When AWS Lambda consumes messages from an Amazon SQS queue, failed messages can be delivered again after the queue’s visibility timeout. Configure a redrive policy to move repeatedly failing messages to a dead-letter queue (DLQ), and enable partial batch responses when you want successful records in a batch to avoid unnecessary retries. Make processing idempotent: a retry can repeat work that already caused a side effect.
How retries work with an SQS-triggered Lambda
With an SQS event source mapping, Lambda polls the queue and invokes your function with a batch of messages. When a message is received, SQS hides it for the visibility timeout. If processing fails and the message is not deleted, it can become visible and be received again. The queue’s visibility timeout and redrive policy are central to redelivery timing and the destination for messages that exceed the configured receive threshold. Lambda also applies backoff behavior, but this integration is not governed by Lambda’s native asynchronous-invocation retry schedule. AWS Lambda: Creating and configuring an Amazon SQS event source mapping.
For comparison, Lambda’s separate asynchronous invocation model uses a Lambda-managed event queue. By default, function errors receive two further attempts: one after one minute and another after two minutes. Throttling and system errors follow different defaults: Lambda retries for up to six hours, with intervals that increase from one second to as much as five minutes. Those are defaults for Lambda asynchronous invocation, not SQS maxReceiveCount settings. See How Lambda handles errors and retries with asynchronous invocation and Understanding retry behavior in Lambda.
For direct synchronous Lambda invocations, Lambda does not automatically retry function-code errors; the caller or application decides whether and how to try again. Always identify the trigger before choosing retry controls.
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What should the SQS visibility timeout be for Lambda?
AWS recommends setting the source queue’s visibility timeout to at least six times the Lambda function timeout. If you configure a batching window, add MaximumBatchingWindowInSeconds to that calculation. The function timeout must not exceed the queue visibility timeout. This gives the integration room to handle throttling and batch processing. See AWS’s event source mapping configuration guidance.
For example, if the function timeout is 30 seconds and the batching window is 10 seconds, the recommendation works out to at least 190 seconds: (6 × 30) + 10. This is an application of AWS’s recommendation, not a universal value; use your configured function timeout and batching window.
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How to configure retries and a DLQ
- Set a visibility timeout that fits processing. Apply the six-times-function-timeout guidance, adding the batching window if configured, and ensure the function timeout is no greater than the queue visibility timeout.
- Set a redrive policy on the source queue. Specify a DLQ and a deliberate
maxReceiveCount. For Lambda SQS event sources, AWS recommends a value of at least 5 so messages have several attempts before being moved. This is a recommendation for this integration, not a universal setting for all SQS consumers. See the Lambda event source mapping guidance. - Decide how batch failures should behave. If any record fails, the default behavior can make every message in the batch eligible for another delivery, including records already processed successfully. Enable
ReportBatchItemFailureson the event source mapping and return the identifiers of failed records to limit retries to those records. If your handler throws an exception, Lambda treats the entire batch as failed. See Handling errors for an SQS event source in Lambda. - Alert on DLQ messages. A DLQ makes repeated failures available for inspection; configure monitoring so operators know when messages arrive there.
How partial batch failures work
Partial batch responses are useful when records in one invocation can succeed or fail independently. Configure the event source mapping to report batch item failures, then have the function return only the failed message identifiers. Successfully processed records can then avoid the retry caused by another record’s failure. AWS describes this feature as a way to make only failed messages visible again after a batch failure; see the SQS event source error-handling guide.
For FIFO queues, preserve ordering when using partial batch responses: stop processing after the first failure and report that record along with any later, unprocessed records. Moving a failed message to a DLQ can itself break the exact order of messages or operations, so use a FIFO DLQ only if the workflow can tolerate that consequence. The Amazon SQS Developer Guide warns against using a DLQ with a FIFO queue when exact order must not be broken.
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Why Lambda may process the same SQS message again
Redelivery is part of retry behavior, not proof that a message will execute only once. A message may be received again when processing fails, when the visibility timeout expires before it is deleted, or when an invocation-level failure causes the batch to be retried. A duplicate can repeat an external side effect unless the application protects against it.
Make operations idempotent: use a durable operation key, such as a payment or business-event identifier, to detect that the work has already been applied before applying it again. Do not assume that one SQS receive corresponds to one execution or one side effect. AWS discusses retry handling in Understanding retry behavior in Lambda.
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What happens to messages in a DLQ?
A DLQ isolates messages that have not been processed successfully after the configured receive threshold. Operators can inspect message contents and related exception logs, diagnose the problem, and redrive messages after addressing its cause. Retention behavior differs by queue type:
- Standard queue: The original enqueue timestamp is preserved when SQS moves a message to a DLQ, and expiry remains based on that original timestamp. AWS recommends setting the DLQ retention period longer than the source queue’s retention period.
- FIFO queue: The enqueue timestamp resets when a message moves to the DLQ. A DLQ may also interrupt required message or operation ordering.
See Using dead-letter queues in Amazon SQS for the queue-specific behavior.
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Delay queues and visibility timeouts solve different problems
A delay queue postpones the first delivery of a newly sent message. Its configured delay can be up to 15 minutes. A visibility timeout begins after a consumer receives a message: it temporarily hides the message while processing occurs, and an undeleted message can become visible again when the timeout expires. A delay queue is therefore not a general-purpose exponential-backoff scheduler. See Amazon SQS delay queues.
For an individual message delay, SQS message timers can set DelaySeconds. For advanced scheduling beyond SQS’s 15-minute queue-delay and message-timer window, AWS recommends EventBridge Scheduler.
Choosing between SQS retries and Lambda asynchronous retries
| Decision point | SQS event source mapping | Lambda asynchronous invocation |
|---|---|---|
| Retry owner | Source queue and Lambda’s SQS event source mapping | Lambda-managed asynchronous event queue |
| Retry timing controls | Queue visibility timeout and redrive policy; Lambda also applies backoff | Lambda’s asynchronous retry behavior |
| Failure unit | Messages delivered in a batch; partial batch responses can identify failed records | Asynchronous invocation event |
| Terminal failure handling | SQS redrive policy and DLQ | Lambda DLQ or on-failure destination, depending on configuration |
| Ordering concerns | FIFO ordering requires care with partial failures and DLQs | Not governed by an SQS FIFO queue |
| Duplicate side effects | Use idempotent message processing | Use idempotent event processing |
For the Lambda asynchronous defaults, see Lambda asynchronous error handling. For SQS event source configuration, see Creating and configuring an Amazon SQS event source mapping.
Related SQS configuration limits and defaults
Amazon SQS queue configuration documentation lists message retention up to 14 days, with a four-day default, and visibility timeout up to 12 hours, with a 30-second default. These are service configuration values, not recommended retry settings; choose values for the queue and workload you are configuring. See Configuring queue parameters using the Amazon SQS console.
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