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Use CloudTrail as the audit record for AI-agent API activity, not as a replay of the agent’s internal reasoning. Start by identifying the AWS service and endpoint your agent uses, then enable the required management and data-event selectors. Classic Amazon Bedrock agent invocations, many AgentCore operations, and Bedrock Mantle inference require explicit data-event selectors; they will not appear merely because management events are enabled. Pair CloudTrail with AgentCore Observability in CloudWatch when you need execution traces, latency, token usage, or error metrics.
What CloudTrail can—and cannot—show about an AI agent
CloudTrail records activity that AWS exposes as monitorable API events. Each captured event can help answer who made a request, which service accepted it, what operation was requested, when it occurred, and which resource was involved. That makes CloudTrail valuable for security investigations, change auditing, access reviews, and proving that a particular identity or workload called an AWS API.
It is not a complete transcript of an agent run. CloudTrail does not provide the agent’s private chain of thought, a guaranteed step-by-step workflow, or an ordered execution trace across every tool and downstream system. AWS states that CloudTrail log files are not an ordered stack trace of public API calls, so events can appear out of sequence. Use CloudTrail to establish the request and identity trail; use runtime observability for timing and execution detail.
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First identify the service and endpoint
“Bedrock activity” is not one CloudTrail category. The event class and selector depend on the exact API surface. Inventory every component in the agent path before creating selectors.
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| Agent component or endpoint | Important operations or events | CloudTrail treatment | What to select |
|---|---|---|---|
Bedrock agent runtime (bedrock-runtime) |
InvokeAgent, InvokeInlineAgent |
Data events | AWS::Bedrock::AgentAlias for InvokeAgent; AWS::Bedrock::InlineAgent for InvokeInlineAgent |
| Bedrock runtime model APIs | InvokeModel, Converse, and streaming variants |
Management events | Verify that management-event logging is enabled for the account and Region |
Bedrock Mantle (bedrock-mantle.amazonaws.com) |
Mantle inference operations | Data events | Use Mantle’s documented resource types and event names; selectors for other Bedrock event sources do not automatically cover Mantle |
| Bedrock Knowledge Bases, Flows, and Guardrails | Knowledge Base retrieval, Flow invocation, and Guardrail application | Documented data-event cases | Add only the resource types required by the application, such as Knowledge Base, Flow alias, or Guardrail selectors |
| AgentCore Registry | Registry data operations | Data events | AWS::AgentRegistry::Registry |
| AgentCore Runtime or harness | Runtime invocation and harness operations | Data events | AWS::BedrockAgentCore::Runtime and the event names documented for the operation |
| AgentCore Gateway | Gateway data API invocation | Distinct data-event case | Select the Gateway resource type and its documented events |
Do not assume that an agent calling a model through one endpoint will produce the same event source as an agent using another. In particular, queries restricted to ordinary Bedrock runtime events can miss Bedrock Mantle activity.
Management events versus data events
Management events describe control-plane actions such as creating, changing, or deleting resources and configuring permissions. CloudTrail trails and event data stores record management events by default unless you deliberately exclude them. Event history is useful for recent management activity, but it is not a substitute for a long-term trail or CloudTrail Lake event data store.
Data events describe operations performed on or within a resource. They are often high volume and are not logged by default. Bedrock agent invocations and many AgentCore operations fall into this category, so a trail with only its default management-event settings will appear healthy while still missing the calls you care about.
| Question | Management events | Data events |
|---|---|---|
| Typical purpose | Who changed or configured an AWS resource? | Who invoked or accessed an operation on a resource? |
| Default status | Recorded by trails and event data stores by default | Not recorded by default |
| Agent example | Changing an agent, alias, policy, or configuration | Calling InvokeAgent or an AgentCore runtime |
| Scope controls | Management read/write choices and exclusions | Resource type, event name, and resource ARN selectors |
| Cost characteristic | Included in the normal management-event configuration | Additional charges can apply, especially at high volume |
Configure CloudTrail coverage step by step
1. Map the agent’s AWS call path
Write down the account and Region, the identity that starts the agent, and each AWS component it can call. Include classic Bedrock Agent aliases or inline agents, model APIs, Knowledge Bases, Flows, Guardrails, Bedrock Mantle, AgentCore Runtime or harness, Gateway, and Registry where applicable. Record the endpoint host as well as the friendly product name. This inventory prevents a selector aimed at one Bedrock event source from being mistaken for coverage of another.
