Comprehensive registry migration guide
AWS Agent Registry — Migrating from Public Preview to General Availability
Introduction
As part of launching as Generally Available (GA) on August 6, 2026, AWS Agent Registry is introducing significant changes to the service principal, data and API model. If you used AWS Agent Registry during the public preview, you must complete a migration that spans three areas:
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Namespace and configuration changes – We are moving AWS Agent Registry from the AWS Bedrock AgentCore namespace into its own dedicated namespace. This namespace change applies only to AWS Agent Registry. All other AgentCore offerings—such as Identity, Gateway, Runtime, and Policy—remain unaffected. For AWS Agent Registry, the service namespace changes from
bedrock-agentcoretoagent-registry. This affects every surface that references the service: endpoints, IAM policies, SDK clients, CLI commands, resource ARNs, and observability integrations. You must update your code and infrastructure to use the new namespace. -
API schema changes – The registry and registry record data models are updated based on customer feedback during the public preview. These changes break backward compatibility with the existing API schemas. Your application code that constructs or parses API requests and responses must be updated to reflect the new schema, as part of migrating to the new namespace.
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Data migration – You must migrate your existing registries and registry records from the old namespace to the new one. We provide migration tooling to extract your data, transform it to the new schema, and load it into the new namespace. The data is migrated to the same account and region — only the namespace changes.
This guide covers each area in detail with before-and-after examples to help you plan and execute your migration.
What is the migration timeline?
There are two important milestones you must remember for this migration:
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August 6, 2026 — AWS Agent Registry becomes Generally Available, and the new
agent-registrynamespace officially launches. If you have existing registries and records, you have simultaneous access to thebedrock-agentcoreandagent-registrynamespaces. Migration tooling becomes available in the agentcore-samples GitHub repository. You can begin the process of migration. Note
If you are a new customer without existing registries or records as of August 6, 2026, you cannot access AWS Agent Registry through the
bedrock-agentcorenamespace. Start using AWS Agent Registry directly from theagent-registrynamespace. -
September 17, 2026 — Migration window closes. The old
bedrock-agentcorenamespace shuts down on this date. You lose read/write access to the service and any remaining data in the old namespace. After this date, you must use theagent-registrynamespace.
Namespace and configuration changes
The agent-registry namespace replaces bedrock-agentcore in the following places. This section lists every surface that changes and provides examples of how to update your code.
Important
The namespace changes only affect APIs offered by AWS Agent Registry, but not the rest of AWS Bedrock AgentCore, such as AWS AgentCore Identity. Thus, workload identity and OAuth credential provider resources remain under the bedrock-agentcore namespace.
Service endpoints
Your applications must point to the new endpoint hostnames. The new endpoints use the .api.aws domain.
| Surface | Old value | New value |
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Data plane endpoint |
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Control plane endpoint |
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IAM and security
All IAM policies, service control policies (SCPs), and permission boundaries that reference bedrock-agentcore must be updated. Resource ARNs also change to reflect the new namespace.
| Surface | Old value | New value |
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IAM action prefix |
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Service principal |
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Registry ARN |
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Record ARN |
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If you have automation that parses ARNs or stores them, update those references as well. Custom policies with conditions on the IAM action prefix or service principal must be updated to match the new values. To see the full list of IAM permissions associated with AWS Agent Registry, refer to the AWS Agent Registry IAM permissions reference.
Note
If you currently use the BedrockAgentCoreFullAccess
AWS Managed Policy for AWS Agent Registry access (see BedrockAgentCoreFullAccess policy details), you must replace it with the new AgentRegistryFullAccess managed policy (available at GA). The old BedrockAgentCoreFullAccess managed policy will NOT be updated to include agent-registry:* permissions.
SDK, CLI, and infrastructure
Update your application code, deployment scripts, and infrastructure-as-code templates to reference the new client class and CLI namespace.
| Surface | Old value | New value |
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Dataplane SDK client class |
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Controlplane SDK client class |
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CLI namespace |
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Service Quotas code |
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If you previously requested custom quota increases under the bedrock-agentcore service code, you must re-request them under agent-registry.
Observability and eventing
Update any CloudTrail Lake queries, Athena queries, SIEM integrations, EventBridge rules, CloudWatch dashboards, and alarms that reference the old namespace.
| Surface | Old value | New value |
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CloudTrail event source |
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EventBridge source |
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CloudWatch namespace |
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Example: Updating IAM policies
Replace the action prefix and resource ARN namespace in all your IAM policies.
