chore: update otel readme, plugin constructor

packages/aws-durable-execution-sdk-python-examples/src/otel/otel_logger_example.py

@@ -1,6 +1,6 @@
 """Demonstrates OTel-enriched logging in a durable execution.
 
-The DurableExecutionOtelPlugin installs a logging filter on the root logger
+The OtelPlugin installs a logging filter on the root logger
 (enrich_logger=True by default) when the plugin is constructed. The filter
 stamps the active OpenTelemetry trace context (otel_trace_id, otel_span_id,
 otel_trace_sampled) onto every log record that flows through the root handler.
@@ -16,10 +16,7 @@
 
 from typing import Any
 
-from aws_durable_execution_sdk_python_otel import DurableExecutionOtelPlugin
-from opentelemetry import trace
-from opentelemetry.sdk.trace import TracerProvider
-from opentelemetry.sdk.trace.export import BatchSpanProcessor, ConsoleSpanExporter
+from aws_durable_execution_sdk_python_otel import OtelPlugin
 
 from aws_durable_execution_sdk_python import StepContext
 from aws_durable_execution_sdk_python.context import (
@@ -30,10 +27,6 @@
 from aws_durable_execution_sdk_python.execution import durable_execution
 
 
-tracer_provider = trace.get_tracer_provider()
-otel = DurableExecutionOtelPlugin(tracer_provider)
-
-
 @durable_step
 def greet(step_context: StepContext, name: str) -> str:
     # Logged inside a step: enriched with this step's span_id.
@@ -51,7 +44,7 @@ def greet_in_child(child_context: DurableContext, name: str) -> str:
     return result
 
 
-@durable_execution(plugins=[otel])
+@durable_execution(plugins=[OtelPlugin()])
 def handler(_event: Any, context: DurableContext) -> str:
     # Logged at the top level: enriched with the invocation span_id.
     context.logger.info("Workflow started")

packages/aws-durable-execution-sdk-python-examples/src/plugin/execution_with_otel.py

@@ -2,24 +2,17 @@
 
 from typing import Any
 
-from opentelemetry import trace
+from aws_durable_execution_sdk_python_otel import OtelPlugin
 
 from aws_durable_execution_sdk_python import StepContext
-from aws_durable_execution_sdk_python.config import Duration, StepConfig, StepSemantics
+from aws_durable_execution_sdk_python.config import Duration
 from aws_durable_execution_sdk_python.context import (
     DurableContext,
     durable_step,
     durable_with_child_context,
 )
 from aws_durable_execution_sdk_python.execution import durable_execution
 
-from aws_durable_execution_sdk_python_otel import DurableExecutionOtelPlugin
-
-
-# use default provider
-tracer_provider = trace.get_tracer_provider()
-otel = DurableExecutionOtelPlugin(tracer_provider)
-
 
 @durable_step
 def add_numbers(_step_context: StepContext, a: int, b: int) -> int:
@@ -39,7 +32,7 @@ def add_numbers_in_child(child_context: DurableContext, a: int, b: int):
     return result
 
 
-@durable_execution(plugins=[otel])
+@durable_execution(plugins=[OtelPlugin()])
 def handler(_event: Any, context: DurableContext) -> int:
     result = 0
     for i in range(3):

packages/aws-durable-execution-sdk-python-otel/README.md

@@ -1,33 +1,284 @@
-# aws-durable-execution-sdk-python-otel
+# AWS Durable Execution SDK - OpenTelemetry Plugin
 
-OpenTelemetry instrumentation for the [AWS Durable Execution SDK for Python](https://github.com/aws/aws-durable-execution-sdk-python).
+OpenTelemetry instrumentation plugin for the [AWS Durable Execution SDK for Python](https://github.com/aws/aws-durable-execution-sdk-python). Emits distributed traces that correlate across multiple Lambda invocations of a single durable execution, producing deterministic span and trace IDs so that spans from different invocations are stitched into a single coherent trace.
 
