Amazon Bedrock AgentCore
Serverless Observability Serverless Security Stack
| Version | 0.0.1 (View all) |
| Subscription level What's this? | Basic |
| Developed by What's this? | Elastic |
| Ingestion method(s) | API |
To use beta integrations, go to the Integrations page in Kibana, scroll down, and toggle on the Display beta integrations option.
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.
Extra AWS charges on API requests will be generated by this integration. Check API Requests for more details.
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, Gateways, Memory, and Identity.
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.
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 agentResource: The Amazon Resource Name (ARN) of the agent resourceAgentId: The unique identifier of the agentEndpointName: The name of the agent endpointSessionId: The session identifier for agent invocations
Example
{ "@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" } } Exported fields
| Field | Description | Type | Unit | Metric Type |
|---|---|---|---|---|
| @timestamp | Event timestamp. | date | ||
| agent.id | Unique identifier of this agent (if one exists). Example: For Beats this would be beat.id. | keyword | ||
| aws.bedrock_agentcore.metrics.ApiKeyFetchFailures.sum | Total number of failed API key fetch operations from credential providers. | long | gauge | |
| aws.bedrock_agentcore.metrics.ApiKeyFetchSuccess.sum | Total number of successful API key fetch operations from credential providers. | long | gauge | |
| aws.bedrock_agentcore.metrics.ApiKeyFetchThrottles.sum | Total number of throttled API key fetch operations from credential providers. | long | gauge | |
| aws.bedrock_agentcore.metrics.CallCount.sum | Total number of calls made to Identity Service operations. | long | gauge | |
| aws.bedrock_agentcore.metrics.CreationCount.sum | Total number of resources created. | long | gauge | |
| aws.bedrock_agentcore.metrics.Duration.avg | Average duration of agent execution for each request. | double | ms | gauge |
| aws.bedrock_agentcore.metrics.Errors.sum | Total number of errors encountered during agent execution. | long | gauge | |
| aws.bedrock_agentcore.metrics.InboundAuthorizationFailure.sum | Total number of inbound authorization failures. | long | gauge | |
| aws.bedrock_agentcore.metrics.InboundAuthorizationSuccess.sum | Total number of successful inbound authorizations. | long | gauge | |
| aws.bedrock_agentcore.metrics.Invocations.sum | Total number of requests made to the Data Plane API. | long | gauge | |
| aws.bedrock_agentcore.metrics.Latency.avg | Average time elapsed between receiving the request and sending the final response token. | double | ms | gauge |
| aws.bedrock_agentcore.metrics.ResourceAccessTokenFetchFailures.sum | Total number of failures in fetching resource access tokens. | long | gauge | |
| aws.bedrock_agentcore.metrics.ResourceAccessTokenFetchSuccess.sum | Total number of successful fetches of resource access tokens. | long | gauge | |
| aws.bedrock_agentcore.metrics.ResourceAccessTokenFetchThrottles.sum | Total number of throttled OAuth2 token fetch operations from credential providers. | long | gauge | |
| aws.bedrock_agentcore.metrics.Sessions.sum | Total number of agent sessions initiated. | long | gauge | |
| aws.bedrock_agentcore.metrics.SystemErrors.sum | Total number of server-side errors indicating infrastructure or service issues. | long | gauge | |
| aws.bedrock_agentcore.metrics.TargetExecutionTime.avg | Average execution time for each target type. | double | ms | gauge |
| aws.bedrock_agentcore.metrics.TargetType_LAMBDA.sum | Total number of invocations targeting AWS Lambda. | long | gauge | |
| aws.bedrock_agentcore.metrics.TargetType_MCP.sum | Total number of invocations targeting MCP (Model Context Protocol). | long | gauge | |
| aws.bedrock_agentcore.metrics.ThrottleCount.sum | Total number of throttled calls for Identity Service operations. | long | gauge | |
| aws.bedrock_agentcore.metrics.Throttles.sum | Total number of requests throttled due to exceeding allowed TPS or quota limits. | long | gauge | |
| aws.bedrock_agentcore.metrics.TokenCount.sum | Total number of tokens processed during agent execution. | long | gauge | |
| aws.bedrock_agentcore.metrics.UserErrors.sum | Total number of client-side errors resulting from invalid requests. | long | gauge | |
| aws.bedrock_agentcore.metrics.WorkloadAccessTokenFetchFailures.sum | Total number of failures in fetching workload access tokens. | long | gauge | |
| aws.bedrock_agentcore.metrics.WorkloadAccessTokenFetchSuccess.sum | Total number of successful fetches of workload access tokens. | long | gauge | |
| aws.bedrock_agentcore.metrics.WorkloadAccessTokenFetchThrottles.sum | Total number of throttled workload access token fetch operations. | long | gauge | |
| aws.cloudwatch.namespace | The namespace specified when query cloudwatch api. | keyword | ||
| aws.dimensions.* | Metric dimensions. | keyword | ||
| cloud.account.id | The cloud account or organization id used to identify different entities in a multi-tenant environment. Examples: AWS account id, Google Cloud ORG Id, or other unique identifier. | keyword | ||
| cloud.region | Region in which this host, resource, or service is located. | keyword | ||
| data_stream.dataset | Data stream dataset. | constant_keyword | ||
| data_stream.namespace | Data stream namespace. | constant_keyword | ||
| data_stream.type | Data stream type. | constant_keyword | ||
| event.module | Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module. | constant_keyword |
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.
Changelog
| Version | Details | Kibana version(s) |
|---|---|---|
| 0.0.1 | Enhancement (View pull request) Initial draft of the package | — |