azure-monitor-opentelemetry-exporter-py
microsoft/skills
使用 Python 将 OpenTelemetry 跟踪、指标和日志导出到 Azure Application Insights。
...展开全部Azure Monitor OpenTelemetry Python 导出器
用于将 OpenTelemetry 跟踪、指标和日志发送到 Application Insights 的低级导出器。
安装
pip install azure-monitor-opentelemetry-exporter
环境变量
APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/ # 所有身份验证方法必需
AZURE_TOKEN_CREDENTIALS=prod # 仅在生产环境中使用 DefaultAzureCredential 时必需
🔑 身份验证与生命周期: 这些导出器在设计上接受连接字符串,但对于 AAD 身份验证的 ingestion(在支持的场景中),建议通过
credential=参数使用DefaultAzureCredential— 请参阅 Azure AD 身份验证部分。您与导出器一起创建的任何 Azure SDK 客户端都应包装在with/async with块中(来自azure.identity.aio的异步凭据也是如此)。
使用场景
| 场景 | 使用 |
|---|---|
| 快速设置,自动仪器化 | `azure-monitor-opentelemetry` (发行版) |
| 自定义 OpenTelemetry 管道 | `azure-monitor-opentelemetry-exporter` (本库) |
| 对遥测数据进行细粒度控制 | `azure-monitor-opentelemetry-exporter` (本库) |
跟踪导出器
from azure.identity import DefaultAzureCredential
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# 从环境变量读取 APPLICATIONINSIGHTS_CONNECTION_STRING 以标识资源;
# DefaultAzureCredential 通过 Microsoft Entra ID 对 ingestion 进行身份验证。
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
)
# 配置跟踪器提供程序
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(
BatchSpanProcessor(exporter)
)
# 使用跟踪器
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("my-span"):
print("Hello, World!")
指标导出器
from azure.identity import DefaultAzureCredential
from opentelemetry import metrics
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
# 从环境变量读取 APPLICATIONINSIGHTS_CONNECTION_STRING;通过 DefaultAzureCredential 进行 AAD 身份验证的 ingestion。
exporter = AzureMonitorMetricExporter(
credential=DefaultAzureCredential(),
)
# 配置度量提供程序
reader = PeriodicExportingMetricReader(exporter, export_interval_millis=60000)
metrics.set_meter_provider(MeterProvider(metric_readers=[reader]))
# 使用度量器
meter = metrics.get_meter(__name__)
counter = meter.create_counter("requests_total")
counter.add(1, {"route": "/api/users"})
日志导出器
import logging
from azure.identity import DefaultAzureCredential
from opentelemetry._logs import set_logger_provider
from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler
from opentelemetry.sdk._logs.export import BatchLogRecordProcessor
from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
# 从环境变量读取 APPLICATIONINSIGHTS_CONNECTION_STRING;通过 DefaultAzureCredential 进行 AAD 身份验证的 ingestion。
exporter = AzureMonitorLogExporter(
credential=DefaultAzureCredential(),
)
# 配置日志提供程序
logger_provider = LoggerProvider()
logger_provider.add_log_record_processor(BatchLogRecordProcessor(exporter))
set_logger_provider(logger_provider)
# 添加到 Python 日志处理程序
handler = LoggingHandler(level=logging.INFO, logger_provider=logger_provider)
logging.getLogger().addHandler(handler)
# 使用日志记录
logger = logging.getLogger(__name__)
logger.info("This will be sent to Application Insights")
从环境变量
导出器自动读取 APPLICATIONINSIGHTS_CONNECTION_STRING:
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# 来自环境的连接字符串;通过 DefaultAzureCredential 进行 AAD 身份验证的 ingestion。
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
)
Azure AD 身份验证
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# 本地开发:DefaultAzureCredential。生产环境:设置 AZURE_TOKEN_CREDENTIALS=prod 或 AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# 或者在生产环境中直接使用特定的凭据:
# 请参阅 https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
exporter = AzureMonitorTraceExporter(
credential=credential
)
</specific_credential>采样
使用 ApplicationInsightsSampler 进行一致的采样:
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.sampling import ParentBasedTraceIdRatio
