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From S3 to R2: An economic opportunity

dansdatathoughts.substack.com

51–60 of 183 posts

Re: From S3 to R2: An economic opportunity

#51

Cloudflare has been attacking the S3 egress problem by creating Sippy: https://developers.cloudflare.com/r2/data-migration/sippy/ It allows you to incrementally migrate off of providers like S3 and onto the egress-free Cloudflare R2. Very clever idea. He calls R2 an undiscovered gem and IMO this is the gem's undiscovered gem. (Understandable since Sippy is very new and still in beta)

Author here and really cool link to Sippy. I love the idea here since you're really migrating data as needed so the cost you incur is really a function of the workload. It's basically acting as a caching layer.

Re: From S3 to R2: An economic opportunity

#52
Should we simply ignore the tremendous amount of phishing hosted using r2.dev? Or is this also part of "an economic opportunity"?

Cloudflare may well be on their way to becoming a monopoly, but they certainly show they don't care about abuse. Even if it weren't a simple matter of principle, in case they aren't successful in forcing themselves down everyone's throats, I wouldn't want to host anything on any service that hosts phishers and scammers without even a modicum of concern.

Re: From S3 to R2: An economic opportunity

#53

The other hidden cost when you are working with data hosted on S3 is the LIST requests. Some of the data tools seem very chatty with S3, and you end up with thousands of them when you have small filed buried in folders with a not insignifcant cost. I need to dig into it more, but they are always up there towards the top of my AWS bills.

[deleted]

Re: From S3 to R2: An economic opportunity

#54
post #26

Earlier quoted context omitted.

What are the economics that Amazon and other providers have egress fees and R2 doesn't? Is it acting as a loss leader or does this model still make money for CloudFlare?

also, egress fees are a sort of vendor lock-in, because getting data out of the cloud is vastly more expensive then putting new data into the cloud..

The big cloud providers are Hotel California - you can check in but you can't check out.

Of course you can (like Snap) but it's a MASSIVE engineering effort and initial expense.

Re: From S3 to R2: An economic opportunity

#55

OP is missing that a correct implementation of Databricks or Snowflake will have those instances are running inside the same AWS region as the data. That's not to say R2 isn't an amazing product, but the egregious costs aren't as high since egress is $0 on both sides.

Author here and it is true that costs within a region are free and if you do design your system appropriately you can take advantage of it but I've seen accidental cases where someone will try to access in another region and it's nice to not even have to worry about it. Even that can be handled with better tooling/processes but the bigger point is if you want to have your data be available across clouds to take advantage of the different capabilities. I used AI as an example but imagine you have all your data in S3 but want to use Azure due to the OpenAI partnership. It's that use case that's enabled by R2.

Re: From S3 to R2: An economic opportunity

#56

Earlier quoted context omitted.

What are the economics that Amazon and other providers have egress fees and R2 doesn't? Is it acting as a loss leader or does this model still make money for CloudFlare?

Amazon doesn't have unit cost for egress. They charge you for the stuff you put through their pipe, while paying their transit providers only for the size of the pipe (or more often, not paying them anything since they just peer directly with them at an exchange point). Amazon uses $/gb as a price gouging mechanism and also a QoS constraint. Every bit you send through their pipe is basically printing money for them,…

Honest question, how is this different than a toll road? An entity creates a road network with a certain size (lanes, capacity/hour, literal traffic) and pays for it by charging individual cars put through the road.

Re: From S3 to R2: An economic opportunity

#57

OP is missing that a correct implementation of Databricks or Snowflake will have those instances are running inside the same AWS region as the data. That's not to say R2 isn't an amazing product, but the egregious costs aren't as high since egress is $0 on both sides.

I could be mistaken, but I believe AWS would still charge for one direction of an S3 to Databricks/Snowflake instance/cluster.

Re: From S3 to R2: An economic opportunity

#58

Earlier quoted context omitted.

Amazon doesn't have unit cost for egress. They charge you for the stuff you put through their pipe, while paying their transit providers only for the size of the pipe (or more often, not paying them anything since they just peer directly with them at an exchange point). Amazon uses $/gb as a price gouging mechanism and also a QoS constraint. Every bit you send through their pipe is basically printing money for them,…

You don't get charge for transit if you are sending stuff IN from the internet or to any other AWS resource in that region. So there is no QOS constraint inside except for perhaps paying for the S3 GET/SELECT/LIST costs. It is pretty much exclusively to lock you into their services. It heavily impacts multi-cloud and outside of AWS service decisions when your data lives in AWS and is taxed at 5-9 cents a GB to come o…

Author here - have you tried using R2? As others mentioned there's also Sippy (https://developers.cloudflare.com/r2/data-migration/sippy/) which makes this easy to try.

Re: From S3 to R2: An economic opportunity

#59
post #28

> In fact, there’s an opportunity to build entire companies that take advantage of this price differential and I expect we’ll see more and more of that happening. Interesting. What sort of companies can take advantage of this?

Basically any company offering special services that work with very large data sets. That could be a consumer backup system like Carbonite or a bulk photo processing service. In either case, legal agreements with customers are key, because you ultimately don't control the storage system on which your business and their data depend.

I work for a non-profit doing digital preservation for a number of universities in the US. We store huge amounts of data in S3, Glacier and Wasabi, and provide services and workflows to help depositors comply with legal requirements, access controls, provable data integrity, archival best practices, etc.

There are some for-profits in this space as well. It's not a huge or highly profitable space, but I do think there are other business opportunities out there where organizations want to store geographically distributed copies of their data (for safety) and run that data through processing pipelines.

The trick, of course, is to identify which organizations have a similar set of needs and then build that. In our case, we've spent a lot of time working around data access costs, and there are some cases where we just can't avoid them. They can really be considerable when you're working with large data sets, and if you can solve the problem of data transfer costs from the get-go, you'll be way ahead of many existing services built on S3 and Glacier.

Re: From S3 to R2: An economic opportunity

#60
post #28

> In fact, there’s an opportunity to build entire companies that take advantage of this price differential and I expect we’ll see more and more of that happening. Interesting. What sort of companies can take advantage of this?

Author here but some ideas I was thinking about: - An open source data pipeline built on top of R2. A way of keeping data on R2/S3 but then having execution handled in Workers/Lambda. Inspired by what https://www.boilingdata.com/ and https://www.bauplanlabs.com/ are doing. - Related to above but taking data that's stored in the various big data formats (Parquet, Iceberg, Hudi, etc) and generating many more combinations of the datasets and choose optimal ones based on the workload. You can do this with existing providers but I think the cost element just makes this easier to stomach. - Abstracting some of the AI/ML products out there and choosing best one for the job by keeping the data on R2 and then shipping it to the relevant providers (since data ingress to them is free) for specific tasks. -
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