I’m a web dev turned DevOps (with the front end design eye and CSS knowledge of a DevOps! Lol) but this seems like a great place to use a css grid, no?
bignavy
joined 1 year ago
Wish I could upvote more than once. Azure artifacts has some fucky authentication requirements (cleartextpassword is the dumbest field I’ve ever heard of - especially since it’s not clear text or a password, it’s a base64ed PAT) but there’s plenty of first party support to make it less painful, and it’s a problem you only have to ‘fix’ once.
Our prior solution was verdaccio for NPM and a shared drive location for Nuget, and….well, it beats the tar out of either of those. Being able to see exactly what’s in the feed, when it got there, who put it there….all grade a stuff. Handling SSO and such seamlessly is nice too, and being able to scope access with tons of granularity….well it seems like a rake waiting to be stepped on, honestly, but if you need to manage access it seems like a big win.
Public feeds - yes. Why reinvent the wheel? Will be easier to find and use if it’s on nuget.org.
If OP’s goal is to be able to source control all the public packages that their projects use, for security or peace of mind purposes (or to make it the sole source of packages to avoid dependency injection/confusion attacks)…there’s actually a feature of Azure Artifacts where you can pull packages from an ‘upstream’ like nuget.org and host public packages in a private feed. It’s got a gui, and it’s pretty convenient as far as such things go.
Junior-ish DevOps with some blue/green experience.
It’s a very thorny problem, and I think your willingness to put up with the trade offs really would drive what patttern of architectecture.
Most of our blue/green deployment types use a unitary database behind the backend infra. There’s a lot ways to implement changes to the database (mostly done through scripting in the pipeline, we don’t typically use hibernate or other functionality that wants to control the schema more directly), and it avoids the pain of trying to manage consistency with multiple db instances. It helps that most of our databases are document types, so a lot of db changes can be implemented via flag. But I’ve seen some SQL implementations for table changes that lend themselves to blue/green - you just have to be very mindful to not Bork the current live app with what you’re doing in the background. It requires some planning - not just “shove the script into source control and fire the pipeline.”
If we were using SQL with a tightly integrated schema and/or we couldn’t feature flag, I think we’d have to monkey around with blue/greening the database as well. But consistency is non trivial, especially depending on what kind of app it is. And at least one time when a colleague set up a database stream between AWS accounts, he managed a circular dependency, which….well it wasn’t prod so it wasn’t a big deal, but it easily could’ve been. The data transfer fees are really what kills you. We managed to triple our Dev AWS bill prototyping some database streams at one point. Some of it undoubtedly was inefficient code, but point stands. With most blue/green infra, your actual costs are a lot less than 2x what a ‘unitary’ infra would cost, because most infra is pay for use and isn’t necessary except when you go to deploy new code anyway. But database consistency, at least when we tried it, was way MORE expensive than just 2x the cost of a unitary db, because of the compute and transfer fees.
Wants is doing some heavy lifting on this one.
I want to date Taylor Swift by 2030. Where’s my national media coverage?!?
Like the SEAL who became a doctor and then went to space. Don’t feel like you have to limit yourself, you know?
So glad I Xited right after Musk’s purchase was finalized. My days are freer and my conscience is clear!
You didn’t expect the world to say hello back, did you?
Hello you!
Oh yeah, well I’ll make my own community! With blackjack! And hookers! You know what, forget the community and the blackjack! Aw, forget the whole thing.
I watched it in Vim, mostly because I don’t hate myself enough.
Not to spoil the ending either, but the nuclear device goes off because Oppenheimer smashes a bunch of keys and then finally remembers :wq.
Tech doesn’t really self select for well balanced, socially confident, neurologically normal folks.
I’m sure those people are in tech and have success as well, but the stereotype of the “hacker nerd” didn’t spring out of nothing. The obsessiveness and desire to be right and know everything that make IT geniuses can also make those same folks really, really hard to be around.
People that are ostracized for their socially aberrant behavior usually (not always!) have sympathy for other outcast groups, whatever the reason.
And you’re right, too - writing code is sort of one of those ultimate bullshit tests - either it works, or it doesn’t. Computers don’t care about your pedigree or your appearance or even your personality. Nice guys who write shit code might have management or product team in their future, but they don’t usually write code for very long. But good devs are hard to find, so even the most straight laced companies are willing to bend a bit when it comes to talented developers.
My $.02, and worth every penny 😂
Just because it's 'the hot new thing' doesn't mean it's a fad or a bubble. It doesn't not mean it's those things, but....the internet was once the 'hot new thing' and it was both a bubble (completely overhyped at the time) and a real, tidal wave change to the way that people lived, worked, and played.
There are already several other outstanding comments, and I'm far from a prolific user of AI like some folks, but - it allows you to tap into some of the more impressive capabilities that computers have without knowing a programming language. The programming language is English, and if you can speak it or write it, AI can understand it and act on it. There are lots of edge cases, as others have mentioned below, where AI can come up with answers (by both the range and depth of its training data) where it's seemingly breaking new ground. It's not, of course - it's putting together data points and synthesizing an output - but even if mechanically it's 2 + 3 = 5, it's really damned impressive if you don't have the depth of training to know what 2 and 3 are.
Having said that, yes, there are some problematic components to AI (from my perspective, the source and composition of all that training data is the biggest one), and there are obviously use cases that are, if not problematic in and of themselves, at very least troubling. Using AI to generate child pornography would be one of the more obvious cases - it's not exactly illegal, and no one is being harmed, but is it ethical? And the more societal concerns as well - there are human beings in a capitalist system who have trained their whole lives to be artists and writers and those skills are already tragically undervalued for the most part - do we really want to incentivize their total extermination? Are we, as human beings, okay with outsourcing artistic creation to this mechanical turk (the concept, not the Amazon service), and whether we are or we aren't, what does it say about us as a species that we're considering it?
The biggest practical reasons to not get too swept up with AI is that it's limited in weird and not totally clearly understood ways. It 'hallucinates' data. Even when it doesn't make something up, the first time that you run up against the edges of its capabilities, or it suggests code that doesn't compile or an answer that is flat, provably wrong, or it says something crazy or incoherent or generates art that features humans with the wrong number of fingers or bodily horror or whatever....well then you realize that you should sort of treat AI like a brilliant but troubled and maybe drug addicted coworker. Man, there are some things that it is just spookily good at. But it needs a lot of oversight, because you can cross over from spookily good to what the fuck pretty quickly and completely without warning. 'Modern' AI is only different from previous AI systems (I remember chatting with Eliza in the primordial moments of the internet) because it maintains the illusion of knowing much, much better.
Baseless speculation: I think the first major legislation of AI models is going to be to require an understanding of the training data and 'not safe' uses - much like ingredient labels were a response to unethical food products and especially as cars grew in size, power, and complexity the government stepped in to regulate how, where, and why cars could be used, to protect users from themselves and also to protect everyone else from the users. There's also, at some point, I think, going to be some major paradigm shifting about training data - there's already rumblings, but the idea that data (including this post!) that was intended for consumption by other human beings at no charge could be consumed into an AI product and then commercialized on a grand scale, possibly even at the detriment of the person who created the data, is troubling.
For a second I thought my github was going viral. ;)
This is a hilarious (and interesting!) read.
As a young(er) and slightly shittier web developer, before I really understood or could implement promises effectively (or when my code would 'race' and fail to recognize that the DOM hadn't been loaded yet, so I couldn't attach event listeners yet), I was known to implement a 2 second timeout.
It wasn't pretty, but it worked!