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580 points huntaub | 8 comments | | HN request time: 1.248s | source | bottom

Hey HN, I’m Hunter the founder of Regatta Storage (https://regattastorage.com). Regatta Storage is a new cloud file system that provides unlimited pay-as-you-go capacity, local-like performance, and automatic synchronization to S3-compatible storage. For example, you can use Regatta to instantly access massive data sets in S3 with Spark, Pytorch, or pandas without paying for large, local disks or waiting for the data to download.

Check out an overview of how the service works here: https://www.youtube.com/watch?v=xh1q5p7E4JY, and you can try it for free at https://regattastorage.com after signing up for an account. We wanted to let you try it without an account, but we figured that “Hacker News shares a file system and S3 bucket” wouldn’t be the best experience for the community.

I built Regatta after spending nearly a decade building and operating at-scale cloud storage at places like Amazon’s Elastic File System (EFS) and Netflix. During my 8 years at EFS, I learned a lot about how teams thought about their storage usage. Users frequently told me that they loved how simple and scalable EFS was, and -- like S3 -- they didn’t have to guess how much capacity they needed up front.

When I got to Netflix, I was surprised that there wasn’t more usage of EFS. If you looked around, it seemed like a natural fit. Every application needed a POSIX file system. Lots of applications had unclear or spikey storage needs. Often, developers wanted their storage to last beyond the lifetime of an individual instance or container. In fact, if you looked across all Netflix applications, some ridiculous amount of money was being spent on empty storage space because each of these local drives had to be overprovisioned for potential usage.

However, in many cases, EFS wasn’t the perfect choice for these workloads. Moving workloads from local disks to NFS often encountered performance issues. Further, applications which treated their local disks as ephemeral would have to manually “clean up” left over data in a persistent storage system.

At this point, I realized that there was a missing solution in the cloud storage market which wasn’t being filled by either block or file storage, and I decided to build Regatta.

Regatta is a pay-as-you-go cloud file system that automatically expands with your application. Because it automatically synchronizes with S3 using native file formats, you can connect it to existing data sets and use recently written file data directly from S3. When data isn’t actively being used, it’s removed from the Regatta cache, so you only pay for the backing S3 storage. Finally, we’re developing a custom file protocol which allows us to achieve local-like performance for small-file workloads and Lustre-like scale-out performance for distributed data jobs.

Under the hood, customers mount a Regatta file system by connecting to our fleet of caching instances over NFSv3 (soon, our custom protocol). Our instances then connect to the customer’s S3 bucket on the backend, and provide sub-millisecond cached-read and write performance. This durable cache allows us to provide a strongly consistent, efficient view of the file system to all connected file clients. We can perform challenging operations (like directory renaming) quickly and durably, while they asynchronously propagate to the S3 bucket.

We’re excited to see users share our vision for Regatta. We have teams who are using us to build totally serverless Jupyter notebook servers for their AI researchers who prefer to upload and share data using the S3 web UI. We have teams who are using us as a distributed caching layer on top of S3 for low-latency access to common files. We have teams who are replacing their thin-provisioned Ceph boot volumes with Regatta for significant savings. We can’t wait to see what other things people will build and we hope you’ll give us a try at regattastorage.com.

We’d love to get any early feedback from the community, ideas for future direction, or experiences in this space. I’ll be in the comments for the next few hours to respond!

1. count ◴[] No.42174818[source]
I don't see any other question about it, so maybe I just missed the obvious answer, but how do you handle POSIX ACLs? If the data is stored as an object in S3, but exposed via filesystem, where are you keeping (if at all?) the filesystem ACLs and metadata?

Also, NFSv3 and not 4?

replies(1): >>42174874 #
2. huntaub ◴[] No.42174874[source]
Great call out. Some kinds of data, like ACLs and specific kinds of metadata, don't live in S3. Full disclosure, we don't support ACLs today (but plan to soon). We keep file system metadata in the durable cache. For some files (where users haven't changed permissions, etc), we are able to release that cached metadata when the file is no longer in use. For other files (where permissions have been changed by the user), that metadata must live in the cache long-term.

We selected NFSv3 due to it's broad compatibility with different compute environments. For example, Windows has an NFSv3 client in it, but doesn't have an NFSv4 client. There are lots of enterprise workloads which needs simultaneous access to file data from both Windows and Linux, and supporting NFSv3 was the easiest path to support those workloads.

replies(2): >>42175271 #>>42177171 #
3. count ◴[] No.42175271[source]
Thanks, I keep hoping someone comes up with some magic :)

Is the intent to run this in-vpc?

And how do you differentiate from AWS Storage Gateway?

replies(1): >>42175368 #
4. huntaub ◴[] No.42175368{3}[source]
I'd love to hear more about what you're excited to do when the magic arrives. :D

We are running it as a managed SaaS, so our customers connect to the caching layer that runs in the Regatta VPC. This allows us to manage the infrastructure for them and keep costs low.

Storage Gateway is an interesting product, and I worked closely with that team for several years -- so mad respect for them. It was designed to be an appliance that you run on servers in your own data center (of course, many customers now deploy it to EC2). Because of this, it's designed to operate in an environment with "finite storage" -- for example, different workload pattterns can thrash the cache, which results in poor performance to clients, and it's not designed to run in a high-availability cluster in the cloud. Regatta solves these problems with durable cache storage that's safe to data in long-term, and is designed for high-availability.

5. secabeen ◴[] No.42177171[source]
Do you pay for metadata accesses? Does running a `find` across the filesystem cost anything? What about system calls that don't transfer data? Can I move or rename a file without paying to copy and then delete the associated S3 object?
replies(1): >>42177334 #
6. huntaub ◴[] No.42177334{3}[source]
Today, we only charge for cache usage (storage) and data transfer between Regatta and S3. If your metadata access doesn't require transfer to S3, then it doesn't cost anything! However, renames do require transfer to S3 (because we have to move the object on the backend).
replies(1): >>42181161 #
7. hades32 ◴[] No.42181161{4}[source]
does that mean you pay for the storage twice (i.e. S3 and Regatta) or is the cache size tunable?
replies(1): >>42184615 #
8. huntaub ◴[] No.42184615{5}[source]
That’s correct — you pay for the storage yourself in S3, and then you pay for the storage when it’s in the Regatta cache. We may expose the ability to limit the cache size in the future for teams who need controllable costs more than the highest performance.