existing Container Apps env name
+#   ACR_NAME                           - existing Azure Container Registry
+#   APPLICATIONINSIGHTS_CONNECTION_STRING
+#   AZURE_OPENAI_ENDPOINT
+#   AZURE_OPENAI_DEPLOYMENT
+#   AZURE_OPENAI_API_KEY               - or rely on AAD via DefaultAzureCredential
+#
+# Optional:
+#   AGENT_NAME              (default: weather-agent)
+#   IMAGE_TAG               (default: current timestamp)
+#   TRACE_INGEST_WAIT_SECS  (default: 90)
+
+set -euo pipefail
+
+AGENT_NAME="${AGENT_NAME:-weather-agent}"
+IMAGE_TAG="${IMAGE_TAG:-$(date +%Y%m%d%H%M%S)}"
+TRACE_INGEST_WAIT_SECS="${TRACE_INGEST_WAIT_SECS:-90}"
+IMAGE="${ACR_NAME}.azurecr.io/${AGENT_NAME}:${IMAGE_TAG}"
+
+: "${AZURE_SUBSCRIPTION_ID:?}"
+: "${RESOURCE_GROUP:?}"; : "${LOCATION:?}"; : "${ACA_ENV:?}"; : "${ACR_NAME:?}"
+: "${APPLICATIONINSIGHTS_CONNECTION_STRING:?}"
+: "${AZURE_OPENAI_ENDPOINT:?}"; : "${AZURE_OPENAI_DEPLOYMENT:?}"
+
+echo "==> Selecting Azure subscription"
+az account set --subscription "$AZURE_SUBSCRIPTION_ID" --only-show-errors
+
+echo "==> Building and pushing image to ACR"
+az acr build \
+  --registry "$ACR_NAME" \
+  --image "${AGENT_NAME}:${IMAGE_TAG}" \
+  --no-logs \
+  --only-show-errors \
+  .
+
+echo "==> Deploying to Azure Container Apps"
+az containerapp create \
+  --name "$AGENT_NAME" \
+  --resource-group "$RESOURCE_GROUP" \
+  --environment "$ACA_ENV" \
+  --image "$IMAGE" \
+  --target-port 8000 \
+  --ingress external \
+  --min-replicas 1 \
+  --max-replicas 2 \
+  --registry-server "${ACR_NAME}.azurecr.io" \
+  --system-assigned \
+  --registry-identity system \
+  --env-vars \
+    AGENT_NAME="$AGENT_NAME" \
+    OTEL_AGENT_ID="${OTEL_AGENT_ID:-$AGENT_NAME}" \
+    APPLICATIONINSIGHTS_CONNECTION_STRING="$APPLICATIONINSIGHTS_CONNECTION_STRING" \
+    AZURE_OPENAI_ENDPOINT="$AZURE_OPENAI_ENDPOINT" \
+    AZURE_OPENAI_DEPLOYMENT="$AZURE_OPENAI_DEPLOYMENT" \
+    AZURE_OPENAI_API_VERSION="${AZURE_OPENAI_API_VERSION:-2024-10-21}" \
+    AZURE_OPENAI_API_KEY="${AZURE_OPENAI_API_KEY:-}" \
+    --output none \
+    --only-show-errors \
+  || az containerapp update \
+       --name "$AGENT_NAME" \
+       --resource-group "$RESOURCE_GROUP" \
+       --image "$IMAGE" \
+    --set-env-vars \
+      AGENT_NAME="$AGENT_NAME" \
+      OTEL_AGENT_ID="${OTEL_AGENT_ID:-$AGENT_NAME}" \
+      APPLICATIONINSIGHTS_CONNECTION_STRING="$APPLICATIONINSIGHTS_CONNECTION_STRING" \
+      AZURE_OPENAI_ENDPOINT="$AZURE_OPENAI_ENDPOINT" \
+      AZURE_OPENAI_DEPLOYMENT="$AZURE_OPENAI_DEPLOYMENT" \
+      AZURE_OPENAI_API_VERSION="${AZURE_OPENAI_API_VERSION:-2024-10-21}" \
+      AZURE_OPENAI_API_KEY="${AZURE_OPENAI_API_KEY:-}" \
+      --output none \
+      --only-show-errors
+
+FQDN=$(az containerapp show -n "$AGENT_NAME" -g "$RESOURCE_GROUP" \
+       --query properties.configuration.ingress.fqdn -o tsv --only-show-errors)
+AGENT_URL="https://${FQDN}"
+echo "==> Agent URL: $AGENT_URL"
+
+echo "==> Waiting for /healthz"
+for i in {1..30}; do
+  if curl -fsS --max-time 10 "${AGENT_URL}/healthz" >/dev/null; then break; fi
