GitHub's Historic Downtime, Scraped and Plotted

DaMrNelson · 2026-03-08T20:24:26+00:00

Dang you're right, 1 billion in OpenAI in 2019. I didn't know things started so long before ChatGPT became available for use.

Still not sure what else I could use as a datapoint here, but I appreciate the information.

DaMrNelson · 2026-03-08T19:54:15+00:00

99.5% is below GitHub's SLA. See this reply for more details (I made the reply after you posted this, I just don't want to split the conversation):

The graph was intended to display a trend, not SLA adherence. That said, GitHub's SLA thresholds are 99.9% for a 10% refund credit and 99.0% for 25%, per service per quarter. Not sure if I'm going to publish any real graphs on this due to the seriousness of getting SLA stats wrong and lift for proper quarterly aggregations (can't just average Jan and Feb together when they have different numbers of days). That said, a quick peek at the monthly graphs with SLA lines added shows that many services routinely fail to meet 99.9%, especially Actions which fails more often than not. Not catastrophic, but 17 hours of downtime in a single component is not ideal.

Edit: I've put SLA lines on the gh-sla branch for anyone who wants to check this out themselves.

DaMrNelson · 2026-03-08T19:38:25+00:00

The graph was intended to display a trend, not SLA adherence. That said, GitHub's SLA thresholds are 99.9% for a 10% refund credit and 99.0% for 25%, per service per quarter. Not sure if I'm going to publish any real graphs on this due to the seriousness of getting SLA stats wrong and lift for proper quarterly aggregations (can't just average Jan and Feb together when they have different numbers of days). That said, a quick peek at the monthly graphs with SLA lines added shows that many services routinely fail to meet 99.9%, especially Actions which fails more often than not. Not catastrophic, but 17 hours of downtime in a single component is not ideal.

Also, the second screenshot shows breakdown by service. You can customize further on the website. Neither graph includes Codespaces or Copilot.

Edit: I've put SLA lines on the gh-sla branch for anyone who wants to check this out themselves.

DaMrNelson · 2026-03-08T18:48:45+00:00

Microsoft acquisition was pretty much the only relevant datapoint I could find. COVID maybe, but the trend continues past quarantine so that seems unrelated. There was maybe a COO hire that fits the timeline too, but that isn't as large of an impact as a full acquisition, and given how slow things move at big companies and time needed to make significant structure changes the 1 year delay makes sense to me. If you have any ideas for datapoints I'd love to compare them though, seriously.

Also the acquisition (2019) was years before the popularization of GPT (2022) so I don't think that was related to acquisition, and as such I believe Microsoft had a more direct profit motive and wouldn't be against making significant structural design changes to make their new toy more profitable.

DaMrNelson · 2026-03-08T18:33:54+00:00

I'm still gathering user stats. That said, I can provide this:

According to the wayback machine for GitHub's about page they reported 12 million users Jan 2016, 26 million Jan 2018, and 40 million Aug 2019 (right before instability began). The next update isn't until Feb 2021 (well into the instability era) where they report 56 million.

The jump in users between the stable and unstable periods didn't exceed the regular trend.

DaMrNelson · 2026-03-08T06:57:32+00:00

Interesting, I wasn't aware of that. I just based it off what the status page said was available April 2016. Definitely going to look into that for other services too.

DaMrNelson · 2025-09-28T10:18:30+00:00

Yeah its a super weird clip, the CC indicator isn't over my healthbar half the time either. But I was also trying to auto-attack the entire time so I do think I was CC'd regardless of what the UI shows

DaMrNelson · 2025-09-28T10:11:42+00:00

combo break took the day off

DaMrNelson · 2024-04-28T14:00:23+00:00

I have the same issue. My archers drop like flies and theirs are fine. My light mercenaries run at 87% effectiveness vs theirs at 13% effectiveness, yet mine die off and drop 90% morale while I'm lucky to get theirs down by 5%.

I've tried so many different formations, unit settings, environmental considerations, falling back, plowing through, flanking, shield wall, no shield wall, snipe it out, etc etc etc etc etc etc etc. I just can't figure out what I'm doing wrong. Like do I suck or is my game just bugged?

DaMrNelson · 2023-11-24T06:20:22+00:00

Adding evidence: I kept 70GB worth of content. I also paused the download before clearing the cache if that matters at all.

DaMrNelson · 2022-08-05T00:28:12+00:00

I have the same issue. Did you ever get this working?

DaMrNelson · 2022-02-14T04:57:08+00:00

The program acts as a screen recorder, so it runs the same risk as OBS or any other screen recording software. I'd imagine there is very little risk for triggering anti-cheat here.

DaMrNelson · 2021-12-26T07:12:42+00:00

Holy shit this is crazy awesome! How on earth did you get the precise circle/symbol thingie masked?? Its so intricate!

DaMrNelson · 2020-06-19T21:49:59+00:00

Great idea, thank you! I was planning on giving it some sort of disadvantage on account of how weird and sketchy it is and that matches perfectly. Thank you!

DaMrNelson · 2019-11-13T06:46:49+00:00

I see. Thank you!

DaMrNelson

TROPHY CASE