Merge pull request #42 from ks6088ts-labs/feature/issue-37_otel

add environment variables for Otel

Author: ks6088ts

.env.template

@@ -1,3 +1,9 @@
+# Azure Application Insights
+APPLICATIONINSIGHTS_CONNECTION_STRING="InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/;LiveEndpoint=https://xxx.livediagnostics.monitor.azure.com/;ApplicationId=xxx"
+OTEL_RESOURCE_ATTRIBUTES="service.namespace=local-template-fastapi-namespace,service.instance.id=local-template-fastapi-instance"
+OTEL_SERVICE_NAME="local-template-fastapi-service"
+OTEL_TRACES_SAMPLER_ARG="1"
+
 # Azure OpenAI Service
 AZURE_OPENAI_ENDPOINT="https://<YOUR_AOAI_NAME>.openai.azure.com/"
 AZURE_OPENAI_API_KEY="<YOUR_API_KEY>"

docs/index.md

@@ -31,6 +31,21 @@ make dev
 
 The application will be available at http://localhost:8000 with interactive API documentation at http://localhost:8000/docs.
 
+### Docker Setup
+
+See [ks6088ts/template-fastapi](https://hub.docker.com/r/ks6088ts/template-fastapi) for Docker images.
+
+```shell
+# Configure environment
+cp .env.template .env
+# Edit .env with your Azure service credentials
+
+# Run Docker container
+docker run --rm -p 8000:8000 \
+  --volume "$PWD/.env:/app/.env" \
+  ks6088ts/template-fastapi:latest
+```
+
 ## Architecture Overview
 
 For detailed architecture information, see:

template_fastapi/app.py

@@ -38,7 +38,7 @@ def server_request_hook(span: Span, scope: dict):
 
     configure_azure_monitor(
         connection_string=AZURE_CONNECTION_STRING,
-        # enable_live_metrics=True,
+        enable_live_metrics=True,
         server_request_hook=server_request_hook,
     )
     FastAPIInstrumentor.instrument_app(app)

template_fastapi/routers/demos.py

@@ -1,5 +1,5 @@
+import asyncio
 import random
-import time
 
 from fastapi import APIRouter, HTTPException
 
@@ -73,10 +73,9 @@ async def heavy_sync_with_sleep(sleep_ms: int):
 
     with tracer.start_as_current_span("parent"):
         logger.debug(f"Starting sleep for {sleep_ms} milliseconds")
-        time.sleep(sleep_ms / 1000.0)
+        await asyncio.sleep(sleep_ms / 1000.0)  # Convert milliseconds to seconds
         with tracer.start_as_current_span("child"):
             logger.debug("Child span execution")
-
     logger.info(f"Completed sleep operation for {sleep_ms}ms")
     return {
         "message": f"Slept for {sleep_ms} milliseconds",