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Amazon Bedrock Agents → OpenObserve

Automatically capture latency and invocation metadata for every Amazon Bedrock Agent call using the OpenInference Bedrock instrumentation.

Prerequisites

  • Python 3.8+
  • An OpenObserve account (cloud or self-hosted)
  • Your OpenObserve organisation ID and Base64-encoded auth token
  • AWS credentials with AmazonBedrockFullAccess permissions
  • A Bedrock Agent with an Agent ID and Alias ID. See Create a Bedrock agent.

Installation

pip install openobserve-telemetry-sdk openinference-instrumentation-bedrock boto3 python-dotenv

Configuration

Create a .env file in your project root:

OPENOBSERVE_URL=https://api.openobserve.ai/
OPENOBSERVE_ORG=your_org_id
OPENOBSERVE_AUTH_TOKEN=Basic <your_base64_token>

AWS_ACCESS_KEY_ID=your-access-key-id
AWS_SECRET_ACCESS_KEY=your-secret-access-key
AWS_DEFAULT_REGION=your-aws-region
BEDROCK_AGENT_ID=your-agent-id
BEDROCK_AGENT_ALIAS_ID=TSTALIASID

Instrumentation

Call BedrockInstrumentor().instrument() before creating any boto3 client.

from dotenv import load_dotenv
load_dotenv()

from openinference.instrumentation.bedrock import BedrockInstrumentor
from openobserve import openobserve_init

BedrockInstrumentor().instrument()
openobserve_init(resource_attributes={"service.name": "amazon-bedrock-agents"})

import os, uuid, boto3

client = boto3.client(
    "bedrock-agent-runtime",
    region_name=os.environ.get("AWS_DEFAULT_REGION", "us-east-1"),
)

response = client.invoke_agent(
    agentId=os.environ["BEDROCK_AGENT_ID"],
    agentAliasId=os.environ.get("BEDROCK_AGENT_ALIAS_ID", "TSTALIASID"),
    sessionId=str(uuid.uuid4()),
    inputText="What can you help me with?",
)
completion = ""
for event in response.get("completion", []):
    if "chunk" in event:
        completion += event["chunk"]["bytes"].decode("utf-8")
print(completion)

What Gets Captured

Attribute Description
operation_name Always bedrock_agent.invoke_agent
openinference_span_kind Always AGENT
llm_provider Always aws
input_value Text sent to the agent
output_value Agent response text
output_mime_type Always text/plain
span_status OK on success, ERROR on failure
duration End-to-end invocation latency

Viewing Traces

  1. Log in to OpenObserve and navigate to Traces in the left sidebar
  2. Click any bedrock_agent.invoke_agent span to inspect latency and input/output content

Amazon Bedrock Agents trace in OpenObserve

Next Steps

Track agent response times, monitor failure rates, and correlate agent spans with the rest of your application traces.

Read More

Last update: May 11, 2026