HN Reader

There's a ton of jargon here. Summarized...

Why EBS didn't work:

  - EBS costs for allocation
  - EBS is slow at restores from snapshot (faster to spin up a database from a Postgres backup stored in S3 than from an EBS snapshot in S3)
  - EBS only lets you attach 24 volumes per instance
  - EBS only lets you resize once every 6–24 hours, you can't shrink or adjust continuously
  - Detaching and reattaching EBS volumes can take 10s for healthy volumes to 20m for failed ones, so failover takes longer

Why all this matters:

  - their AI agents are all ephemeral snapshots; they constantly destroy and rebuild EBS volumes

What didn't work:

  - local NVMe/bare metal: need 2-3x nodes for durability, too expensive; snapshot restores are too slow
  - custom page-server psql storage architecture: too complex/expensive to maintain

Their solution:

  - block COWs
  - volume changes (new/snapshot/delete) are a metadata change
  - storage space is logical (effectively infinite) not bound to disk primitives
  - multi-tenant by default
  - versioned, replicated k/v transactions, horizontally scalable
  - independent service layer abstracts blocks into volumes, is the security/tenant boundary, enforces limits
  - user-space block device, pins i/o queues to cpus, supports zero-copy, resizing; depends on Linux primitives for performance limits

Performance stats (single volume):

  - (latency/IOPS benchmarks: 4 KB blocks; throughput benchmarks: 512 KB blocks)
  - read: 110,000 IOPS and 1.375 GB/s (bottlenecked by network bandwidth
  - write: 40,000–67,000 IOPS and 500–700 MB/s, synchronousy replicated
  - single-block read latency ~1 ms, write latency ~5 ms

TimescaleDB was such a great project!

I'm really sad to see them waste the opportunity and instead build an nth managed cloud on top of AWS, chasing buzzword after buzzword.

Had they made deals with cloud providers to offer managed TimescaleDB so they can focus on their core value proposition they could have won the timeseries business, but ClickHouse made them irrelevant and Neon already has won the "Postgres for agents" business thanks to a better architecture than this.

Are they not using aws anymore? I found that confusing. It says they're not using ebs, not using attached nvme, but I didn't think there were other options in aws?

Thanks for the writeup.

I'm curious whether you evaluated solutions like zfs/Gluster? Also curious whether you looked at Oracle Cloud given their faster block storage?

IUUC they built a EBS replacement on top of NVME attached to a dynamically sized fleet of EC2 instances.

The advantage is that it’s allocating pages on demand from an elastic pool of storage so it appears as an infinite block device. Another advantage is cheap COW clones.

The downside is (probably) specialized tuning for Postgres access patterns. I shudder to think what went into page metadata management. Perhaps it’s similar to e.g. SQL Server buffer pool manager).

It’s not clear to me why it’s better than Aurora design - on the surface page servers are higher level concepts and should allow more holistic optimizations (and less page write traffic due to shipping log in lieu of whole pages). Is also not clear what stopped Amazon from doing the same (perhaps EBS serving more diverse access patterns?).

Very cool!

I’m a bit confused about this:

“The storage device driver exposes Fluid Storage volumes as standard Linux block devices mountable with filesystems such as ext4 or xfs. It...allows volumes to be resized dynamically while online.”

Yet an xfs file system cannot be shrunk at all, and an ext4 filesystem cannot be shrunk without first unmounting it.

Are you simply doing thin provisioning of these volumes, so they appear to be massive but aren’t really? I see later that you say you account for storage based on actual consumption.

If anyone is interested in reading about a similar ”local-NVMe made redundant & shared over network as block devices” engine, last year I did some testing of Silk’s cloud block storage solution (1.3M x 8kB IOPS and 20 GiB/s throughput when reading the block store from a single GCP VM). They’re using iSCSI with multipathing on the client side instead of a userspace driver:

https://tanelpoder.com/posts/testing-the-silk-platform-in-20...

@graveland Which Linux interface was used for the userspace block driver (ublk, nbd, tcmu-runner, NVMe-over-TCP, etc)? Why did you choose it?

Also, were existing network or distributed file systems not suitable? This use case sounds like Ceph might fit, for example.

Yes, EBS sucks, but plenty of cloud providers already implemented the same thing Tiger Data has a decade ago. Like Google.

Though AWS instance-attached NVMe(oF?) still has less IOPS per TB than bare metal NVMe does.

    E.g. i8g.2xlarge, 1875 GB, 300k IOPS read
    vs. WD_BLACK SN8100, 2TB, 2300k IOPS read

EC2 instances have dedicated throughput to EBS via Nitro that you lose out on when you run your own EBS equivalent over the regular network. You only get 5Gbps maximum between two EC2 instances in the same AZ that aren't in the same placement group[1], and you're limited by the instance type's general networking throughput. Dedicated throughput to EBS from a typical EC2 instance is multiple times this figure. It's an interesting tradeoff--I assume they must be IOPS-heavy and the throughput is not a concern.

[1] https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-inst...

If you are targeting customers on AWS, don’t challenge EBS, because it is a losing game to begin with. There are 100 ways for AWS to optimize but none of them are available to you.

This has a similar flavor to xata.io's SimplyBlock based storage system * https://xata.io/blog/xata-postgres-with-data-branching-and-p... * https://www.simplyblock.io/

It's a great way to mix copy on write and effectively logical splitting of physical nodes. It's something I've wanted to build at a previous role.

pretty cool

Postgres for agents, of course! It makes too much sense.

So they've built a competitor to EBS that runs on EC2 and nvme. Seems like their prices will need to be much higher than those of AWS to get decent profit margins. I really hate being in the high-cost ecosystem of the large cloud providers, so I wouldn't make use of this.