+  sleep 5
+done
+
+echo "==> Generating traffic"
+AGENT_URL="$AGENT_URL" AGENT_NAME="$AGENT_NAME" OTEL_AGENT_ID="${OTEL_AGENT_ID:-$AGENT_NAME}" python generate_traffic.py
+
+if [ "$TRACE_INGEST_WAIT_SECS" -gt 0 ]; then
+  echo "==> Waiting ${TRACE_INGEST_WAIT_SECS}s for OTel export and ingestion"
+  sleep "$TRACE_INGEST_WAIT_SECS"
+fi
+
+echo "==> Done. Agent URL: $AGENT_URL"
+echo "==> Then run: python register_external_agent.py && python run_trace_eval.py"
diff --git a/samples/python/external-agents/observability/generate_traffic.py b/samples/python/external-agents/observability/generate_traffic.py
new file mode 100644
index 00000000..4a1d0002
--- /dev/null
+++ b/samples/python/external-agents/observability/generate_traffic.py
@@ -0,0 +1,36 @@
+"""Hit the deployed weather agent with varied questions so there are
+spans in Application Insights for the eval run to score.
+"""
+
+from __future__ import annotations
+
+import os
+import sys
+
+import httpx
+
+QUESTIONS = [
+    "What's the weather in Seattle right now?",
+    "Give me a 5-day forecast for Tokyo.",
+    "Compare today's weather in New York and London.",
+    "Should I bring an umbrella in Seattle today?",
+    "What's the warmest of these cities right now: Seattle, Tokyo, London?",
+]
+
+
+def main() -> None:
+    base_url = os.environ.get("AGENT_URL") or (sys.argv[1] if len(sys.argv) > 1 else None)
+    if not base_url:
+        raise SystemExit("Set AGENT_URL or pass the agent base URL as argv[1].")
+
+    base_url = base_url.rstrip("/")
+    with httpx.Client(timeout=60.0) as client:
+        for question in QUESTIONS:
+            print(f"\n>>> {question}")
+            response = client.post(f"{base_url}/ask", json={"question": question})
+            response.raise_for_status()
+            print(response.json().get("answer"))
+
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/samples/python/external-agents/observability/register_external_agent.py b/samples/python/external-agents/observability/register_external_agent.py
new file mode 100644
index 00000000..cd8fd6d8
--- /dev/null
+++ b/samples/python/external-agents/observability/register_external_agent.py
@@ -0,0 +1,62 @@
+"""Register the externally hosted weather agent in Foundry.
+
+After this runs successfully, open the Foundry portal -> your project ->
+Agents -> ``weather-agent`` to see the trace view light up with spans
+emitted by the running container.
+
+Prereqs:
+    * FOUNDRY_PROJECT_ENDPOINT env var
+    * AAD credentials with permission to create agents in the project
+    * The external runtime (weather_agent.py) is already emitting OTel
+      spans to the Application Insights connected to the Foundry project
+"""
+
+from __future__ import annotations
+
+import os
+
+from azure.ai.projects import AIProjectClient
+from azure.ai.projects.models import ExternalAgentDefinition
+from azure.identity import DefaultAzureCredential
+
+AGENT_NAME = os.environ.get("AGENT_NAME", "weather-agent")
+# The id the running agent emits as gen_ai.agent.id on its OTel spans.
