Merge pull request #8 from ks6088ts-labs/feature/issue-7_application-insights

support application insights

Author: ks6088ts

docs/index.md

@@ -15,3 +15,11 @@
 - [FastAPI で作成した API エンドポイントをモデル コンテキスト プロトコル (MCP) ツールとして公開してみる](https://dev.classmethod.jp/articles/fastapi-api-mcp/)
 - [MCP Inspector > docs](https://modelcontextprotocol.io/docs/tools/inspector)
 - [MCP Inspector > codes](https://github.com/modelcontextprotocol/inspector)
+
+## Application Insights
+
+- [Application Insights の概要 - OpenTelemetry の可観測性](https://learn.microsoft.com/ja-jp/azure/azure-monitor/app/app-insights-overview)
+- [open-telemetry/opentelemetry-python > Basic Trace](https://github.com/open-telemetry/opentelemetry-python/tree/main/docs/examples/basic_tracer)
+- [FastAPI のテレメトリデータを Azure Application Insights に送る](https://qiita.com/hoto17296/items/2f366dfabdbe3d1d4e97)
+- [【Azure Functions】 - Application Insights のログが表示されない問題](https://zenn.dev/headwaters/articles/ff19f7e1b99b44)
+- [opentelemetry-instrumentation-fastapi (python) から OpenTelemetry に入門する](https://zenn.dev/taxin/articles/opentelemetry-fast-api-instrumentation-basics)

local.settings.json

@@ -1,6 +1,7 @@
 {
   "IsEncrypted": false,
   "Values": {
+    "APPLICATIONINSIGHTS_CONNECTION_STRING": "InstrumentationKey=YOUR_INSTRUMENTATION_KEY;IngestionEndpoint=https://japaneast-1.in.applicationinsights.azure.com/;LiveEndpoint=https://japaneast.livediagnostics.monitor.azure.com/;ApplicationId=YOUR_APPLICATION_ID",
     "FUNCTIONS_WORKER_RUNTIME": "python",
     "AzureWebJobsFeatureFlags": "EnableWorkerIndexing",
     "AzureWebJobsStorage": ""

pyproject.toml

@@ -6,8 +6,10 @@ readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
     "azure-functions>=1.23.0",
+    "azure-monitor-opentelemetry>=1.6.10",
     "fastapi-mcp>=0.3.4",
     "fastapi[standard]>=0.115.12",
+    "opentelemetry-instrumentation-fastapi>=0.52b1",
 ]
 
 [project.optional-dependencies]
@@ -52,3 +54,7 @@ show_missing = true
 
 [tool.ty]
 environment = { python-version = "3.10" }
+
+[tool.ty.rules]
+unresolved-attribute = "ignore" # Ignore unresolved attributes in classes
+possibly-unbound-attribute = "ignore" # Ignore possibly unbound attributes in classes

template_fastapi/app.py

@@ -3,11 +3,47 @@
 ref. https://github.com/tadata-org/fastapi_mcp/blob/v0.3.4/examples/shared/apps/items.py
 """
 
+import random
+import uuid
+from os import getenv
+
+from azure.monitor.opentelemetry import configure_azure_monitor
 from fastapi import FastAPI, HTTPException, Query
+from opentelemetry import trace
+from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor
+from opentelemetry.sdk.trace import TracerProvider
+from opentelemetry.sdk.trace.export import (
+    BatchSpanProcessor,
+    ConsoleSpanExporter,
+)
+from opentelemetry.trace import Span
 from pydantic import BaseModel
 
+trace.set_tracer_provider(TracerProvider())
+trace.get_tracer_provider().add_span_processor(BatchSpanProcessor(ConsoleSpanExporter()))
+tracer = trace.get_tracer(__name__)
+
 app = FastAPI()
 
+# If APPLICATIONINSIGHTS_CONNECTION_STRING exists, configure Azure Monitor
+AZURE_CONNECTION_STRING = getenv("APPLICATIONINSIGHTS_CONNECTION_STRING")
+if AZURE_CONNECTION_STRING:
+
+    def server_request_hook(span: Span, scope: dict):
+        if span and span.is_recording():
+            try:
+                # Application Insights に送るデータにユーザ ID を追加する
+                user_id = uuid.uuid4().hex  # Replace with actual user ID retrieval logic
+                span.set_attribute("enduser.id", user_id)
+            except KeyError:
+                pass
+
+    configure_azure_monitor(
+        connection_string=AZURE_CONNECTION_STRING,
+        server_request_hook=server_request_hook,
+    )
+    FastAPIInstrumentor.instrument_app(app)
+
 
 class Item(BaseModel):
     id: int
@@ -124,3 +160,64 @@ async def search_items(
 ]
 for item in sample_items:
     items_db[item.id] = item
+
+
+# Add flaky API which receives percentage of failure
+@app.get("/flaky/{failure_rate}", tags=["flaky"], operation_id="flaky")
+async def flaky(failure_rate: int):
+    """
+    A flaky endpoint that simulates a failure based on the provided failure rate.
+
+    The failure rate is a percentage (0-100) that determines the likelihood of failure.
+    """
+    if not (0 <= failure_rate <= 100):
+        raise HTTPException(
+            status_code=400,
+            detail="Failure rate must be between 0 and 100",
+        )
+
+    if random.randint(0, 100) < failure_rate:
+        raise HTTPException(
+            status_code=500,
+            detail="Simulated failure",
+        )
+
+    return {
+        "message": "Request succeeded",
+    }
+
+
+# Add flaky API which raises an exception
+@app.get("/flaky/exception", tags=["flaky"], operation_id="flaky_exception")
+async def flaky_exception():
+    """
+    A flaky endpoint that always raises an exception.
+    """
+    raise HTTPException(
+        status_code=500,
+        detail="Simulated exception",
+    )
+
+
+# Add a heavy synchronous endpoint which receives milliseconds to sleep
+@app.get("/heavy_sync/{sleep_ms}", tags=["heavy"], operation_id="heavy_sync_with_sleep")
+async def heavy_sync_with_sleep(sleep_ms: int):
+    """
+    A heavy synchronous endpoint that sleeps for the specified number of milliseconds.
+
+    This simulates a long-running synchronous operation.
+    """
+    if sleep_ms < 0:
+        raise HTTPException(
+            status_code=400,
+            detail="Sleep time must be a non-negative integer",
+        )
+
+    import time
+
+    with tracer.start_as_current_span("foo"):
+        print(f"Sleeping for {sleep_ms} milliseconds")
+        time.sleep(sleep_ms / 1000.0)
+    return {
+        "message": f"Slept for {sleep_ms} milliseconds",
+    }