I still think S3 is underutilized.

The range of things you can do with blob storage and a (very simple) auth model are surprisingly broad.

We recently replaced our Docker container registry with S3 using a tiny tool [1] we built in-house. I think that even with current capabilities, we can still model a lot services as a very thin layer over object storage.

[1]: https://github.com/Simple-Observability/grue

Definitely agree that every data system that doesn't need <100ms latency is moving to object storage.

> I do wonder if we will see an expansion of the s3 api to support more of these use cases

This is actually an area where I think we have a big leg up on folks building on top of S3. My team (which built K2) sits next to the R2 team, and we have the opportunity to co-evolve the products in mutually beneficial ways.

doesn't that make egress fees egregious? or still cheaper than disks?

People like S3 because they have hard engineering guarantees around bit rot and work well as a high level abstraction of a network filesystem with all of the low level failure recovery built-in. You don't have to worry about doing your own RAID configs. The bigger question is whether non-AWS services can offer the same level of guarantees. I have heard horror stories for example when it comes to downtime on Hetzner's S3 object store.

I am currently using Cloudflare R2 right now and if you see their forums, there's always the occasional post about objects going missing.

I trust that this is not the case. Check out both the authors. Micah's company was acquired by Cloudflare, and both of these guys actually bring good expertise around this area.

The question is less about "vibe coding" the product, and more about how their acquired teams function. For most products they have released so far, they are backed by a company they acqui-hired. They will usually rebrand the product and absorb the team.

You would not be surprised if this release was from a product for a startup company rather than a large enterprise company.

Cloudflare hired a bunch of folks for sure, but they also fired a lot of folks. What they are doing these days is building products by buying out entire companies, giving them nearly independent authority to build a product like they would build a company.

They've always been this fast. The trick is that they release beta products a lot. Kind of classic "lean" (does anyone remember that?)

My bigger concern would be their increasing grip on a lot of the market, and eventually becoming a monopoly (or part of the big tech "duopoly")

They are working on a set of primitives that make building this kind of software easier. With AI, runtimes matter more than ever and languages matter less.

I find this release relieving because it fills a hole that was really needed. Another hole would be a proper database and improvements to D1.

That's just perception. At the same time they were hiring 1 k. People and hired 2 k. People the year before ( interns).

There was just more news about it than with other companies ( I think they let go about 2 k. People a year ago).

( Not saying it's good, just a little perception balance)

After reading the post, still don't fully understand when you would use CF Queues vs K2. Can you help to elaborate a bit more?

Great product, congratulation on launch. Are you using this internally in any way?

Presumably the Kafka-compatible API that they say is in the works will address this?

Google PubSub is a great product. The primary benefit of K2 is cost, particularly for longer retention periods. Being backed by object storage means that we can store data extremely cheaply compared to disk backed solution, and we pass that on in our pricing.

Compared to self-hosted or cloud-hosted Kafka (e.g., Amazon MSK or Confluent), K2 is much cheaper, and fully serverless. There are no clusters to manage or scale, and consistent performance even as you vastly increase the amount of data.

The main downside is produce (and end to end) latency is higher (around 1s p99) than systems that rely on local disk replication, like Kafka.

So it's great if you're trying to move a huge amount of data around, or for use cases where cost is more important than latency.

Ha setup and management is costly. K2 relieves you off that by charging you 0.04/0.04/GB read/write and 0.02/GB/month storage. Pretty useful if your volume is not into multi-GB's a month. GKE pub/sub seems pretty costly by comparison.