from azure.monitor.opentelemetry.exporter import ApplicationInsightsSampler
# 采样 10% 的跟踪
sampler = ApplicationInsightsSampler(sampling_ratio=0.1)
trace.set_tracer_provider(TracerProvider(sampler=sampler))
离线存储
配置用于重试的离线存储:
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
storage_directory="/path/to/storage", # 自定义存储路径
disable_offline_storage=False # 启用重试(默认)
)
禁用离线存储
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
disable_offline_storage=True # 失败时不重试
)
主权云
from azure.identity import AzureAuthorityHosts, DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Azure Government
credential = DefaultAzureCredential(authority=AzureAuthorityHosts.AZURE_GOVERNMENT)
exporter = AzureMonitorTraceExporter(
connection_string="InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.us/",
credential=credential
)
导出器类型
| 导出器 | 遥测类型 | Application Insights 表 |
|---|---|---|
| `AzureMonitorTraceExporter` | 跟踪/跨度 | requests, dependencies, exceptions |
| `AzureMonitorMetricExporter` | 指标 | customMetrics, performanceCounters |
| `AzureMonitorLogExporter` | 日志 | traces, customEvents |
配置选项
| 参数 | 描述 | 默认值 |
|---|---|---|
| `connection_string` | Application Insights 连接字符串 | 来自环境变量 |
| `credential` | 用于 AAD 身份验证的 Azure 凭据 | None |
| `disable_offline_storage` | 禁用重试存储 | False |
| `storage_directory` | 自定义存储路径 | 临时目录 |
最佳实践
- 选择同步或异步并保持一致。 不要在同一调用路径中混合使用
azure.xxx同步客户端和azure.xxx.aio异步客户端。每个模块选择一种模式。 - 在进程退出时刷新并关闭提供程序。 在进程退出时调用 shutdown/flush API(例如
tracer_provider.shutdown()、meter_provider.shutdown()、logger_provider.shutdown()),以便在进程终止前刷新遥测数据。 - 生产环境中使用 BatchSpanProcessor(而非 SimpleSpanProcessor)
- 使用 ApplicationInsightsSampler 以实现跨服务的一致性采样
- 启用离线存储 以提高生产环境的可靠性
- 使用 Microsoft Entra 身份验证 替代仪器化密钥
- 设置适合您工作负载的导出间隔
- 除非需要自定义管道,否则使用发行版 (
azure-monitor-opentelemetry)
---
name: azure-monitor-opentelemetry-exporter-py
description: Export OpenTelemetry traces, metrics, and logs to Azure Application Insights using Python.
license: MIT
---
# Azure Monitor OpenTelemetry Exporter for Python
Low-level exporter for sending OpenTelemetry traces, metrics, and logs to Application Insights.
## Installation
```bash
pip install azure-monitor-opentelemetry-exporter
```
## Environment Variables
```bash
APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/ # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
```
> **🔑 Auth & lifecycle:** These exporters take a connection string by design, but for *AAD-authenticated ingestion* (where supported) prefer `DefaultAzureCredential` via the `credential=` parameter — see the [Azure AD Authentication](#azure-ad-authentication) section. Any Azure SDK clients you create alongside the exporter should be wrapped in `with`/`async with` blocks (and async credentials from `azure.identity.aio` likewise).
## When to Use
| Scenario | Use |
|----------|-----|
| Quick setup, auto-instrumentation | `azure-monitor-opentelemetry` (distro) |
| Custom OpenTelemetry pipeline | `azure-monitor-opentelemetry-exporter` (this) |
| Fine-grained control over telemetry | `azure-monitor-opentelemetry-exporter` (this) |
## Trace Exporter
```python
from azure.identity import DefaultAzureCredential
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Reads APPLICATIONINSIGHTS_CONNECTION_STRING from env to identify the resource;
# DefaultAzureCredential authenticates ingestion via Microsoft Entra ID.
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
)
# Configure tracer provider
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(
BatchSpanProcessor(exporter)
)
# Use tracer
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("my-span"):
print("Hello, World!")