+# Defaults to AGENT_NAME but can differ -- e.g. "weather-agent-v1".
+OTEL_AGENT_ID = os.environ.get("OTEL_AGENT_ID", AGENT_NAME)
+
+
+def main() -> None:
+    project_client = AIProjectClient(
+        endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        credential=DefaultAzureCredential(),
+        # External agents are gated behind a preview feature flag during
+        # public preview. See spec: Foundry-Features: ExternalAgents=V1Preview.
+        allow_preview=True,
+    )
+
+    # First-time create goes through create_version() in azure-ai-projects
+    # v2.1.0; called with a new agent_name it atomically creates the
+    # agent + first registration revision. External agents are
+    # versionless from the user's perspective.
+    agent = project_client.agents.create_version(
+        agent_name=AGENT_NAME,
+        description="Weather agent hosted externally on Azure Container Apps.",
+        definition=ExternalAgentDefinition(
+            # Optional: defaults to agent_name. Set explicitly here so
+            # the mapping to gen_ai.agent.id on the OTel spans is
+            # obvious -- and to show otel_agent_id can differ from the
+            # Foundry agent name (e.g. "weather-agent-v1").
+            otel_agent_id=OTEL_AGENT_ID,
+        ),
+    )
+
+    print(f"Registered external agent: {agent.name}")
+    print(f"Resolved otel_agent_id  : {agent.versions.latest.definition.otel_agent_id}")
+    print()
+    print("Open the Foundry portal and navigate to:")
+    print(f"  Project -> Agents -> {agent.name} -> Traces")
+    print("to see traces emitted by the external runtime.")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/samples/python/external-agents/observability/requirements.txt b/samples/python/external-agents/observability/requirements.txt
new file mode 100644
index 00000000..c964c3e4
--- /dev/null
+++ b/samples/python/external-agents/observability/requirements.txt
@@ -0,0 +1,10 @@
+azure-ai-projects>=2.1.0
+azure-identity>=1.17.0
+microsoft-opentelemetry[langchain]>=1.2.0
+langchain>=0.3.0
+langchain-openai>=0.2.0
+langchain-core>=0.3.0
+fastapi>=0.115.0
+uvicorn[standard]>=0.30.0
+httpx>=0.27.0
+openai>=1.50.0
diff --git a/samples/python/external-agents/observability/run_trace_eval.py b/samples/python/external-agents/observability/run_trace_eval.py
new file mode 100644
index 00000000..20a029ec
--- /dev/null
+++ b/samples/python/external-agents/observability/run_trace_eval.py
@@ -0,0 +1,116 @@
+"""Run a one-off trace-based evaluation over the registered external
+weather agent and print the per-criterion scores.
+
+The trace-eval surface is currently exposed only via the OpenAI-compatible
+``evals`` API (``azure_ai_source`` / ``azure_ai_traces_preview`` data sources),
+so we go through ``project_client.get_openai_client()`` per the spec.
+"""
+
+from __future__ import annotations
+
+import os
+import time
+
+from azure.ai.projects import AIProjectClient
+from azure.identity import DefaultAzureCredential
+
+AGENT_NAME = os.environ.get("AGENT_NAME", "weather-agent")
+EVAL_DEPLOYMENT = os.environ.get(
+    "EVAL_MODEL_DEPLOYMENT",
+    os.environ.get("AZURE_OPENAI_DEPLOYMENT", "gpt-4o-mini"),
+)
+LOOKBACK_HOURS = int(os.environ.get("LOOKBACK_HOURS", "24"))
+POLL_TIMEOUT_SECS = int(os.environ.get("EVAL_POLL_TIMEOUT_SECS", "900"))
+
+
+def main() -> None:
+    project_client = AIProjectClient(
+        endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
+        credential=DefaultAzureCredential(),
+        allow_preview=True,
+    )
+
+    # Resolve otel_agent_id from the registration so we evaluate exactly
+    # the spans Foundry attributes to this agent.
