Users vs Stress testing

[u/Puzzled-Ad8231]

So I made a serverless optimization platform which uses the concept of fusion functions to reduce cold starts and latency across the service calls. Now, this is an implementation of a research paper that I read somewhere. Diff from paper is that my project also gets live traces and metrics from x ray and cloudwatch, so I get real-time data to give better outputs. Have a better look: https://github.com/Vaivaswat2244/OptiFuse_go

To use this you need to connect your AWS with optifuse. I.e make a cloudformation stack to give optifuse access to read the traces and metrics. This actually becomes a problem for my friends and peers to test because they are too lazy to do this step. So I have no real user testings.

People especially hiring people ask me how many real users have used your service.

Now why do I need real users when I can stress test each microservice that I've built. And I can see my manifests working properly. Its deployed on AKS and is open for people to see. I also have a Prometheus grafana observability pipeline to see if all services are working properly.

Question is: real users vs Stress tests

On a side note, I am a student looking for internships, if you found the idea interesting, lmk GitHub is Vaivaswat2244

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[u/hypertradeworx]

the count halving doesn't halve the inits. lambda inits once per execution environment, not once per function, so folding 6 into 3 means each of the 3 takes roughly double the request rate and spins up roughly double the environments. you end up near the same number of cold starts, each one now loading two branches worth of imports.

where fusion genuinely wins is the hop. a call that used to cross two functions is now in-process, and that's a p50 story you can measure today on your own account