Redrive failed ingestions

Extraction from short-term memory to long-term memory is usually automatic. If extraction from short-term memory to long-term memory is unsuccessful for any reason, AgentCore Memory attempts to address the issue. If issues persist, developer intervention may be needed and the failed jobs are moved to a dedicated queue for your memory resource. One example is if your account is ingesting to long-term memory at a greater rate than what is allowed. In this case, you should wait until traffic is lower and manually redrive the impacted jobs.

To identify and redrive failed jobs:

1. Call ListMemoryExtractionJobs to list failed jobs. Each job in the response includes a jobId and a failureReason that indicates why extraction failed.

2. Address the root cause using the failure reason code in the following table.

3. Call StartMemoryExtractionJob, passing the jobId from the failed job list to re-ingest it into long-term memory.

We recommend monitoring the vended metric FailedExtraction to be notified of any issues. This metric also has dimensions on StrategyId, Resource (the memory ARN), and StrategyType. AgentCore Memory emits a count of this metric whenever an extraction job fails and is written to the extraction jobs storage.

For built-in strategies, the only failure scenario is hitting the ingestion limit. For built-in with override, there are additional failure scenarios, including issues with the model you’ve selected to use in your account or the permissions you’ve granted to AgentCore Memory.

Failure Reason Code	Description	Recommended mitigation
LTM_RATE_EXCEEDED	This account has exceeded the allocated tokens per minute quota for long-term memory processing	Through Service Quotas, request a higher limit for the Bedrock Agentcore quota "Tokens per minute for long-term memory extraction." Then invoke the StartMemoryExtractionJob API on the failed extraction’s jobID.
CUSTOM_MODEL_BEDROCK_ACCESS_DENIED	The memoryExecutionRoleArn provided during CreateMemory lacks adequate permissions to invoke all of the model IDs provided in the custom strategies attached to the memory	Ensure that the role has the permissions and trust policy as defined here and add any missing permissions. Or call UpdateMemory to switch to a different role with adequate permissions. Then invoke the StartMemoryExtractionJob API on the failed extraction’s jobID.
CUSTOM_MODEL_BEDROCK_INTERNAL_ERROR	The service received an internal error from Bedrock when attempting to invoke the model provided in the custom strategy.	This could be a temporary service error from Bedrock. Try again later by invoking the StartMemoryExtractionJob API on the failed extraction’s jobID.
CUSTOM_MODEL_BEDROCK_THROTTLING	The service received a throttling exception from Bedrock when attempting to invoke the model provided in the custom strategy.	Ensure that your account has requested adequate TPM and RPM quota for that model from Bedrock. Invoke the StartMemoryExtractionJob API on the failed extraction’s jobID after quota increase or during low-traffic hours.
CUSTOM_MODEL_BEDROCK_MODEL_ERROR	The service received a Model Error Exception from Bedrock when attempting to invoke the model provided in the custom strategy.	This is usually a temporary service error from Bedrock. Try again later by invoking the StartMemoryExtractionJob API on the failed extraction’s jobID.
CUSTOM_MODEL_BEDROCK_MODEL_TIMEOUT	The service received a Model Timeout Exception from Bedrock when attempting to invoke the model provided in the custom strategy.	This occurs when the model processing time exceeds its timeout. Consider switching to a faster model before invoking StartMemoryExtractionJob API on the failed extraction’s jobID.
CUSTOM_MODEL_BEDROCK_RESOURCE_NOT_FOUND	The service received a Resource Not Found from Bedrock when attempting to invoke the model provided in the custom strategy.	Ensure that the modelID provided in any custom strategies associated with the memory is correct. Call UpdateMemory to update those values if necessary. Then invoke the StartMemoryExtractionJob API on the failed extraction’s jobID.
CUSTOM_MODEL_BEDROCK_MODEL_NOT_READY	The service received a Model Not Ready from Bedrock when attempting to invoke the model provided in the custom strategy.	Wait for the model to be in a ready state. Refer to Bedrock documentation for more details. Then invoke the StartMemoryExtractionJob API on the failed extraction’s jobID.
CUSTOM_MODEL_BEDROCK_SERVICE_UNAVAILABLE	The service received Service Unavailable from Bedrock when attempting to invoke the model provided in the custom strategy.	This is usually a temporary service error from Bedrock. Try again later by invoking the StartMemoryExtractionJob API on the failed extraction’s jobID.
CUSTOM_MODEL_BEDROCK_VALIDATION_EXCEPTION	The service received Validation Exception from Bedrock when attempting to invoke the model provided in the custom strategy.	Ensure that the modelID provided in any custom strategies associated with the memory is correct. Call UpdateMemory to update those values if necessary. Then invoke the StartMemoryExtractionJob API on the failed extraction’s jobID.