+    agent = project_client.agents.get(agent_name=AGENT_NAME)
+    otel_agent_id = agent.versions.latest.definition.otel_agent_id
+    print(f"Evaluating traces for agent_id={otel_agent_id} (last {LOOKBACK_HOURS}h)")
+
+    openai_client = project_client.get_openai_client()
+
+    # 1. Eval group -- defines what we measure.
+    eval_group = openai_client.evals.create(
+        name=f"{AGENT_NAME}-trace-eval",
+        data_source_config={"type": "azure_ai_source", "scenario": "traces_preview"},
+        testing_criteria=[
+            {
+                "type": "azure_ai_evaluator",
+                "name": "intent_resolution",
+                "evaluator_name": "builtin.intent_resolution",
+                "data_mapping": {
+                    "query": "{{query}}",
+                    "response": "{{response}}",
+                    "tool_definitions": "{{tool_definitions}}",
+                },
+                "initialization_parameters": {"deployment_name": EVAL_DEPLOYMENT},
+            },
+            {
+                "type": "azure_ai_evaluator",
+                "name": "task_adherence",
+                "evaluator_name": "builtin.task_adherence",
+                "data_mapping": {
+                    "query": "{{query}}",
+                    "response": "{{response}}",
+                    "tool_definitions": "{{tool_definitions}}",
+                },
+                "initialization_parameters": {"deployment_name": EVAL_DEPLOYMENT},
+            },
+        ],
+    )
+
+    # 2. One-off run -- scoped to this agent's traces over the lookback.
+    run = openai_client.evals.runs.create(
+        eval_id=eval_group.id,
+        name=f"{AGENT_NAME}-trace-run",
+        data_source={
+            "type": "azure_ai_traces_preview",
+            "agent_id": otel_agent_id,
+            "lookback_hours": LOOKBACK_HOURS,
+        },
+    )
+    print(f"Created eval run {run.id}; polling for completion...")
+
+    # 3. Poll until terminal.
+    deadline = time.time() + POLL_TIMEOUT_SECS
+    terminal = {"completed", "failed", "canceled"}
+    while time.time() < deadline:
+        run = openai_client.evals.runs.retrieve(run_id=run.id, eval_id=eval_group.id)
+        if run.status in terminal:
+            break
+        print(f"  status={run.status} ...")
+        time.sleep(15)
+    else:
+        raise TimeoutError(f"Eval run did not finish within {POLL_TIMEOUT_SECS}s")
+
+    print(f"\nEval run finished: status={run.status}")
+    if run.status != "completed":
+        print(run)
+        return
+
+    # 4. Print per-criterion aggregate scores.
+    print("\nResult counts:")
+    print(f"  passed : {getattr(run.result_counts, 'passed', 'n/a')}")
+    print(f"  failed : {getattr(run.result_counts, 'failed', 'n/a')}")
+    print(f"  errored: {getattr(run.result_counts, 'errored', 'n/a')}")
+    print(f"  total  : {getattr(run.result_counts, 'total', 'n/a')}")
+
+    print("\nPer-criterion scores:")
+    for tc in getattr(run, "per_testing_criteria_results", []) or []:
+        name = getattr(tc, "testing_criteria", None) or getattr(tc, "name", "?")
+        passed = getattr(tc, "passed", "?")
+        failed = getattr(tc, "failed", "?")
+        print(f"  - {name}: passed={passed} failed={failed}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/samples/python/external-agents/observability/weather_agent.py b/samples/python/external-agents/observability/weather_agent.py
new file mode 100644
index 00000000..dcdc32a6
--- /dev/null
+++ b/samples/python/external-agents/observability/weather_agent.py
@@ -0,0 +1,130 @@
+"""Weather agent built with LangChain, instrumented with the Microsoft
+OpenTelemetry distro so its spans flow into Application Insights.
