It can be achieved with a zero-knowledge proof - there are many schemes, but in essence, they all allow you to prove something (e.g. your birthdate, validated by a government agency), without revealing who you are. You can prove to a third party "the government authenticated that I was born on 1970-01-01" without exposing who "I" is.
Some worthwhile reading on the topic if you're interested:
> And you will never know code as well as a reader and you would have as the author for anything larger than a very small project.
This feels very true - but also consider how much code exists for which many of the current maintainers were not involved in the original writing.
There are many anecdotal rules out there about how much time is spent reading code vs writing. If you consider the industry as a whole, it seems to me that the introduction of generative code-writing tools is actually not moving the needle as far as people are claiming.
We _already_ live in a world where most of us spend much of our time reading and trying to comprehend code written by others from the past.
What's the difference between a messy codebase created by a genAI, and a messy codebase where all the original authors of the code have moved on and aren't available to ask questions?
Or shard it - divide your objects up based on some criteria (hash the name of the object, use the first N digits of the hash to assign to a shard), and distribute them across multiple redis instances. Yes, you then need to maintain some client code to pick the right redis instance to fetch from, but you can now pick the most $/memory efficient instance types to run redis, and you don't have to worry about introducing disk read latency and the edge cases that brings with it.
Edit: looks like redis has some built-in support for data sharding when used as a cluster (https://redis.io/docs/latest/commands/cluster-shards/) - I haven't used that, so not sure how easy it is to apply, and exactly what you'd have to change.
To add another anecdote to this thread, a few years ago, I picked up an old Consew 226R compound walking foot machine to do canvas work for a boat. That machine was a beast once I tuned it. Fast, powerful, smooth, quiet, and with a servo motor, had awesome slow and high speeds, would punch through anything. Its only real downside was the size, and it only did straight stitches. For canvas work, that was everything I needed.
I later picked up a Sailrite LSZ to do some zigzag work on sails. Compared to the Consew, the sailrite feels really clunky, even with the Sailrite servo motor upgrade. It's relatively rough and noisy compared to the Consew, and has less power. Main upsides are the size, and the zigzag stitch for sail work where you need some stretch.
I've ultimately kept the Sailrite because it's still pretty solid, and can be stored on the boat where I need it the most. If I was doing upholstery or canvas work in a permanent shop, I would've kept the Consew, hands down, it was a much more capable and pleasant machine.
The walking foot feature is very useful for heavy materials. I tried sewing light-weight materials on both of these machines and it was awful (bunching, tearing on the foot, can't use really fine needles, etc).
My company is in a similar situation - have large teams in several eastern European cities (primarily Minsk), and a few long-term remote teammates in Ukraine. A couple have fled (from Kyiv) with children, others are worried about being conscripted. It makes me want to vomit just thinking about it. I'm amazed many of them are still on Slack and making PRs.
We're fortunate some of our leadership has quite close ties to the area, so our company's response so far has been extremely understanding.
Some worthwhile reading on the topic if you're interested:
https://en.wikipedia.org/wiki/Zero-knowledge_proof#Zero-Know...
https://en.wikipedia.org/wiki/Blind_signature
It should even possible to construct a protocol where you can prove that you're over 18 without revealing your birthdate.
Zero-Knowledge Range Proofs: https://eprint.iacr.org/2024/430
"Zero-knowledge range proofs (ZKRPs) allow a prover to convince a verifier that a secret value lies in a given interval."