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Lambda vs. Fargate: The Cost of Running 24/7

Lambda vs. Fargate: The Cost of Running 24/7

It is straightforward arithmetic, (for a 1GB function in us-east-1 at time of writing):
0.0000000167 $/ms * 1000 ms/s * 60 s/min * 60 min/h * 24 h/day = 1.44 $/day

What does this mean?

AWS Lambda is expensive if you're using it for regularly occurring, long-running processes that do not to take advantage of the very short scaling time the service provides. If the work requires constant processing throughout the day — and it is not unpredictably bursty or massively parallelizable with requirements to get the processing done ASAP — it is worth looking to move your compute needs to a different service. And, increasingly worthwhile the more RAM the processing requires.

Leaving more affordable (but more operationally complex) options to the side, let's do a quick comparison of Lambda vs. Fargate.

Lambda vs. Fargate

In this example, we have a Fargate container that runs 24/7 with no scaling, and a Lambda function that is invoked once a minute and runs for 60 seconds:


As you see in the graph above, at no point is doing this work in Lambda more affordable.

In the below example, we introduce a massive performance improvement in our Lambda code — dropping the execution time by two-thirds, down to 20 seconds:


This magic only brings the Lambda function's cost to what Fargate would charge for middle-of-the-road CPU allocation. 😒 I'd bet those performance improvements would work just as well in Fargate too. 😁

AWS Lambda is great, but it’s not great for everything. So, pay attention to your infrastructure patterns, folks!

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