opentelemetry-instrumentation-sagemaker
OpenTelemetry SageMaker instrumentation
Decision gist · record as of 2026-08-14
Yes, if you are invoking SageMaker endpoints via Boto3 and need observability. The package is actively maintained, has no known vulnerabilities, installs cleanly, and integrates directly into OpenTelemetry. The privacy control via TRACELOOP_TRACE_CONTENT is a practical feature for sensitive workloads. Install it as part of your observability setup.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; requires an active OpenTelemetry trace provider to be configured separately.
- Low friction install with a pure-Python wheel.
- Actively maintained as of 2026-08-10 with recent releases, and depends only on core OpenTelemetry packages.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions.
last release 2026-08-10 (4 days) · last repo commit 2026-08-10 · 7,377 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 6,795,401 downloads/mo, #1,847 on PyPI
Alternatives
Verify before relying
pip install opentelemetry-instrumentation-sagemaker
from opentelemetry.instrumentation.sagemaker import SageMakerInstrumentor
SageMakerInstrumentor().instrument()- Whether the instrumentation works with all SageMaker endpoint types or only specific model types.
- Performance overhead of tracing on high-volume endpoint invocations.
- Compatibility with non-Boto3 SageMaker clients or SDKs.
What it is and what it does
This package is an OpenTelemetry instrumentation plugin that automatically intercepts and traces calls to Amazon SageMaker endpoints made through Boto3. When activated, it wraps SageMaker API calls and records them as spans, capturing request bodies and response data by default to give visibility into model invocations and help debug LLM application behavior.
The instrumentation is designed for developers building observability into applications that invoke SageMaker models. It integrates with the OpenTelemetry ecosystem, requiring opentelemetry-api, opentelemetry-instrumentation, and semantic convention packages. By default it logs endpoint request and response content to span attributes; this can be disabled via the TRACELOOP_TRACE_CONTENT environment variable if privacy or trace size is a concern.
Use it for
- Debug LLM application behavior by tracing what data is sent to and returned from SageMaker endpoints.
- Monitor SageMaker endpoint performance and latency in production observability systems.
- Evaluate output quality by capturing model responses in traces for later analysis.
- Reduce trace size in high-volume scenarios by disabling request/response body logging.
- Integrate SageMaker calls into a broader OpenTelemetry tracing pipeline across your application.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are invoking SageMaker endpoints via Boto3 and need observability.
The package is actively maintained, has no known vulnerabilities, installs cleanly, and integrates directly into OpenTelemetry. The privacy control via TRACELOOP_TRACE_CONTENT is a practical feature for sensitive workloads. Install it as part of your observability setup.
Install
opentelemetry-instrumentation-sagemaker on PyPI
Before you install
Low friction install with a pure-Python wheel. Actively maintained as of 2026-08-10 with recent releases, and depends only on core OpenTelemetry packages.
Requires Python 3.10 or later; requires an active OpenTelemetry trace provider to be configured separately.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions.
Quickstart
pip install opentelemetry-instrumentation-sagemaker
from opentelemetry.instrumentation.sagemaker import SageMakerInstrumentor
SageMakerInstrumentor().instrument()Verify before relying
- Whether the instrumentation works with all SageMaker endpoint types or only specific model types.
- Performance overhead of tracing on high-volume endpoint invocations.
- Compatibility with non-Boto3 SageMaker clients or SDKs.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <4,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesopentelemetry-apiopentelemetry-instrumentationopentelemetry-semantic-conventions-aiopentelemetry-semantic-conventions |
| Maintenance | Actively maintained 4 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 6,795,401 / month, #1,847 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: opentelemetry_instrumentation_sagemaker-0.62.3-py3-none-any.whl
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See also opentelemetry-instrumentation-mistralai · opentelemetry-instrumentation-bedrock · opentelemetry-instrumentation-groq · opentelemetry-instrumentation-openai · opentelemetry-instrumentation-writer · opentelemetry-instrumentation-boto · opentelemetry-instrumentation-watsonx · model-hosting-container-standards · opentelemetry-instrumentation-replicate · opentelemetry-instrumentation-agno