karlmdavis

I love absolutely everything about this… except for the lack of cross-platform support. I know how ludicrous it is to expect that, but… most workflows I’m considering solutions like this for are crippled by their inability to run Xcode or a native Windows build. Heck, I’m pretty sure I’ll even run into glibc version mismatches that block work I care about.

Frustrating that the best solution is still, “well, if that’s important to you, then set that up in your home lab or rent some extra (pet) VMs in the cloud.”

I would take the other side of that bet.

  # if >10 then was_created_by_agent = true
  $ grep -oP '\p{Emoji}' vulns.md | wc -l

I find it kind of baffling that this toolkit is so popular when it makes handling database joins so difficult. After bashing my head against it for a while, I moved to Diesel, and while that has its own set of problems, I am generally able to get through them without resorting to horrible hacks or losing compile time checks.

I suspect they meant “scenario”.

I almost gave up on Leptos, because I was trying to use it with Actix, which it supports less-well than it does Axum (and I’m too stubborn for my own good and wouldn’t switch).

I came back to it recently after the Leptos 0.7 release, though, and it’s MUCH smoother.

Still early days for a framework like this, but I think it’s got a lot of magic.

What an absolutely delightful little project and write up.

A number of US federal agencies still have astonishing amounts of it. The world’s largest insurer, Medicare, uses 10M+ lines of COBOL to process the claims it receives — total dollar amounts that make up 3% of the yearly GDP.

Maintaining and modernizing these critical systems is important work.

From personal experience, it scales very well vertically. Have a system in production with tens of billions of rows and north of 12 TB of storage total. That system is read-heavy with large batched inserts, not many deletes or updates.

Biggest limiter is memory, where the need for it grows linearly with table index size. Postgres really really wants to keep the index pages hot in the OS cache. Gets very sad and weird if it can’t: will unpredictably resort to table scans sometimes.

We are running on AWS Aurora, on a db.r6i.12xlarge. Nowhere even close to maxed out on potential vertical scaling.

You and I must work in very different contexts, as these questions are so obvious that they first seemed like satire to me.

You enforce API contracts in a monolith (or any codebase, really) via an at-least-modest amount of typing and a compiler. You diagnose performance issues via any number of tools, prominently including metrics and profilers.

My context for this is a lot of years working with backend languages like Java, Rust, etc. though the same assurances and tooling are available for most every platform I’m aware of.

Looks perfect for me with one show stopper: no Home Kit support. I love the idea of Home Assistant but do not have the free time to pick up another service to support in our house.

Nu is using a data frame abstraction to drive this and it’s really quite powerful and fast.

I was rather skeptical on the value of having this stuff as a shell built in, but it won me over. Very convenient!

I’ve used Synthea for a whole assortment of small and large projects and it’s been boring in the best possible way: reliable and easy to use.

I’ve also had the pleasure of working directly with the team at MITRE that owns it on a consulting engagement (we needed some improvements to it) and they are a delight to work with.

I don’t really understand how any file system designed in the last 20 years could be lacking data checksums. Data integrity is job #1, and yet.

“Year of Efficiency”? Hoo boy… is Zuck picking up his management strategies from a podcast/YouTube channel? I mean, I shouldn’t/wouldn’t be surprised by that but still, wow. Playing in the kiddie pool.

(Strongly reminiscent of the Cortex podcast’s “yearly themes”. Which I like! But… I’m not running one of the world’s largest companies, am I?)