Hi everyone. I'm pretty new to serverless, but I'm diving in headfirst at my new company as we're evaluating everything from the ground up. I've been tasked with getting some lightweight data processing functions up and running on a popular cloud function service.
Here's my head-scratcher. I have a Python function that processes small batches of incoming webhook data. I set its memory to 256MB, which should be plenty for its simple task. The function runs fine, no explicit errors.
But when I look at the platform's memory usage metric, it consistently shows a peak of around 90-95MB. That seems well within the limit. However, the function's billed duration is *significantly* higher than the duration reported by my own logging inside the handler. We're talking about a 300-400ms difference on a 1-second task, which is adding up.
I was under the impression that the billed duration was purely execution time, but now I'm wondering if the memory setting itself is causing some kind of provisioning delay or cold-start penalty that gets counted? Or is the memory metric misleading? I've double-checked for large imports or lazy loading outside the handler, and I don't *think* that's it.
Has anyone run into a disconnect like this, where the numbers just don't seem to add up? I'm trying to optimize costs and performance, but I feel like I'm missing a piece of the puzzle. Any insight would be super appreciated
That's not a cold-start penalty, that's your platform billing you for the *provisioned* memory duration, not just the memory you used. You're paying for the full 256MB for the entire billed time, even though you only used 95MB.
The discrepancy between your logged duration and the billed duration is usually the function runtime's overhead - initialization, logging teardown, that kind of thing. It's all billed. Check if you have any layers or a particularly heavy runtime.
Welcome to serverless, where the main cost variable is memory-time and the metrics are designed to obscure that.
- Nina
Yeah, the billed vs logged duration gap is real. I hit something similar with a marketing automation webhook on a different platform. My own logs said 120ms, but the bill said 450ms. I ended up wrapping everything in a tighter timer and found the platform was counting the time to package and send the response log entry itself as part of the runtime.
Your 256MB setting might be making that overhead worse, even if your actual use is low. Have you tried dropping the memory to 128MB and seeing if the billed duration changes? Sometimes the platform allocates slower at higher memory tiers.