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luhn

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The focus of this seems to be entirely AI agents, but I wonder if there's a future where browsers implement this and us humans can finally get micropayments in the web. It's been tried unsuccessfully many times but always falls prey to the chicken-and-egg problem. Maybe the AI hype will finally give it the push it needs for widespread deployment.

I can't tell you why Fargate is so slow, but the reason Lambda containers are so fast is because it doesn't actually load the image. It loads a manifest of the layers and the files in each, and then each file is loaded on-demand from a multi-tier cache. 90% of the image is never loaded, and 90% of the remainder is served from local cache. It's a pretty cool architecture.

I can't make sense of your comment, but whatever you're trying to get at is wrong: Table sugar is sucrose. Corn syrup is mostly glucose and contains no fructose. HFCS is commonly produced at 42% and 55% fructose formulations. I don't think HFCS is meaningfully more or less harmful than any other sugar, but chemically there's a significant difference.

GPT-5.2 7 months ago

That's hilarious and right on brand for Google that they spend millions developing cutting-edge technology and fumble the ball making a chat app.

IIRC the wisdom of the time cloud started becoming popular was to always be on-prem and use cloud to scale up when demand spiked.

I've heard that before but was never able to make sense of it. Overflowing into the cloud seems like a nightmare to manage, wouldn't overbuilding on-prem be cheaper than paying your infra team to straddle two environments?

That's exactly what they're doing, it's just driving engagement for their sales:

While Git makes an interesting database alternative for specific use cases, your production applications deserve better. Upsun provides managed PostgreSQL, MySQL, and other database services

Like most ALTER TABLE subcommands, you need an exclusive lock on the table while the catalog is updated. But no table scan or rewrite is required, so that lock is sub-second and can usually be done without disrupting a live application.

The improvements to migrations have been the biggest boon for running even modestly-sized Postgres DBs. It wasn't that long ago that you couldn't add a column with a default value without rewriting the whole table, or adding NOT NULL without an exclusive lock while the whole table was scanned. That becomes unfeasible pretty quickly.

You don't need to optimize anything beyond appropriate indices, Postgres can handle tables of that size out of the box without breaking a sweat.

By Jan 2024, our largest table had roughly 100 million rows.

I did a double take at this. At the onset of the article, the fact they're using a distributed database and the mention of a "mid 6 figure" DB bill made me assume they have some obscenely large database that's far beyond what a single node could do. They don't detail the Postgres setup that replaced it, so I assume it's a pretty standard single primary and a 100 million row table is well within the abilities of that—I have a 150 million row table happily plugging along on a 2vCPU+16GB instance. Apples and oranges, perhaps, but people shouldn't underestimate what a single modern server can do.

A synchronous replica via WAL shipping is a well-worn feature of Postgres. I’d expect RDS to be using that feature behind the scenes and would be extremely surprised if that has consistency bugs.

Two replicas in a “semi synchronous” configuration, as AWS calls it, is to my knowledge not available in base Postgres. AWS must be using some bespoke replication strategy, which would have different bugs than synchronous replication and is less battle-tested.

But as nobody except AWS knows the implementation details of RDS, this is all idle speculation that doesn’t mean much.

It's not mentioned in the headline and not made super clear in the article: This is specific to multi-AZ clusters, which is a relatively new feature of RDS, and differ from multi-AZ instance that most will be familiar with. (Clear as mud.)

Multi-AZ instances is a long-standing feature of RDS where the primary DB is synchronously replicated to a secondary DB in another AZ. On failure of the primary, RDS fails over to the secondary.

Multi-AZ clusters has two secondaries, and transactions are synchronously replicated to at least one of them. This is more robust than multi-AZ instances if a secondary fails or is degraded. It also allows read-only access to the secondaries.

Multi-AZ clusters no doubt have more "magic" under the hood, as its not a vanilla Postgres feature as far as I'm aware. I imagine this is why it's failing the Jepsen test.

I get your point, but that's a terrible example because Boise is one of the fastest growing metro areas in the country.

`TAKE LOCK ACCESS EXCLUSIVE VACUUM FULL` is just an incantation that will be blindly copy-pasted. I don't see how it would stop anyone from shooting themselves in the foot.