Before (public preview):
{ "Version": "2012-10-17", "Statement": [{ "Effect": "Allow", "Action": [ "bedrock-agentcore:CreateRegistry", "bedrock-agentcore:GetRegistry", "bedrock-agentcore:UpdateRegistry", "bedrock-agentcore:ListRegistries", "bedrock-agentcore:DeleteRegistry", "bedrock-agentcore:CreateRegistryRecord", "bedrock-agentcore:GetRegistryRecord", "bedrock-agentcore:UpdateRegistryRecord", "bedrock-agentcore:ListRegistryRecords", "bedrock-agentcore:DeleteRegistryRecord", "bedrock-agentcore:SubmitRegistryRecordForApproval", "bedrock-agentcore:UpdateRegistryRecordStatus", "bedrock-agentcore:SearchRegistryRecords" ], "Resource": ["arn:aws:bedrock-agentcore:us-west-2:123456789012:*"] }] }
After (General Availability):
{ "Version": "2012-10-17", "Statement": [{ "Effect": "Allow", "Action": [ "agent-registry:CreateRegistry", "agent-registry:GetRegistry", "agent-registry:UpdateRegistry", "agent-registry:ListRegistries", "agent-registry:DeleteRegistry", "agent-registry:CreateRegistryRecord", "agent-registry:GetRegistryRecord", "agent-registry:UpdateRegistryRecord", "agent-registry:ListRegistryRecords", "agent-registry:DeleteRegistryRecord", "agent-registry:SubmitRegistryRecordForApproval", "agent-registry:UpdateRegistryRecordStatus", "agent-registry:SearchDiscoverableRegistryRecords", "agent-registry:ListDiscoverableRegistryRecords", "agent-registry:GetDiscoverableRegistryRecord" ], "Resource": ["arn:aws:agent-registry:us-west-2:123456789012:*"] }] }
Note
The BatchGetDiscoverableRegistryRecord API does not have its own IAM action. It authorizes each requested record against the agent-registry:GetDiscoverableRegistryRecord action. Ensure your policy includes GetDiscoverableRegistryRecord to use BatchGet.
Important
Workload identity and OAuth credential provider resources remain under the bedrock-agentcore namespace. If your registries use URL sync (source.fromUrl) with OAuth or IAM credentials, you must retain the following permissions alongside your new agent-registry:* permissions:
"bedrock-agentcore:CreateWorkloadIdentity", "bedrock-agentcore:GetWorkloadIdentity", "bedrock-agentcore:DeleteWorkloadIdentity"
Do not replace every bedrock-agentcore action — these identity resources intentionally retain the old namespace.
Example: Updating SDK client configuration
Update the service name, client class, and endpoint URL in your SDK calls.
Before (public preview):
import boto3 session = boto3.Session(region_name="us-west-2") cp_client = session.client( "bedrock-agentcore-control", endpoint_url="https://bedrock-agentcore-control.us-west-2.amazonaws.com" ) dp_client = session.client( "bedrock-agentcore", endpoint_url="https://bedrock-agentcore.us-west-2.amazonaws.com" )
After (General Availability):
import boto3 session = boto3.Session(region_name="us-west-2") cp_client = session.client( "agent-registry-control", endpoint_url="https://agent-registry-control.us-west-2.api.aws" ) dp_client = session.client( "agent-registry", endpoint_url="https://agent-registry.us-west-2.api.aws" )
Example: Updating CLI commands
Replace the CLI namespace in all scripts and automation.
Before (public preview):
aws bedrock-agentcore-control create-registry \ --name "MyRegistry" \ --description "Production registry" \ --region us-west-2 \ --endpoint-url https://bedrock-agentcore-control.us-west-2.amazonaws.com
After (General Availability):
aws agent-registry-control create-registry \ --name "MyRegistry" \ --description "Production registry" \ --region us-west-2 \ --endpoint-url https://agent-registry-control.us-west-2.api.aws
API schema changes
In addition to the namespace migration, we updated the registry and registry record data models for General Availability. These changes improve the consistency and extensibility of the API based on feedback from the public preview. This section covers each change category with before and after examples so you can update your application code.
Change 1: Registry entity updates
The authorization configuration on the registry resource — which controls how a registry’s data plane is accessed — now sits under a dedicated discoveryConfiguration wrapper that makes its purpose explicit. The approval configuration (which controls whether records submitted to PENDING_APPROVAL status automatically transition to APPROVED status) moves from a boolean to an extensible enum array.
