[chris_money202]

Has nothing to do with Microsoft acquisition... AI usage has increased demand and load. More PRs, more Action runners, more of everything firing. GitHub just wasn't ready for the scale and are now having issues catching up with it as it continues to increase exponentially.

[semiquaver]

This is a convenient lie that GH likes to tell. Growth is nothing like exponential, its at most 300% over several years according to their own public numbers (presented misleadingly on graphs)

But a couple of years ago they were crowing about how much work they were doing to prepare for “a billion developers”. If they had actually done that then the actual load from agents should have been no problem.

[chris_money202]

Is this growth in resource usage or growth in revenue? Because those numbers aren't necessarily coupled. I.e most action runners are free

[semiquaver]

usage

[chris_money202]

There was an x post in another thread under this post that showed all the standard usage numbers are way up: 14x, 2.1x, etc. And the OP hinted at the usage growth being non-linear for 2026

[officialchicken]

Are you sure? Seems like they "completed" a migration about the same time all these problems started to become daily. https://www.theverge.com/tech/796119/microsoft-github-azure-...

[voncheese]

Yeah, that and Microsoft has been slow to move the infrastructure to something that scales better to handle that load.

The more surpassing part is that Microsoft hasn't figured out a way to manage/contain the AI-sourced traffic better so it doesn't create all this noisy neighbor problems for non-AI usage/users.

[chris_money202]

Github's core platform doesn't really make that separation, anything a human can leverage on github an AI agent can as well, just faster and with heavier usage. End of day agents and humans are using the same services.

[voncheese]

Sure, still need to enable access the same info but feels like bucketing the clients into

bucket1 = clients that were working just fine before (users and whatever automation they had in place) bucket2 = ai clients that contributed to, if not flat out caused, the scale problems

then slowing down/limiting the bucket2 clients while keeping the bucket1 clients rolling as-is, is both doable and keeps existing customers happy while the underlying infra gets scale/perf improvements needed to support ai clients at scale.

[lqstuart]

MSFT is also forcing its subsidiaries to “lean into AI” so that they can fire people to cover for Satya’s bad investments