-> **Note:** v0.1.0 reserves the package name. Instrumentation lands in v0.2.0.
+## Features
 
-## Overview
-
-This package will provide automatic OpenTelemetry tracing for durable execution workflows, giving you visibility into step execution, waits, retries, and overall workflow performance.
+- **Deterministic Trace IDs**: All invocations of the same durable execution share a single trace, derived from the X-Ray trace header or execution ARN
+- **Span-per-Operation**: Each durable operation (step, wait, invoke) gets its own span with accurate timing
+- **Continuation Spans**: Operations completing in a different invocation are linked back to the original span
+- **Log Correlation**: Enrich application logs with trace ID and span ID for end-to-end observability
+- **Configurable Sampling**: Control trace volume via plugin options
+- **Self-Contained Setup**: No manual TracerProvider configuration required
 
 ## Installation
 
 ```bash
 pip install aws-durable-execution-sdk-python-otel
 ```
 
-## Quick Start
+## Quick Start using X-Ray/CloudWatch Tracing
+
+1. Add the [ADOT Lambda Layer](#1-adot-lambda-layer) to your function and set `AWS_LAMBDA_EXEC_WRAPPER=/opt/otel-instrument`
+2. Enable [X-Ray Active Tracing](#2-aws-x-ray-active-tracing) on the function
+3. Pass `OtelPlugin` to your handler's `plugins` list
+4. Add X-Ray write permissions
+
+### 1. ADOT Lambda Layer
+
+This plugin requires the [AWS Distro for OpenTelemetry (ADOT) Lambda layer](https://aws-otel.github.io/docs/getting-started/lambda) to export traces from your Lambda function.
+
+The layer ARN follows the format:
+
+```
+arn:aws:lambda:<region>:<awsAccountId>:layer:aws-otel-python-<arch>-ver-<version>
+```
+
+Refer to the [ADOT Lambda Layer ARNs](https://aws-otel.github.io/docs/getting-started/lambda/lambda-python) page for the latest version number, architecture, and supported regions.
+
+**AWS CLI:**
+
+```bash
+aws lambda update-function-configuration \
+  --function-name your-function-name \
+  --layers "arn:aws:lambda:<region>:<awsAccountId>:layer:aws-otel-python-amd64-ver-<version>"
+```
+
+You must also set the `AWS_LAMBDA_EXEC_WRAPPER` environment variable:
+
+```bash
+aws lambda update-function-configuration \
+  --function-name your-function-name \
+  --environment "Variables={AWS_LAMBDA_EXEC_WRAPPER=/opt/otel-instrument}"
+```
+
+> **Note:** Replace `<region>` with your function's region and `<version>`/`<arch>` with the latest layer version and architecture from the ADOT docs.
+
+**CloudFormation / SAM:**
+
+```yaml
+MyFunction:
+  Type: AWS::Serverless::Function
+  Properties:
+    Layers:
+      - !Sub arn:aws:lambda:${AWS::Region}:<awsAccountId>:layer:aws-otel-python-amd64-ver-<version>
+    Environment:
+      Variables:
+        AWS_LAMBDA_EXEC_WRAPPER: /opt/otel-instrument
+```
+
+**CDK:**
 
 ```python
-from aws_durable_execution_sdk_python_otel import __version__
+from aws_cdk import aws_lambda as lambda_
+
+adot_layer = lambda_.LayerVersion.from_layer_version_arn(
+    self,
+    "AdotLayer",
+    f"arn:aws:lambda:<region>:<awsAccountId>:layer:aws-otel-python-amd64-ver-<version>",
+)
+
+fn = lambda_.Function(
+    self,
+    "MyFunction",
+    runtime=lambda_.Runtime.PYTHON_3_12,
+    handler="index.handler",
+    code=lambda_.Code.from_asset("lambda"),
+    layers=[adot_layer],
+    environment={"AWS_LAMBDA_EXEC_WRAPPER": "/opt/otel-instrument"},
+)
+```
+
+> **Tip:** Pin the layer version to a specific number in production deployments to avoid unexpected behavior from automatic version changes.
+
+### 2. AWS X-Ray Active Tracing
+
+Enable active tracing on your Lambda function so the `_X_AMZN_TRACE_ID` environment variable is populated at invocation time. The plugin uses this header to derive deterministic trace IDs that remain consistent across all invocations of the same durable execution.
+
+**AWS Console:** Lambda → Configuration → Monitoring and operations tools → Active tracing → Enable
+
+**AWS CLI:**
+
+```bash
+aws lambda update-function-configuration \
+  --function-name your-function-name \
+  --tracing-config Mode=Active
+```
+
+**CloudFormation / SAM:**
+
+```yaml
+MyFunction:
+  Type: AWS::Lambda::Function
+  Properties:
+    TracingConfig:
+      Mode: Active
+```
+
+**CDK:**
+
+```python
+lambda_.Function(
+    self,
+    "MyFunction",
+    tracing=lambda_.Tracing.ACTIVE,
+)
+```
+
+### 3. In your Lambda handler (index.py)
+
+```python
+from aws_durable_execution_sdk_python import DurableContext
+from aws_durable_execution_sdk_python.execution import durable_execution
+from aws_durable_execution_sdk_python_otel import OtelPlugin
+
+
+@durable_execution(plugins=[OtelPlugin()])
+def handler(event: dict, context: DurableContext) -> dict:
+    result = context.step(lambda _: fetch_data(event["id"]), name="fetch-data")
+
+    context.wait(duration=Duration.from_seconds(5))
+
+    context.step(lambda _: process(result), name="process")
 
-print(__version__)
+    return result
 ```
 
