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by rfoo 828 days ago
> And if its pseudo-random then it is predictable, and if its predictable then we can exploit that to great effect

This is an interesting hack. However, an IOP is an IOP, no matter how good you predicted it and prefetch it so that you hide the latency it's going to be translated to a GetObject.

I think what you really exploited here is that even though S3 is built on HDDs (and have very low IOPS per TiB) their scale is so large that even if you milk 1M+ IOPS out of it AWS still doesn't care and is happy to serve you. But if my back-of-envelope calculation is correct this isn't going to work well if everyone starts to do it.

How do you get around S3's 5.5k GET per second per prefix limit? If I only have ~200 20GiB files can you still get decent IOPS out of it?

and...

> IOPS is a really lazy benchmark that we believe can greatly diverge from most real life workloads

No, it's not. I have a workload training a DL model on time series data which demands 600k 8KiB IOPS per compute instance. None of the thing I tested work well. Had to build a custom one with bare metal NVMe-s.
1 comments
cuno 826 days ago
Sorry for the late response - I didn't see your comment until now.

Our aim is to unleash all the potential that S3/Object has to offer for file system workloads. Yes, the scale of AWS S3 helps, as does erasure coding (which enhances flexibility for better load balancing of reads).

Is it suitable for every possible workload? No, which is why we have a mode called cunoFS Fusion where we let people combine a regular high-performance filesystem for IOPS, and Object for throughput, with data automatically migrated between the two according to workload behaviour. What we find is that most data/workloads need high throughput rather than high IOPS, and this tends to be the bulk of data. So rather than paying for PBs of ultra-high IOPS storage, they only need to pay for TBs of it instead. Your particular workload might well need high IOPS, but a great many workloads do not. We do have organisations doing large scale workloads on time-series (market) data using cunoFS with S3 for performance reasons.

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