The specific field changes are:
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authorizerTypeandauthorizerConfigurationare moved inside a newdiscoveryConfigurationobject. -
approvalConfiguration.autoApproval(boolean) is replaced withapprovalConfiguration.autoApprovalRules(array of enum strings). The value"APPROVE_ALL"has the same semantic meaning asautoApproval: true. Rules specified in the enum list are applied. Not specifying (null) means approval is needed.
Before (public preview):
{ "name": "string", "description": "string", "authorizerConfiguration": { ... }, "authorizerType": "string", "approvalConfiguration": { "autoApproval": true } }
After (General Availability): with Approval ALL
{ "name": "string", "description": "string", "discoveryConfiguration": { "authorizerConfiguration": { ... }, "authorizerType": "string" }, "approvalConfiguration": { "autoApprovalRules": ["APPROVE_ALL"] } }
After (General Availability): with NULL in enum list
{ "name": "string", "description": "Registry with manual approval only", "approvalConfiguration": { "autoApprovalRules": [] } }
Change 2: New required fields on registry records
Registry records gain two new required top-level fields to support better categorization and deduplication. You must specify both fields when creating a registry record using the CreateRegistryRecord API, and you can change them later using the UpdateRegistryRecord API.
| Field | Type | Description |
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String (required) |
A unique identifier within the registry which can be specified by the customer. Every record must have a unique name in the registry. When |
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Enum (required) |
The semantic type of the record. Valid values: |
Change 3: Registry record restructuring
The descriptors field changes from a discriminated union to a flat keyed structure.
In the previous model, the descriptorType field (MCP, A2A, AGENT_SKILLS, CUSTOM) determined the inner shape. This coupled descriptor content to a coarse protocol or format classification. That field no longer exists. recordType, a separate top-level attribute, replaces it for semantic categorization. The API enforces valid descriptor keys for each recordType at runtime rather than structurally in the shape. Each top-level key under descriptors now represents a granular primary descriptor type (for example, a2aAgentCard, mcpServer, agentSkillsDefinition, custom). Supplementary descriptors (for example, tools, skillMd) nest under the primary descriptor’s additionalData. The inlineContent field becomes data. The schemaVersion and protocolVersion fields consolidate into dataSchemaVersion.
The top-level synchronizationConfiguration attribute becomes source and moves inside each descriptor (including additionalData children).
The existing name field becomes displayName, making its meaning more explicit. A net-new name field serves as the dedup key and must be unique across all records in a registry. If you specify both name and recordVersion for the same record, their combination must be unique.
The following fields are renamed:
| Before | After | Notes |
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Display name of the record. There will also be a new |
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Removed |
Replaced by the top-level |
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The content payload within each descriptor. |
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Unified version field for all descriptor types. |
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Moved inside each descriptor (including |
Before (public preview):
{ "recordId": "string", "name": "string", "descriptorType": "string", // A2A, MCP, AGENT_SKILL, CUSTOM "descriptors": { "agent": { "a2aAgentCard": { "inlineContent": "string", "schemaVersion": "string" } }, "agentSkills": { "skillDefinition": { "inlineContent": "string", "schemaVersion": "string" }, "skillMd": { "inlineContent": "string" } }, "mcp": { "server": { "inlineContent": "string", "schemaVersion": "string" }, "tools": { "inlineContent": "string", "protocolVersion": "string" } }, "custom": { "inlineContent": "string" } }, "synchronizationType": "URL", "synchronizationConfiguration": { "fromUrl": { "url": "string", "credentialProviderConfigurations": [ { "credentialProvider": { ... }, "credentialProviderType": "string" } ] } }, ... }
After (General Availability):
{ "recordId": "string", "displayName": "string", "name": "string", "recordVersion": "string", "recordType": "AGENT" | "MCP" | "SKILL" | "CUSTOM", "descriptors": { "a2aAgentCard": { "data": "string", "dataSchemaVersion": "string", "source": { "fromUrl": { "url": "string", "credentialProviderConfigurations": [...] } } }, "mcpServer": { "data": "string", "dataSchemaVersion": "string", "source": { "fromUrl": { ... } }, "additionalData": { "tools": { "data": "string", "dataSchemaVersion": "string" } } }, "agentSkillsDefinition": { "data": "string", "dataSchemaVersion": "string", "additionalData": { "skillMd": { "data": "string", "dataSchemaVersion": "string", "source": { "fromUrl": { ... } } } } }, "custom"?: { "data": "string" } }, "metadata": Document ... }
The following constraints apply:
Exactly one primary descriptor key may be populated per record. The valid primary descriptor per recordType are:
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AGENT:
a2aAgentCard,mcpServer,custom -
MCP:
mcpServer,custom -
SKILL:
agentSkillsDefinition,custom -
CUSTOM:
custom
source is per-descriptor rather than a single top-level block. It attaches to descriptors that carry a source field in the schema — mcpServer and a2aAgentCard. The tools child (under mcpServer.additionalData), the agentSkillsDefinition parent, and the custom descriptor carry no source.
