Question

A data-processing Lambda function is configured with 128 MB of memory. It is CPU-bound and currently runs for about 8 seconds per invocation. The team wants to reduce both execution time and overall cost. After using AWS Lambda Power Tuning to test several memory settings, they find that at 1024 MB the function completes in about 1 second, and the total invocation cost is lower than at 128 MB. What is the primary reason increasing memory reduced both latency and cost in this case?

Accepted Answer

Lambda allocates CPU proportionally to memory, so more memory gave the CPU-bound function more compute, cutting duration enough to offset the higher per-millisecond price.

Answer

Higher memory tiers automatically enable provisioned concurrency, which eliminates cold starts and reduces billed duration.

Answer

Increasing memory reduces the number of billed invocations because Lambda batches more work into each request.

Answer

Lambda charges a flat rate per invocation regardless of memory, so any duration reduction is pure cost savings.