```
## Metric Exporter
```python
from azure.identity import DefaultAzureCredential
from opentelemetry import metrics
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
# Reads APPLICATIONINSIGHTS_CONNECTION_STRING from env; AAD-authenticated ingestion via DefaultAzureCredential.
exporter = AzureMonitorMetricExporter(
credential=DefaultAzureCredential(),
)
# Configure meter provider
reader = PeriodicExportingMetricReader(exporter, export_interval_millis=60000)
metrics.set_meter_provider(MeterProvider(metric_readers=[reader]))
# Use meter
meter = metrics.get_meter(__name__)
counter = meter.create_counter("requests_total")
counter.add(1, {"route": "/api/users"})
```
## Log Exporter
```python
import logging
from azure.identity import DefaultAzureCredential
from opentelemetry._logs import set_logger_provider
from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler
from opentelemetry.sdk._logs.export import BatchLogRecordProcessor
from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
# Reads APPLICATIONINSIGHTS_CONNECTION_STRING from env; AAD-authenticated ingestion via DefaultAzureCredential.
exporter = AzureMonitorLogExporter(
credential=DefaultAzureCredential(),
)
# Configure logger provider
logger_provider = LoggerProvider()
logger_provider.add_log_record_processor(BatchLogRecordProcessor(exporter))
set_logger_provider(logger_provider)
# Add handler to Python logging
handler = LoggingHandler(level=logging.INFO, logger_provider=logger_provider)
logging.getLogger().addHandler(handler)
# Use logging
logger = logging.getLogger(__name__)
logger.info("This will be sent to Application Insights")
```
## From Environment Variable
Exporters read `APPLICATIONINSIGHTS_CONNECTION_STRING` automatically:
```python
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Connection string from environment; AAD-authenticated ingestion via DefaultAzureCredential.
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
)
```
## Azure AD Authentication
```python
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()
exporter = AzureMonitorTraceExporter(
credential=credential
)
```
## Sampling
Use `ApplicationInsightsSampler` for consistent sampling:
```python
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.sampling import ParentBasedTraceIdRatio
from azure.monitor.opentelemetry.exporter import ApplicationInsightsSampler
# Sample 10% of traces
sampler = ApplicationInsightsSampler(sampling_ratio=0.1)
trace.set_tracer_provider(TracerProvider(sampler=sampler))
```
## Offline Storage
Configure offline storage for retry:
```python
from azure.identity import DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
storage_directory="/path/to/storage", # Custom storage path
disable_offline_storage=False # Enable retry (default)
)
```
## Disable Offline Storage
```python
exporter = AzureMonitorTraceExporter(
credential=DefaultAzureCredential(),
disable_offline_storage=True # No retry on failure
)
```
## Sovereign Clouds
```python
from azure.identity import AzureAuthorityHosts, DefaultAzureCredential
from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
# Azure Government
credential = DefaultAzureCredential(authority=AzureAuthorityHosts.AZURE_GOVERNMENT)
exporter = AzureMonitorTraceExporter(
connection_string="InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.us/",
credential=credential
)
```
## Exporter Types
| Exporter | Telemetry Type | Application Insights Table |
|----------|---------------|---------------------------|
| `AzureMonitorTraceExporter` | Traces/Spans | requests, dependencies, exceptions |
| `AzureMonitorMetricExporter` | Metrics | customMetrics, performanceCounters |
| `AzureMonitorLogExporter` | Logs | traces, customEvents |
## Configuration Options
| Parameter | Description | Default |
|-----------|-------------|---------|
| `connection_string` | Application Insights connection string | From env var |
| `credential` | Azure credential for AAD auth | None |
| `disable_offline_storage` | Disable retry storage | False |
| `storage_directory` | Custom storage path | Temp directory |
## Best Practices
1. **Pick sync OR async and stay consistent.** Do not mix `azure.xxx` sync clients with `azure.xxx.aio` async clients in the same call path. Choose one mode per module.
2. **Flush and shut down providers at process exit.** Call the shutdown/flush APIs (e.g. `tracer_provider.shutdown()`, `meter_provider.shutdown()`, `logger_provider.shutdown()`) at process exit to flush telemetry before the process terminates.
3. **Use BatchSpanProcessor** for production (not SimpleSpanProcessor)
4. **Use ApplicationInsightsSampler** for consistent sampling across services
5. **Enable offline storage** for reliability in production
6. **Use Microsoft Entra authentication** instead of instrumentation keys
7. **Set export intervals** appropriate for your workload
8. **Use the distro** (`azure-monitor-opentelemetry`) unless you need custom pipelines
所有文件
0 个文件安装 azure-monitor-opentelemetry-exporter-py
将技能文件下载并解压至你的 .claude/skills/ 目录。
下载ZIP克隆仓库并复制技能文件到您的项目中。
git clone https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-monitor-opentelemetry-exporter-py # Copy SKILL.md to your .claude/skills/ directory
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