-## Planned Features (v0.2.0)
+That's it. The plugin handles TracerProvider setup, deterministic ID generation, and span lifecycle internally.
+
+### 4. Grant Permissions
+
+The function's execution role needs the `AWSXRayDaemonWriteAccess` managed policy (or equivalent permissions) if using X-Ray as the tracing backend.
+
+### Environment Variables for ADOT layer
+
+| Variable                      | Description                                                                                   | Default           |
+| ----------------------------- | --------------------------------------------------------------------------------------------- | ----------------- |
+| `OTEL_EXPORTER_OTLP_ENDPOINT` | Endpoint for the OTLP exporter (e.g., `http://localhost:4318` for the ADOT collector sidecar) | Set by ADOT layer |
+| `AWS_LAMBDA_EXEC_WRAPPER`     | Set to `/opt/otel-instrument` for the ADOT layer to instrument your function                  | —                 |
+| `OTEL_TRACES_SAMPLER`         | Sampler to use (e.g., `traceidratio` for ratio-based sampling)                                | `always_on`       |
+| `OTEL_TRACES_SAMPLER_ARG`     | Argument for the sampler (e.g., `0.3` to sample 30% of traces)                                | —                 |
+
+See the [ADOT sampling configuration](https://aws-otel.github.io/docs/getting-started/lambda#sampling-configuration) for more details.
+
+## Configuration
+
+### Plugin Options
+
+```python
+from aws_durable_execution_sdk_python_otel import (
+    OtelPlugin,
+    xray_context_extractor,
+)
+
+plugin = OtelPlugin(
+    # Provide your own TracerProvider if you already have one configured.
+    # Defaults to the globally configured tracer provider.
+    trace_provider=None,
+    # Use a custom context extractor (default: xray_context_extractor).
+    context_extractor=xray_context_extractor,
+    # Custom instrumentation scope name
+    # (default: "aws-durable-execution-sdk-python").
+    instrument_name="my-service",
+    # Install a root-logger filter that stamps trace context onto every
+    # log record (default: True).
+    enrich_logger=True,
+)
+```
+
+### Context Extractors
+
+The plugin supports multiple strategies for extracting upstream trace context:
+
+```python
+from aws_durable_execution_sdk_python_otel import (
+    OtelPlugin,
+    w3c_client_context_extractor,
+    xray_context_extractor,
+)
+
+# Default: X-Ray trace header (recommended for most Lambda deployments)
+OtelPlugin(context_extractor=xray_context_extractor)
+
+# W3C Trace Context via clientContext (requires backend propagation support)
+OtelPlugin(context_extractor=w3c_client_context_extractor)
+```
+
+### Log Correlation
+
+When `enrich_logger=True` (the default), the plugin installs a logging filter on
+the root logger at invocation start. The filter stamps the active OTel trace
+context onto every emitted log record using these attributes:
+
+- `otel_trace_id`: 32-char hex trace identifier
+- `otel_span_id`: 16-char hex span identifier
+- `otel_trace_sampled`: boolean indicating if the trace is sampled
+
+These attributes are only set when a valid span context is active, so any log
+formatter or schema must treat the fields as optional.
+
+## Verification
+
+After deploying your function with the plugin configured:
+
+1. **Invoke your durable function** — trigger at least one execution that includes multiple steps or a wait/resume cycle.