At GA, only source.fromUrl is supported.
Auto-synchronization is only triggered for the mcpServer and a2aAgentCard primary descriptors — that is, MCP and AGENT record types. A source on the skillMd child is persisted but not used to run sync, and SKILL records cannot be auto-synchronized. CUSTOM records must be created manually by providing data directly.
Change 4: Data plane filter updates
SearchRegistryRecords becomes SearchDiscoverableRegistryRecords (POST /discoverable-records-search). Its request and response pick up the new field names and data model:
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Filter by
recordType(replacesdescriptorType). -
Filter by
recordVersion(replacesversion). -
The response returns descriptors in the new format, without
credentialProviderConfigurations.
The MCP search tool search_registry_records becomes search_discoverable_registry_records, returns the new descriptor format, and uses the new filter names.
Change 5: New browsing APIs
Two new data plane APIs support building browsing and catalog experiences over approved records. These APIs do not require any explicit migration; we mention them here as additions to the AWS Agent Registry API model at GA.
ListDiscoverableRegistryRecords — Returns a paginated list of approved registry records. Use this to build browsing interfaces over published content.
// HTTP: POST /registries/{registryId}/discoverable-records-list { "registryId": "string", // path param, required (ARN or ID) "maxResults": 1-100, // query param, optional "nextToken": "string", // query param, optional "filters": [ { "name": "recordType", "values": ["MCP"] } ] } { "registryRecords": [ { "registryArn": "string", "recordArn": "string", "recordId": "string", "name": "string", "displayName": "string", "description": "string", "recordType": "string", "recordVersion": "string", "status": "string", "createdAt": "string", "updatedAt": "string" } ], "nextToken": "string" }
BatchGetDiscoverableRegistryRecord — Retrieves full details for a batch of records across one or more registries in a single call.
// HTTP: POST /discoverable-records-batch { "entries": [ { "registryId": "reg-AAA", "recordIds": ["rec-111", "rec-222"] } ] } { "registryRecords": [ { "registryArn": "string", "recordArn": "string", "recordId": "string", "name": "string", "displayName": "string", "description": "string", "recordType": "string", "descriptors": { ... }, "recordVersion": "string", "status": "string", "createdAt": "string", "updatedAt": "string" } ], "errors": [ { "registryId": "string", "recordId": "string", "errorCode": "RESOURCE_NOT_FOUND" | "ACCESS_DENIED" | "INTERNAL_ERROR", "message": "string" } ] }
The response includes a registryRecords array with the full record details and an errors array for any records that could not be retrieved.
At launch, exactly one entry (one registry, 1-100 record IDs) is accepted. The grouped shape is forward-compatible with cross-registry batching in future releases.
Change 6: List APIs adopt structured filters parameter
In public preview, List APIs expose each filterable field as its own query parameter (for example, --status READY, --recordType MCP). In GA, a single structured filters parameter replaces these discrete parameters. The filters value is a list of { "name": "<dotted.path>", "values": ["<value>"] } entries where name is a dot-delimited attribute path. New filterable fields, including nested ones, become new name paths rather than new API parameters. List operations also change from GET to POST. Pagination parameters (maxResults, nextToken) are unchanged.
Before (public preview):
GET /registries?status=READY&authorizerType=AWS_IAM GET /registries/{registryId}/records?name=my-agent&status=APPROVED&recordType=MCP
After (General Availability):
// ListRegistries // POST /registries-list { "filters": [ { "name": "status", "values": ["READY"] }, { "name": "discoveryConfiguration.authorizerType", "values": ["AWS_IAM"] } ], "maxResults": 100, "nextToken": "string" } // ListRegistryRecords // POST /registries/{registryId}/records-list { "filters": [ { "name": "name", "values": ["my-agent"] }, { "name": "status", "values": ["APPROVED"] }, { "name": "recordType", "values": ["MCP"] } ], "maxResults": 100, "nextToken": "string" }
Data migration
You must migrate your existing registries and registry records from the bedrock-agentcore namespace to the agent-registry namespace. We provide a script to assist with the migration. The script handles extraction of existing data, transformation from the old schema to the new schema, and loading into registries in the new namespace. The script creates new registries in the agent-registry namespace within the same account and region. It migrates all existing records from your old registries to the new ones, accounting for namespace and API schema changes.
