# How SQS Can Reduce Lambda Costs
Lambda costs are primarily driven by two factors:
- Memory allocated
- Execution time
Using an SQS queue as an event source for Lambda functions can help reduce costs in the following ways:
Batching Messages
By configuring a batch size and batch window for the SQS event source mapping, Lambda can process messages in batches instead of one at a time. This means:
- Fewer Lambda invocations
- Shorter execution time per invocation
For example, processing 10 messages in a single invocation will be cheaper than 10 separate invocations, even if the total execution time is the same.
You can configure the batch size up to 10,000 messages and the batch window up to 20 seconds. Larger batch sizes and windows generally mean lower costs.
{
"BatchSize": 100,
"BatchWindow": 5
}Adjusting Memory
Lambda will allocate more memory when processing larger batches of messages to optimize performance.
You can define memory “steps” based on the batch size to avoid overprovisioning memory.
For example:
- 1-100 messages: 128 MB
- 100-600 messages: 384 MB
- 600-1100 messages: 512 MB
This ensures the optimal memory is used for a given batch size.
Avoiding Empty Receives
Long polling SQS queues can help avoid “empty receives”, which are billed requests that return no messages.
By configuring a long polling duration of up to 20 seconds, Lambda will wait until a message is available before invoking the function. This minimizes empty receives.
You can enable long polling in your Lambda function code or at the queue level.
Following these best practices around batching, memory allocation, and long polling can help optimize the cost of Lambda functions triggered by SQS messages. Let me know if you have any other questions!
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