+
+2. **Check the CloudWatch console** — Navigate to CloudWatch → Traces in the AWS Console. You should see a trace with:
+   - An "invocation" span per invocation
+   - Child spans for each durable operation (named after your step names)
+   - All invocations of the same execution grouped under one trace ID
+
+3. **Check log correlation** — verify that your logs include `otel_trace_id` and `otel_span_id` fields matching the spans in X-Ray.
+
+4. **Confirm sampling** — If you set `OTEL_TRACES_SAMPLER=traceidratio` and `OTEL_TRACES_SAMPLER_ARG` to a value less than 1.0, verify that only the expected proportion of traces appear.
+
+5. **Span links** — For operations that span multiple invocations (e.g., after a wait resumes), though span links are set, they are not visualized within the CloudWatch console.
+
+### Troubleshooting
+
+| Symptom                           | Likely Cause                                                    |
+| --------------------------------- | --------------------------------------------------------------- |
+| No traces appear                  | ADOT layer not configured, or `AWS_LAMBDA_EXEC_WRAPPER` not set |
+| Traces appear but are fragmented  | X-Ray active tracing not enabled on the Lambda function         |
+| Missing spans for some operations | `OTEL_TRACES_SAMPLER_ARG` set below 1.0                         |
+| `_X_AMZN_TRACE_ID` not populated  | X-Ray active tracing not enabled                                |
+
+## API Reference
+
+### `OtelPlugin`
+
+The main plugin class. Implements `DurableInstrumentationPlugin` from `aws_durable_execution_sdk_python`.
+
+```python
+OtelPlugin(
+    trace_provider=None,
+    context_extractor=None,
+    instrument_name="aws-durable-execution-sdk-python",
+    enrich_logger=True,
+)
+```
+
+### `DeterministicIdGenerator`
+
+A custom OpenTelemetry `IdGenerator` that produces reproducible trace and span IDs from execution metadata. Exported for advanced use cases.
+
+### `xray_context_extractor`
+
+Default context extractor. Reads the `_X_AMZN_TRACE_ID` environment variable to derive trace context.
+
+### `w3c_client_context_extractor`
+
+Alternative context extractor. Reads W3C `traceparent` from `context.clientContext.custom.traceparent`. Requires backend `clientContext` propagation to be enabled.
+
+### `ContextExtractor`
+
+Type alias for custom context extractor functions.
+
+### `OtelContextLogFilter` / `install_log_filter`
 
-- Automatic span creation for steps, waits, invokes, and child contexts
-- Replay-aware tracing (distinguishes fresh executions from replays)
-- Error recording with proper OTel status codes
-- Configurable span attributes and naming
+The logging filter (and its installer) used to stamp trace context onto log
+records. Installed automatically when `enrich_logger=True`; exported for manual
+setups.
 
 ## Requirements
 

packages/aws-durable-execution-sdk-python-otel/src/aws_durable_execution_sdk_python_otel/__init__.py

@@ -14,16 +14,16 @@
     install_log_filter,
 )
 from aws_durable_execution_sdk_python_otel.plugin import (
-    DurableExecutionOtelPlugin,
+    OtelPlugin,
 )
 
 
 __all__ = [
     "__version__",
     "ContextExtractor",
     "DeterministicIdGenerator",
-    "DurableExecutionOtelPlugin",
     "OtelContextLogFilter",
+    "OtelPlugin",
     "install_log_filter",
     "w3c_client_context_extractor",
     "xray_context_extractor",