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The August 17 outage

github.blog

561–570 of 804 posts

Re: The August 17 outage

#561
post #531

> Both incidents were capacity failures at their core. We failed to scale critical components before demand exceeded their capacity. This is the wrong way to think about this because there's no such thing as infinite capacity. A large distributed system will be simultaneously mostly idle and (in some subcomponents) overloaded. The root cause is not "a component didn't have enough capacity (because of auto scaling fai…

GH didn't collapse so it's not impossible that they already implement these measures:

> At peak, web/API error rates were approximately 20%, while archive and raw-content downloads reached approximately 50%.

https://www.githubstatus.com/incidents/zkxwbgr0cnmx

Re: The August 17 outage

#563
post #525

Earlier quoted context omitted.

I wondered that myself. Curious as to why they couldn’t shed load at the edge to help protect goodput.

Isn't that what they did though? Start returning more-or-less hardcoded 403s for the Copilot endpoint that was causing the issues?

That’s more surgical than load shedding. With load shedding you intentionally return 503s to a proportion of all legitimate requests. It turns a hard blackout (total outage) into a flakiness issue.

Re: The August 17 outage

#564
post #532

Earlier quoted context omitted.

> raised heat is a kind of pollution > water is not unlimited > you don't want to release a bunch of acid into a river > I know next to nothing about this > I know basically nothing > corn is one of the thirstiest major crops grown in the US What is this rant supposed to inform? Whats wrong with OP being concerned about the costs of operating a DC?

Nobody is concerned about the costs and environmental impact of data centers. When someone in a discussion about the benefits of AI goes "did you think about the environment?!", it's always performative. The real motivation is disliking AI itself or doubt about the government's ability to offset the labor market impact. Discussions that start with feigned concerns being raised are nearly always going to be unproducti…

Wrong.

I don’t dislike AI but really of mine are negatively affected by climate change and AI isn’t helping what is easily observed when Google and MS scrapped their CO2 reduction targets.

So every time I use AI I think about the necessity and usefulness of what I‘m doing with AI and if the use outweighs the costs.

Since the rise of AI the environmental impact doesn’t seem to matter anymore.

I guess because it’s the shiny new toy of the hackernews audience.

Privacy also lost importance given the fact that the same people who refused to give information like their phone number to companies like Google and Meta now upload their whole life to their AIs to asks what should the eat, hyperbolically speaking

Re: The August 17 outage

#565
post #508

Earlier quoted context omitted.

So much more stuff and growing- what it is actually useful for ? Are we getting actually more done than with previous volumes or is it just all wasted energy?

Has anyone noticed an increase in the quality, performance or capabilities of the software they use?

I have. Mostly for the software I use that I maintain myself though :P

Re: The August 17 outage

#566

"Since April, monthly commits have grown from 1.4 billion to 2.9 billion. " Wow, that is some incredible growth in a really short time.

So much more stuff and growing- what it is actually useful for ? Are we getting actually more done than with previous volumes or is it just all wasted energy?

[dead]

Re: The August 17 outage

#567
I wonder how much of the traffic increase is enterprise vs. hobbyists? A 7 hour outage for enterprise customers is really, really bad and it's sad if caused by a mass of non-paying vibe coders. It's becoming absolutely obvious that the unlimited free tier needs to go.

Re: The August 17 outage

#568

> Since April, monthly commits have grown from 1.4 billion to 2.9 billion Bonkers. You can tell the entire industry is in a "productivity panic" and here's more proof. There's a velocity zealot crying tears of joy somewhere.

Bonkers is right. Where in those ~12 billion commits is the software, products and "innovations" which are supposed to be making our lives better? Software and apps in particular are getting worse, normies hate AI more than ever because they're even less likely to get their desired outcome when calling their doctor or trying to get their online order refunded when chatting with a cutely named chatbot, wages for (most…

As a hobby I am playing around with mesh radios using Lora.

Let me tell you, it is _silly_ the amount of vibe-coded software in this area is popping up every week. Is the software duplicated? To an extremely large extent, yes. It is useful? Yes, but each piece of software seems to have a smaller and smaller audience, and quality is often severely lacking.

Iv'e done my own, too, for "RF debugging" as I called it to look into SNR issues related to interference. The software getting produced is likely useful _somewhere_, its just that youre not going to notice it.

Are we just moving towards personalised digital assistants for everyone, which in turn will produce software to function? Not unlikely.

Re: The August 17 outage

#569
post #414

Earlier quoted context omitted.

This comment comes up over and over again and it's incredibly ignorant. To give just a single example, ai code dev has enabled people to make tools for themselves that they didn't have before. I've made a language learning app for myself. Its working better than Duolingo so far, for me. Its not really public

On the topic of translation/ language learning, I still find Google Translate better for when I need to type emails in Russian (my older family who only speak it) as far as grammar is concerned than what LLMs spit out.

The transformer was invented as a machine-translation algorithm, later adapted to create LLMs. I think it's a reasonable hypothesis that a ML system designed for translation will always beat an LLM role-playing a translation system (assuming equal computing power and engineer effort).

We're going to see is a lot of stuff people use LLMs for moving back to using bespoke algorithms solving the one specific issue. LLMs are just machine learning unlocked for the masses, where you can ask it "translate this for me", "what's the sentiment of this text", and it just does it. Any of these were already achievable before LLMs, they just needed a machine learning engineer to implement.

I myself started an LLM driven project to classify and sort all the photos I've got. I just ask an LLM to poop out tags for an image. Using a proper algorithm for this is possible, but I'd need to put in some effort to actually get it set up. LLMs do make it easier since they can directly, instructively help you that set up, and provide an easy stream of training data to distill out a model perfectly fit to your usecase.

I think majority of work currently going through LLMs is such inefficient tasks that can be solved quicker and better with a limited algorithm.

You don't need a chatbot.

Re: The August 17 outage

#570
post #559

Earlier quoted context omitted.

I’m getting a lot more done. Hobby projects that languished for years are coming along great, at quality and depth I could never have found time for before.

It's starting to become a cliché to have people reply "I'm getting a lot more done", but without seeing any evidence of this incredible productivity gains, I'm starting to wonder if y'all are suffering from collective hallucination. If the accepted claims are of "100x productivity" (increasing by the day), and LLMs have gotten very good for the past ~year, for sake of argument, where are the 100 year improvements in…

I've heard people use the same word, I was dubious but they did produce some stuff, yet I think that it ends up as an itch-project. You're satisfied you saw the thing emerge into existence but that's about it. No more drive after that. Maybe because LLM don't require you to have a real long term intense need for that thing.
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