2. Confirm your baseline trail or event data store
In the AWS console, open CloudTrail and review Event history for the account and Region. Event history is a quick way to confirm recent management activity. For an ongoing record, use Trails to deliver events to Amazon S3, or use a CloudTrail Lake event data store when you need queryable retention and governance.
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Management-event visibility in Event history does not prove that data events are enabled. Decide how long the record must survive and where investigators will query it before you turn on high-volume selectors. The Agent Registry documentation states that its management events appear in Event history for 90 days (Amazon Web Services documentation, 2026); treat that figure as specific to the cited Registry documentation rather than a universal retention promise for every CloudTrail collection mode.
3. Enable the required management events
For a trail, open CloudTrail > Trails, select the trail, and review its management-event settings. Keep the read and write categories that match your audit requirement. If your agent creates or updates resources during deployment, retain write management events; read events help establish which configuration was inspected.
4. Add classic Bedrock agent data selectors
In the trail’s Data events area, choose the advanced selector interface. Add a selector for the resource type AWS::Bedrock::AgentAlias and include the InvokeAgent event. Add AWS::Bedrock::InlineAgent when the application uses InvokeInlineAgent. Scope each selector to the aliases or resources that need auditing whenever the console permits ARN filtering.
If the agent retrieves from a Knowledge Base, invokes a Flow, or applies a Guardrail, add the corresponding documented data-event resource type and event name. Do not enable every available Bedrock data event automatically; broad capture can create a large volume of records and additional charges.
5. Cover Bedrock Mantle separately
For inference through the Bedrock Mantle endpoint, bedrock-mantle.amazonaws.com, create selectors using Mantle’s own documented resource types and event names. Mantle inference is classified as data activity. A search that filters only the ordinary Bedrock runtime event source can therefore return no Mantle records even while the agent is operating normally.
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6. Add AgentCore selectors that match the component
For Registry data operations, select AWS::AgentRegistry::Registry. For AgentCore Runtime or harness operations, select AWS::BedrockAgentCore::Runtime and verify the invocation event names in the current service documentation. Gateway invocation is a separate data-event case and needs its Gateway resource type and events rather than a Runtime selector.
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7. Save, run a known operation, and inspect the event
- Deploy or choose a test alias, inline agent, Runtime, Gateway, or other resource that you intentionally selected.
- Perform one known operation, such as a single agent invocation, Knowledge Base retrieval, Mantle inference, or Registry action.
- Wait for delivery according to the trail or event data store you selected, then search CloudTrail for the expected event name and time window.
- Check the event source, event name, event category, event time, selected resource type or ARN, and identity fields.
- Compare the event with the identity that actually made the request. If the event is absent, recheck Region, account, endpoint, selector scope, and whether the operation is a data event.
Use a deliberately narrow test first. It is easier to prove that one selector works than to diagnose a large, all-resource configuration.
How to read an agent event during an investigation
Confirm the service and operation
Start with the event source and event name. InvokeAgent, InvokeInlineAgent, Mantle inference events, Registry events, Runtime events, and Gateway events belong to different coverage paths. The event category should also tell you whether the record is a management or data event.
Establish time and resource context
Use the event time, Region, account, and resource identifier to align the call with application logs and deployment records. A resource ARN or resource-type field is especially useful when several aliases, runtimes, or gateways exist.
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Determine the calling identity carefully
For ordinary AWS API calls, inspect the CloudTrail identity fields to determine whether the caller was an IAM user, role, service, or federated session. Do not infer that the end user of a chatbot is the AWS caller; the recorded identity may be the application role or service identity that made the request.
AgentCore Gateway data events are different. AWS documents that they do not contain standard AWS identity information. Instead, selected JWT claims, including sub, can be recorded. Gateway requests and responses are redacted, and these data events route only to the resource-owner account. Avoid putting personally identifiable information in the recorded sub claim.
