--- id: openinference-instrumentation-bedrock version: "0.1.45" license: Apache-2.0 license_treatment: permissive maintenance: active --- # openinference-instrumentation-bedrock — OpenInference Bedrock Instrumentation License: permissive · Maintenance: active · Downloads: 233.9K/mo ## What it is and what it does This package automatically captures traces from AWS Bedrock API calls made through boto3 (sync) and aioboto3 (async), converting them into OpenTelemetry spans that conform to the OpenInference specification. It wraps the bedrock-runtime and bedrock-agent-runtime clients to intercept invoke_model, converse, and invoke_agent calls, extracting request and response details without requiring manual instrumentation code. The traces are exported to any OpenTelemetry-compatible backend where they can be visualized and analyzed. It supports a range of Bedrock models including Anthropic Claude variants, Meta Llama, Amazon Nova, and Mistral models, with different APIs (invoke_model vs. converse) supported depending on the model. The package requires Python 3.10 or later and depends on opentelemetry-api, opentelemetry-instrumentation, opentelemetry-semantic-conventions, dacite, wrapt, and typing-extensions. Use it for: - Debug and trace LLM calls to Bedrock models by viewing request/response details in observability backends. - Monitor latency and error rates of Bedrock API calls across your application using OpenTelemetry exporters. - Instrument async Bedrock workloads built with aioboto3 to correlate LLM calls with application traces. - Analyze multi-turn conversations with Bedrock's converse API to understand model behavior. - Integrate Bedrock observability into existing OpenTelemetry pipelines without modifying application code. ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. Automatically instruments AWS Bedrock API calls (invoke_model, converse, invoke_agent) made via boto3 and aioboto3 to emit OpenTelemetry traces for observability and debugging. Yes. The package is actively maintained (release 7 days ago), has no known vulnerabilities, carries a permissive Apache-2.0 license, and solves a real observability gap for Bedrock users. Install friction is low, and it integrates cleanly into existing OpenTelemetry setups. Suitable for production use if you need to trace Bedrock calls. ## Install pip install openinference-instrumentation-bedrock uv add openinference-instrumentation-bedrock poetry add openinference-instrumentation-bedrock ## Installing openinference-instrumentation-bedrock Before you install: Low friction: pure Python wheel with 8 runtime dependencies including opentelemetry-api, opentelemetry-instrumentation, and wrapt. Actively maintained with a release 7 days ago; repo shows 1147 stars and recent activity. License in practice: Apache-2.0 permissive license allows use in commercial and private projects with minimal restrictions; attribution required. Quickstart: pip install openinference-instrumentation-bedrock from openinference.instrumentation.bedrock import BedrockInstrumentor from opentelemetry import trace as trace_api BedrockInstrumentor().instrument() Requires botocore v1.34.116 or above for converse API support; AWS credentials must be configured separately. Verify before relying: - Whether all listed Bedrock models are equally well-tested or if some remain experimental. - Performance overhead of instrumentation on high-throughput workloads. - Compatibility with custom OpenTelemetry exporters beyond those shown in examples. ## Package facts - License: Apache-2.0 (permissive) - Python support: supports_current - Install friction: low - Maintenance: active - Downloads: 233.9K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags bedrock tracing instrumentation, aws bedrock opentelemetry, llm call tracing aws, bedrock api monitoring, openinference bedrock, aioboto3 instrumentation, bedrock observability, aws-bedrock, opentelemetry, llm-observability [View on SkillFed](https://skillfed.io/packages/openinference-instrumentation-bedrock) · [View on PyPI](https://pypi.org/project/openinference-instrumentation-bedrock/)