Choosing your migration approach
The right approach depends on the scale of your registry usage and your operational environment.
Case 1: Small-scale migration with direct script execution
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Profile: Fewer than 5 registries and fewer than 100 records. You have direct access to a terminal or CloudShell in the target account.
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Approach: Run the migration Python script directly. The script connects to the preview namespace, lists your registries and records, transforms the data to the GA schema, and creates them in the new namespace. This is the simplest path and requires no infrastructure deployment.
Case 2: Managed migration with Lambda or Glue
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Profile: You do not have direct terminal access to the target environment, or you prefer a managed execution model.
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Approach: Deploy the migration as an AWS Lambda function or AWS Glue job. The migration engine performs the same extract-transform-load workflow but runs as a managed job within your account. For most accounts, the full migration completes in under 15 minutes.
The migration engine:
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Extracts registries and records from the preview namespace, supporting both full and incremental loads. It paginates through all API responses and serializes the data to a staging location.
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Transforms each record by applying the API schema changes (field renames, descriptor restructuring, new required fields).
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Loads the transformed data into the new
agent-registrynamespace, creating registries and records using the GA API. -
Generates a report summarizing what was migrated, any errors encountered, and record counts for verification.
Case 3: Dual-write migration for active production workloads
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Profile: You have built a platform or automation pipeline on top of the public preview APIs and are actively writing new data in production.
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Approach: Use a dual-write migration strategy to avoid data loss during the transition:
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Update your writer – Modify your application to write to both the preview namespace and the new
agent-registrynamespace simultaneously. -
Run the migration script with deduplication – Execute the migration tooling to migrate historical data. The script deduplicates based on the
namefield, so records that already exist in the new namespace (from your dual-write) are not duplicated. -
Switch your reader – After you verify that all data exists in the new namespace, update your application to read exclusively from
agent-registry. -
Remove the dual-write – After confirming all reads and writes are successful on the new namespace, remove the preview namespace writer from your application.
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Verifying your migration
After running the migration, confirm that your data was migrated correctly:
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List all registries in the new namespace using the
list-registriesCLI command and confirm the count matches your source. -
For each registry, compare the record count using
list-registry-records. -
Spot-check individual records to confirm that descriptors were transformed correctly (field renames, descriptor restructuring).
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Update your IAM policies, endpoints, and SDK clients as described in the Namespace and configuration changes section.
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Verify that your applications can successfully read and write using the new namespace.
FAQ
What is changing in AWS Agent Registry?
AWS Agent Registry is moving from the public preview bedrock-agentcore namespace to the generally available agent-registry namespace. The migration spans three areas: namespace and configuration changes (endpoints, IAM, SDK, CLI, ARNs, observability), API schema changes (restructured data model for registries and records), and data migration (moving your existing registries and records to the new namespace).
Can I continue using Registry on the bedrock-agentcore namespace?
Your existing Registry usage on the bedrock-agentcore namespace continues to work without interruption during the migration window. However, we recommend that you begin your migration as soon as tooling becomes available to ensure you have sufficient time to complete both data migration and code updates.
However, if you do not have existing registries or records as of August 6, 2026, you cannot access the bedrock-agentcore namespace for AWS Agent Registry from August 6, 2026. If you have existing registries or records as of August 6, 2026, you have access to the bedrock-agentcore namespace for AWS Agent Registry during the migration window (August 6, 2026 – September 17, 2026).
Will my data be automatically migrated?
No. You must initiate the migration yourself using the migration tooling that we provide. See the Data migration section for details on the available approaches based on your scale.
What API schema changes are included?
In addition to the namespace change, we updated the API data model in six areas: registry entity (authorization config grouped under discoveryConfiguration), registry record new fields (name and recordType), registry record restructuring (descriptors flattened, field renames), search API filter updates (recordType, recordVersion), new browsing APIs (ListDiscoverableRegistryRecords, BatchGetDiscoverableRegistryRecord), and structured filters for List operations.
How long will the data migration take?
Migration time depends on the number of registries and records in your account. For accounts with fewer than 100 records, the migration completes in minutes when running locally. For accounts with thousands of records, expect the migration to complete in under 15 minutes when running as a managed job.
What if I have a large-scale deployment with active writes?
If you are actively writing data to the preview namespace in production, use the dual-write migration strategy as described in Case 3. This approach ensures no data is lost during the transition by writing to both namespaces simultaneously, migrating historical data with deduplication, and then cutting over reads.
Where can I get help?
For questions or assistance with your migration, contact AWS Support