---
title: "Amazon Bedrock"
description: "Learn about using Sentry for Amazon Bedrock."
url: https://docs.sentry.io/platforms/python/agent-tracing/bedrock/
---

# Amazon Bedrock for Python

This integration connects Sentry with [Amazon Bedrock](https://aws.amazon.com/bedrock/) calls made through the [Boto3](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html) `bedrock-runtime` client.

Once you've installed this SDK, you can use the Sentry Agents Tracing, a Sentry dashboard that helps you understand what's going on with your AI requests.

Sentry AI Observability will automatically collect information about prompts, tools, tokens, and models. Learn more about the [Agents Dashboard](https://docs.sentry.io/product/agents/dashboards.md).

If you're using stream mode, this page's references to "transaction" should be applied to service spans instead. See [Streamed Spans](https://docs.sentry.io/platforms/python/tracing/streamed-spans.md) for more information.

## [Install](https://docs.sentry.io/platforms/python/agent-tracing/bedrock.md#install)

Install `sentry-sdk` from PyPI:

```bash
pip install sentry-sdk
```

*Other available variations of the above snippet: uv*

## [Configure](https://docs.sentry.io/platforms/python/agent-tracing/bedrock.md#configure)

Add `Boto3Integration()` to your `integrations` list:

```python
import sentry_sdk
from sentry_sdk.integrations.boto3 import Boto3Integration

sentry_sdk.init(
    dsn="https://<key>@o<orgId>.ingest.sentry.io/<projectId>",
    # Set traces_sample_rate to 1.0 to capture 100%
    # of transactions for tracing.
    traces_sample_rate=1.0,
    # Check https://docs.sentry.io/platforms/python/data-management/data-collected/ to configure what data is collected
    data_collection={
        "gen_ai": {"inputs": True, "outputs": True},
    },
    integrations=[
        Boto3Integration(),
    ],
)
```

## [Verify](https://docs.sentry.io/platforms/python/agent-tracing/bedrock.md#verify)

Verify that the integration works by making a chat request to Bedrock.

```python
import boto3
import sentry_sdk

sentry_sdk.init(...)  # same as above

client = boto3.client("bedrock-runtime", region_name="us-east-1")

def my_llm_stuff():
    # or sentry_sdk.traces.start_span(name="The result of the AI inference", parent_span=None) in stream mode
    with sentry_sdk.start_transaction(name="The result of the AI inference"):
        response = client.converse(
            modelId="us.anthropic.claude-haiku-4-5-20251001-v1:0",
            messages=[
                {
                    "role": "user",
                    "content": [{"text": "Tell me a short story about a robot."}],
                }
            ],
        )
        print(response["output"]["message"]["content"][0]["text"])
```

After running this script, the resulting data should show up in the `AI Spans` tab on the `Explore > Traces > Trace` page on Sentry.io.

If you manually created an [Invoke Agent Span](https://docs.sentry.io/platforms/python/agent-tracing/manual-instrumentation.md#invoke-agent-span) (not done in the example above) the data will also show up in the [Agents Dashboard](https://docs.sentry.io/product/agents/dashboards.md).

It may take a couple of moments for the data to appear in [sentry.io](https://sentry.io).

## [Behavior](https://docs.sentry.io/platforms/python/agent-tracing/bedrock.md#behavior)

* The Boto3 integration will connect Sentry with the supported Bedrock methods automatically.

* The supported methods are currently `converse` and `converse_stream` on the `bedrock-runtime` client.

* Sentry considers LLM inputs/outputs as PII (Personally identifiable information) and doesn't include prompts, messages, or responses by default. Tool definitions are still attached by default; setting `inputs` to `False` in the `gen_ai` key described below removes them. To include prompts, messages, and responses, use the `gen_ai` key of the [`data_collection` option](https://docs.sentry.io/platforms/python/configuration/options.md#data_collection), which lets you control inputs and outputs separately. When you pass a `data_collection` dictionary, both are collected by default:

  ```python
  sentry_sdk.init(
      # ...
      data_collection={
          # Record LLM inputs, but not outputs
          "gen_ai": {"inputs": True, "outputs": False},
      },
  )
  ```

  Alternatively, set `send_default_pii=True` in the `sentry_sdk.init()` call. `send_default_pii` will be removed in version 3.0 of the SDK.