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prpl

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Knoppix 22 days ago

I built a 40 (later 80) node cluster with clusterknoppix ~2006 to run a bunch of physics simulations off of old library computers after I replaced a bunch of PSU fans. Kept my cubicle toasty until we moved them into a random subterranean room I think was used for some early nuclear research at university.

SAT isn’t an IQ test, and probably all sorts of people took it before they had cultural awareness or a diagnosis that would have lead to different testing conditions had it been taken after diagnosis, let alone the fact that test scores are not comparable.

GPAs similarly not comparable over large time ranges, schools, or degrees without normalization you can’t get.

The real core of infrastructure monitoring isn’t dashboards. It’s the alerts.

“it’s not X it’s Y”

at this point when I see this pattern in writing I assume most if not all of it is AI generated - same with em-dashes.

This is not to discount the idea that alerts are more important than dashboards (I work directly in observability) - but just to say that I personally shut off reading anything else with these patterns because, generally speaking, the rest of the content is just not original or interesting.

S3 Files 3 months ago

For files up to 100kB of size, this should effectively be really close to the same price as S3 when writing (didn't check reading so much, but the writes/PUT is always much more expensive than read/GET)

Would be really useful pre-compaction and to deal with small files issue without latency penalties

I find the people who end up with spaghetti code did so because they didn’t translate their normal processes over.

Being completely methodical about development really helps. obra/superpowers, for example, gets close but I think it overindexes on testing and doesn’t go far enough with design document templates, planning, code style guides, code reviews, and more.

Being methodical about it takes more time, but prevents a good bit of the tech debt.

Planning modes help, but they are similarly not methodical enough.

The sklearn to me is (and mirrors) the insane amount of engineering that exists/existed to bring Jupyter notebooks to something more prod-worthy and reproducible. There’s always going to be re-engineering of these things, you don’t need to use the same tools for all use cases

I don’t think that’s what it would look like at all. The first stages would be cheap - mostly requirements gathering and research, but a bit more focus on that. A bit more time would be spent up front, but then you’d see multiple proposals being built, from that multiple plans being built, and finally multiple implementations to choose from. You might see A/B testing of multiple implementations or even products, and then a decision on which to pursue. You could move in multiple dimensions concurrently.

I’m not sure this is agile. I’m not sure it’s a waterfall.

We’ve got bounds on our infinite typing monkeys, but they increase every day

Waterfall came out when hardware and software had to be developed together, and appealed to traditional Engineering practitioners. You are right though, when the hardware constraints went away, software (more code) was cheaper and easier to ship in increments and iterate. But feature-rich products were still difficult to ship - and you had to pick and choose what things to spend your time on.

The SaaS-pocalypse is occurring versus investors don’t believe that to be true anymore.

I think they will still be wrong because ultimately people want people (particularly experts) to be held accountable for things - shipping high stakes software, running company ERPs/CRMs, and more.

Agile itself is predicated on software being difficult to ship/expensive. It might not make sense to continue (waterfall might be better actually)

The real problem is that company decisions will never be made as fast as software can be written (and rewritten) now.