[thekozmo]

ScyllaDB uses Seastar as an engine and the DynamoDB compatible API use HTTP parsing, so this use case is real. Of course the DB has much more to do than this benchmark with a static http reply but Scylla also uses many more core in the server, thus it is close to real life. We do use the kernel's tcp stack, due to all of its features and also since we don't have capacity for a deeper analysis.

Some K/V workloads are affected by the networking stack and we recently seen issues if we chose not the ideal interrupt mode (multiqueue vs single queue in small machines)

[menaerus]

Few questions if you will, it's an interesting work and I figure you're on ScyllaDB team?

1. Is 5s experiment with 1s warmup really a representative workload? How about running for several minutes or tens of minutes? Do you observe the same result?

2. How about 256 connections on 16 vCPUs creating contention against each other and therefore skewing the experiment results? Aren't they competing for the same resources against each other?

3. Are the experiment results reproducible on different machines (at first use the same and then similar SW+HW configurations)?

4. How many times is experiment (benchmark) repeated and what about the statistical significance of the observed results? How do you make sure to understand that what you're observing, and hence drawing a conclusion out of it in the end, is really what you thought you were measuring?

[thekozmo]

Am ScyllaDB but Marc did completely independent work. The client vcpus don't matter that much, the experiment compares the server side, the client shouldn't suck. When we test ScyllaDB or other DBs, we run benchmarks for hours and days. This is just a stateless, static http daemon, so short timing is reasonable.

The whole intent is to make it a learning experience, if you wish to reproduce, try it yourself. It's aligned with past measurements of ours and also with former Linux optimizations by Marc.

[menaerus]

I'm myself doing a lot of algorithmic design but I also enjoy designing e2e performance testing frameworks in order to confirm theories I or others had on a paper. The thing is that I fell too many times into a trap without realizing that the results I was observing weren't what I thought I was measuring. So what I was hoping for is to spark a discussion around the thoughts and methodologies other people from the field use and hopefully learn something new.