Do not reconstruct a stack trace from event order
CloudTrail records are an audit stream, not a guaranteed sequence diagram. Correlate events with timestamps, request identifiers, application logs, and CloudWatch traces rather than assuming the order in which CloudTrail displays them is the order in which the agent executed them.
Use CloudWatch AgentCore Observability for runtime behavior
CloudTrail answers questions about API requests and identities. AgentCore Observability in CloudWatch is the complementary tool when the question is “what happened inside this run, and how did it perform?” AWS documents telemetry such as execution traces, session count, latency, duration, token usage, and errors there.
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|---|---|---|
| Which role or service invoked an AWS API? | CloudTrail | Provides the audit identity and request context |
| Was a Bedrock agent alias invoked? | CloudTrail data event | Use the alias resource type and invocation event selector |
| How long did a run take? | AgentCore Observability in CloudWatch | Provides runtime latency and duration telemetry |
| How many tokens were used? | AgentCore Observability in CloudWatch | Token-usage telemetry is an operational metric, not a CloudTrail stack trace |
| Which run produced an error? | Use both | CloudWatch helps locate the failing execution; CloudTrail verifies the AWS calls and identities around it |
Selector scope, cost, and retention decisions
AWS states that additional charges apply to Bedrock data events. The amount depends on current AWS pricing, event volume, Region, and the collection destination, so check the pricing documentation for the account and Region before enabling broad capture. Do not treat a one-time test volume as a production estimate.
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Use the narrowest selector that still answers your audit question:
- Select specific resource types instead of every possible data-event source.
- Filter by event name when only invocation or retrieval actions matter.
- Use resource ARNs to limit capture to production aliases, runtimes, or gateways.
- Separate high-value security events from noisy operational traffic when your retention and query design allow it.
- Document which Regions and accounts are covered; a selector in one Region does not automatically cover another.
Also decide whether the record must outlast Event history. A trail delivered to S3 or a CloudTrail Lake event data store supports a retention design that you control, subject to the storage and query costs of that destination. Set access controls and lifecycle policies so that audit records remain available for the period required by your security or compliance program.
Troubleshoot missing or misleading records
| Symptom | Likely cause | Correction |
|---|---|---|
| Agent invocation is absent, but configuration changes appear | Only management events are enabled | Add the Bedrock agent data-event selector for the alias or inline-agent resource type |
InvokeAgent appears but InvokeInlineAgent does not |
The selector covers only AWS::Bedrock::AgentAlias |
Add AWS::Bedrock::InlineAgent and its event |
| Mantle calls are missing | The query is restricted to the ordinary Bedrock runtime source | Search the Mantle endpoint and enable its documented data-event selectors |
| Runtime activity is missing while Registry events are present | Only the Registry resource type was selected | Add AWS::BedrockAgentCore::Runtime and the relevant Runtime event names |
| Gateway events show no normal IAM identity | Gateway data events use JWT claims rather than standard AWS identity fields | Inspect the selected claims, including sub, and correlate with the gateway’s authentication logs |
| Events appear out of sequence | CloudTrail is not an ordered execution trace | Correlate timestamps and request IDs with CloudWatch observability and application logs |
| Selectors work in testing but not production | Different account, Region, alias ARN, endpoint, or execution role | Repeat the inventory and verify every selector against the production resource identifiers |
A practical monitoring design
For a small agent, start with management events plus the exact data selectors for its production alias or runtime. Add Knowledge Base, Flow, Guardrail, Mantle, Gateway, or Registry selectors only when the architecture uses those components. Send the audit record to a retained trail or event data store, and use CloudWatch AgentCore Observability for run-level diagnostics.
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For a multi-account deployment, define coverage per account and Region, record which account owns each Gateway or Registry resource, and test one known invocation in every environment. Review selector scope after each architecture change: adding a new endpoint or AgentCore component can create a logging gap even though the original trail remains active.
This division of labor gives investigators a defensible answer to “who called what, when, and against which AWS resource?” while avoiding the false promise that CloudTrail alone can replay an agent’s internal workflow.
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