+
+This file is the runtime that lives *outside* Foundry (e.g. on Azure
+Container Apps, GCP Cloud Run, AWS, on-prem...). Foundry only stores a
+registration record (see ``register_external_agent.py``) and reads the
+spans this process emits.
+
+Reference for the LangChain + distro setup:
+https://github.com/microsoft/opentelemetry-distro-python/blob/main/samples/langchain/sample_langchain_instrumentation.py
+
+The Microsoft distro is configured with an explicit LangChain
+``agent_id`` so emitted spans line up with the Foundry external-agent
+registration.
+"""
+
+from __future__ import annotations
+
+import os
+from contextlib import asynccontextmanager
+
+# --- OTel: configure the Microsoft distro BEFORE importing anything that
+# should be instrumented at runtime. ----------------------------------------
+from microsoft.opentelemetry import use_microsoft_opentelemetry  # type: ignore
+
+AGENT_NAME = os.environ.get("AGENT_NAME", "weather-agent")
+# Emitted on every OTel span as gen_ai.agent.id.
+OTEL_AGENT_ID = os.environ.get("OTEL_AGENT_ID", AGENT_NAME)
+
+use_microsoft_opentelemetry(
+    enable_azure_monitor=True,
+    sampling_ratio=1.0,
+    instrumentation_options={
+        "fastapi": {"enabled": False},
+        "langchain": {
+            "enabled": True,
+            "agent_id": OTEL_AGENT_ID,
+            "agent_name": AGENT_NAME,
+        },
+    },
+)
+
+from fastapi import FastAPI
+from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_core.tools import tool
+from langchain_openai import AzureChatOpenAI
+from langgraph.prebuilt import create_react_agent
+from pydantic import BaseModel
+
+
+# --- Tools -----------------------------------------------------------------
+@tool
+def get_current_weather(city: str) -> str:
+    """Return the current weather for the given city.
+
+    This is a stub that returns deterministic fake data so the sample is
+    runnable without a third-party weather API key.
+    """
+    fake = {
+        "seattle": "59F and raining",
+        "new york": "72F and partly cloudy",
+        "tokyo": "68F and clear",
+        "london": "55F and overcast",
+    }
+    return fake.get(city.lower(), f"70F and sunny in {city}")
+
+
+@tool
+def get_forecast(city: str, days: int = 3) -> str:
+    """Return a short multi-day forecast for the given city."""
+    return f"{days}-day forecast for {city}: mild temperatures, occasional showers."
+
+
+# --- Agent -----------------------------------------------------------------
+def build_agent():
+    llm = AzureChatOpenAI(
+        azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
+        azure_deployment=os.environ["AZURE_OPENAI_DEPLOYMENT"],
+        api_version=os.environ.get("AZURE_OPENAI_API_VERSION", "2024-10-21"),
+        api_key=os.environ.get("AZURE_OPENAI_API_KEY"),
+        temperature=0,
+    )
+    return create_react_agent(
+        model=llm,
+        tools=[get_current_weather, get_forecast],
+        prompt=SystemMessage(
+            content=(
+                "You are a helpful weather assistant. Use the provided "
+                "tools to answer questions about current weather and "
+                "short-term forecasts. Be concise."
+            )
+        ),
+    )
+
+
+# --- HTTP surface ----------------------------------------------------------
+class AskRequest(BaseModel):
+    question: str
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    app.state.agent = build_agent()
+    yield
+
+
+app = FastAPI(title=AGENT_NAME, lifespan=lifespan)
+
+
+@app.get("/healthz")
+def healthz():
+    return {"status": "ok", "agent": AGENT_NAME}
+
+
+@app.post("/ask")
+def ask(req: AskRequest):
+    agent = app.state.agent
+    result = agent.invoke({"messages": [HumanMessage(content=req.question)]})
+    final = result["messages"][-1].content
+    return {"agent": AGENT_NAME, "answer": final}
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(
+        "weather_agent:app",
+        host="0.0.0.0",
+        port=int(os.environ.get("PORT", "8000")),
+    )