Amazon Bedrock AgentCore

Amazon Bedrock AgentCore is a fully-managed platform that empowers you to build, deploy and operate intelligent agents using any framework or foundation model, while eliminating the burden of managing agent infrastructure. It is composed of modular capabilities such as Runtime, Gateway, Memory, Identity, Observability, Code Interpreter, and Browser Tool—enabling you to focus on crafting the agent workflows that interact with your systems and data.

The Amazon Bedrock AgentCore integration enables seamless monitoring of your intelligent agents by collecting comprehensive runtime metrics and observability data. This integration provides visibility into agent execution activity, performance metrics, resource utilization, error rates, and operational insights essential for maintaining optimal agent performance.

This integration is compatible with Amazon Bedrock AgentCore CloudWatch metrics and supports the AWS/Bedrock-AgentCore namespace for comprehensive observability data collection.

The Amazon Bedrock AgentCore integration collects runtime metrics and observability data from your intelligent agents.

Data streams:

• metrics: Collects Amazon Bedrock AgentCore runtime metrics including invocations, sessions, latency, performance indicators, error rates, throttling metrics, token counts, target execution metrics, and authorization metrics from the following AgentCore components: Agent runtime, Gateway, Memory, Identity, Browser Tool and Code Interpreter.

You need Elasticsearch for storing and searching your data and Kibana for visualizing and managing it. You can use our hosted Elasticsearch Service on Elastic Cloud, which is recommended, or self-manage the Elastic Stack on your own hardware.

Before using any Amazon Bedrock AgentCore integration you will need:

• AWS Credentials to connect with your AWS account.
• AWS Permissions to make sure the user you're using to connect has permission to share the relevant data.

For more details about these requirements, check the AWS integration documentation.

• Elastic Agent must be installed. For detailed guidance, follow these instructions.
• You can install only one Elastic Agent per host.
• Elastic Agent is required to collect metrics from CloudWatch and ship the data to Elastic, where the events will then be processed through the integration's ingest pipelines.

Some datasets in this integration require the ARN of the CloudWatch log group where your AgentCore logs are stored. You can find it by:

• Opening CloudWatch in the AWS Console
• Going to Logs > Log groups
• Selecting the log group used by your AgentCore deployment
• Copying the Log group ARN shown

You can then use this ARN when configuring any log-based dataset.

To use the Amazon Bedrock AgentCore metrics, ensure your agents are deployed and running. The integration will automatically collect metrics from the AWS/Bedrock-AgentCore CloudWatch namespace. For enhanced observability, enable detailed monitoring and logging for your AgentCore resources.

For more details about enabling observability for AgentCore, check the Amazon Bedrock AgentCore Observability Guide.

Amazon Bedrock AgentCore runtime metrics provide comprehensive visibility into your agent execution and performance. The integration collects the following categories of metrics:

These metrics enable several use cases, such as:

• Monitoring agent performance and response times
• Tracking resource consumption for cost optimization
• Identifying and troubleshooting error patterns
• Analyzing agent usage patterns and scaling requirements
• Monitoring authorization and access control effectiveness

Dimensions:

The metrics include the following dimensions for enhanced filtering and analysis:

• Operation: The operation name performed by the agent
• Resource: The Amazon Resource Name (ARN) of the agent resource
• AgentId: The unique identifier of the agent
• EndpointName: The name of the agent endpoint
• SessionId: The session identifier for agent invocations

{
    "@timestamp": "2025-11-11T18:25:00.000Z",
    "agent": {
        "ephemeral_id": "76c9ae9c-f0bd-4b82-8157-161deacb8d15",
        "id": "f3b14aaf-60db-49eb-b0aa-5b15ac26df85",
        "name": "elastic-agent-64028",
        "type": "metricbeat",
        "version": "8.19.0"
    },
    "aws": {
        "bedrock_agentcore": {
            "metrics": {
                "ResourceAccessTokenFetchSuccess": {
                    "sum": 1
                },
                "WorkloadAccessTokenFetchSuccess": {
                    "sum": 1
                }
            }
        },
        "cloudwatch": {
            "namespace": "AWS/Bedrock-AgentCore"
        }
    },
    "cloud": {
        "account": {
            "id": "121212121212",
            "name": "MonitoringAccount"
        },
        "provider": "aws",
        "region": "us-east-1"
    },
    "data_stream": {
        "dataset": "aws_bedrock_agentcore.metrics",
        "namespace": "41789",
        "type": "metrics"
    },
    "ecs": {
        "version": "8.0.0"
    },
    "elastic_agent": {
        "id": "f3b14aaf-60db-49eb-b0aa-5b15ac26df85",
        "snapshot": false,
        "version": "8.19.0"
    },
    "event": {
        "agent_id_status": "verified",
        "dataset": "aws_bedrock_agentcore.metrics",
        "duration": 11849440086,
        "ingested": "2025-11-11T18:32:13Z",
        "module": "aws"
    },
    "host": {
        "architecture": "x86_64",
        "containerized": false,
        "hostname": "elastic-agent-64028",
        "ip": [
            "172.19.0.7",
            "172.31.0.2"
        ],
        "mac": [
            "82-28-2D-42-E6-26",
            "AA-84-46-63-32-4C"
        ],
        "name": "elastic-agent-64028",
        "os": {
            "family": "",
            "kernel": "6.14.0-1006-gcp",
            "name": "Wolfi",
            "platform": "wolfi",
            "type": "linux",
            "version": "20230201"
        }
    },
    "metricset": {
        "name": "cloudwatch",
        "period": 300000
    },
    "service": {
        "type": "aws"
    }
}
		

Alert rule templates provide pre-defined configurations for creating alert rules in Kibana.

For more information, refer to the Elastic documentation.

Alert rule templates require Elastic Stack version 9.2.0 or later.

The following alert rule templates are available:

[AWS Bedrock AgentCore] Agent runtime high latency

[AWS Bedrock AgentCore] Agent runtime system errors

[AWS Bedrock AgentCore] Agent runtime user errors

[AWS Bedrock AgentCore] Browser errors

[AWS Bedrock AgentCore] Browser session throttles

[AWS Bedrock AgentCore] Code interpreter errors

[AWS Bedrock AgentCore] Code interpreter high latency

[AWS Bedrock AgentCore] Code interpreter throttles

[AWS Bedrock AgentCore] Gateway errors

[AWS Bedrock AgentCore] Gateway high latency

[AWS Bedrock AgentCore] Gateway throttles

[AWS Bedrock AgentCore] Identity throttles

[AWS Bedrock AgentCore] Identity token fetch failures

[AWS Bedrock AgentCore] Memory errors

[AWS Bedrock AgentCore] Memory high latency

Amazon Bedrock AgentCore runtime application logs provide detailed insights into agent execution, decision-making processes, and operational events. The integration collects comprehensive log data from your intelligent agents to help you understand agent behavior and troubleshoot issues.

For more details about enabling logs for AgentCore, check the Amazon Bedrock AgentCore Observability Guide.

{
    "agent": {
        "name": "docker-fleet-agent",
        "id": "8f26c9ae-e204-484b-aef5-38a8988e0a62",
        "type": "filebeat",
        "ephemeral_id": "d5a1fd3e-1411-4730-8b9a-e237d8000186",
        "version": "8.19.0"
    },
    "log": {
        "file": {
            "path": "arn:aws:logs:us-east-1:627286350132:log-group:/aws/vendedlogs/bedrock-agentcore/runtime/APPLICATION_LOGS/claudeserver-CdBoW2FLP0/BedrockAgentCoreRuntime_ApplicationLogs"
        }
    },
    "elastic_agent": {
        "id": "8f26c9ae-e204-484b-aef5-38a8988e0a62",
        "version": "8.19.0",
        "snapshot": false
    },
    "tags": [
        "forwarded"
    ],
    "cloud": {
        "provider": "aws",
        "service": {
            "name": "bedrock-agentcore"
        },
        "region": "us-east-1",
        "account": {
            "id": "627286350134"
        }
    },
    "input": {
        "type": "aws-cloudwatch"
    },
    "trace": {
        "id": "6909cc3835755ae933e4c5fc38d249a2"
    },
    "@timestamp": "2025-11-04T09:49:45.198Z",
    "ecs": {
        "version": "8.11.0"
    },
    "data_stream": {
        "namespace": "default",
        "type": "logs",
        "dataset": "aws_bedrock_agentcore.runtime_application_logs"
    },
    "service": {
        "name": "customersupport.DEFAULT"
    },
    "event": {
        "agent_id_status": "verified",
        "ingested": "2025-11-17T12:27:05Z",
        "id": "39299483435865920498526836744670895669942873429125169152",
        "dataset": "aws_bedrock_agentcore.runtime_application_logs",
        "outcome": "success"
    },
    "aws": {
        "bedrock_agentcore": {
            "conversation_id": "76d5c1a5-df2d-4299-b536-9f0302e344ab",
            "operation_name": "invoke_agent",
            "provider_name": "aws_bedrock_agentcore",
            "agent_name": "customersupport",
            "endpoint_name": "DEFAULT",
            "request_payload": {
                "actor_id": "DEFAULT",
                "prompt": "Summarize my previous conversation"
            },
            "operation": "InvokeAgentRuntime",
            "request_id": "083603b2-7b75-46ba-bf61-45c562764b68",
            "resource_arn": "arn:aws:bedrock-agentcore:us-east-1:627286350133:runtime/customersupport-3OutfrDDJ3",
            "service_name": "AgentCoreCodeRuntime",
            "session_id": "76d5c1a5-df2d-4299-b536-9f0302e344cb",
            "severity_number": 9
        }
    },
    "log": {
        "level": "INFO"
    },
    "span": {
        "id": "015d756c7d9bf372"
    }
}
		

This integration includes one or more Kibana dashboards that visualizes the data collected by the integration. The screenshots below illustrate how the ingested data is displayed.

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