Why Github Why?

Summary

In this video, the creator highlights the poor state of GitHub Actions runners, focusing on a long-standing bug that led to wasted resources and significant costs for users. The script delves into a history of code neglect, featuring bizarre and inefficient coding practices that have persisted for years. Through humor and frustration, the creator critiques Microsoft's lack of attention to the problem, while illustrating the consequences of outdated code. The video reflects on the absurdity of the situation and calls for change, all while poking fun at the poor engineering decisions made by a multi-billion dollar company.

Takeaways

• 😀 GitHub Actions has been plagued by a long-standing, severe bug that has cost companies significant amounts of money over the years.
• 😀 The root cause of the issue is a problematic function that mismanages sleep intervals and uses excessive CPU resources.
• 😀 The bug originated from a Windows batch file hack dating back 16 years, where ping was used as a workaround to make the system sleep.
• 😀 The function in question, known as 'safe sleep', consumes an excessive amount of CPU when running, making it inefficient and expensive.
• 😀 A single CI job with this bug can run for over 5,000 hours and cost thousands of dollars due to excessive CPU usage.
• 😀 GitHub Actions' CI system costs companies money based on CPU usage, and this bug caused runaway processes, often left unchecked for years.
• 😀 Despite the issue being reported multiple times, GitHub failed to address the bug in a timely manner, with fixes taking over a year to be merged.
• 😀 In February 2022, the bug was replaced with even worse code, exacerbating the problem and causing more issues for users.
• 😀 The fix that finally resolved the bug in 2024 was a simple change in code logic, highlighting the negligence in addressing the issue earlier.
• 😀 Despite the obvious flaws and long-standing nature of the issue, GitHub Actions continues to be widely used, showing a lack of accountability and care from GitHub and Microsoft.

Q & A

What is the main issue discussed in the script?

The main issue discussed is the poor quality of GitHub Action runners, specifically a bug in the code that has persisted for years, causing significant computational and financial issues for users.

How does the speaker describe the code causing the problem?

The speaker humorously describes the code as 'deranged,' 'disgusting,' and 'utterly deranged.' They emphasize how bad the code is by comparing it to bad AI code and highlight how it results in inefficient and costly behavior.

What does the speaker mean by 'cinema' in the context of the code?

The speaker uses 'cinema' as a playful term to refer to the dramatic and almost unbelievable nature of the code and its issues, suggesting that the situation is so absurd it could be a film-worthy moment.

Why does the speaker mention GitHub Actions so negatively?

GitHub Actions is mentioned negatively because it has been plagued by bugs, particularly the 'safe sleep' bug, which has caused GitHub CI to run inefficiently, consuming excessive computational resources and costing users a lot of money.

What is the 'safe sleep' function, and why is it problematic?

The 'safe sleep' function is a piece of code intended to pause execution for a specified time. However, it is problematic because it either uses inefficient methods (like pinging) or causes the CPU to be tied up without performing meaningful tasks, leading to performance issues and high costs.

What impact did this bug have on GitHub Action users?

The bug caused significant delays and resource inefficiency, leading to CI systems becoming backed up and preventing important tasks, like master branch commits, from being processed. This resulted in financial losses for companies relying on GitHub Actions for CI/CD.

What example does the speaker provide to show how expensive the bug was?

The speaker gives an example where a single process ran for over 5,000 hours on a machine, costing around $2,400 in CPU minutes, highlighting the financial burden of the bug.

What solution was proposed to fix the bug, and did it get implemented quickly?

The proposed solution was a simple fix that changed the code logic to prevent the infinite loop from running. However, despite the fix being available, it was ignored and automatically closed for a month before being merged in a year and a half later.

Why does the speaker compare GitHub's response to the bug to a lack of care?

The speaker compares GitHub's response to the bug to a 'cool kid' acting indifferent, suggesting that Microsoft and GitHub have not shown adequate urgency or concern in addressing the issues, despite the serious impact on users.

What does the speaker say about AI and its relationship to code quality?

The speaker humorously suggests that despite AI being a controversial topic in coding, it could never produce code as bad as the GitHub Actions code, restoring the speaker's faith in AI's potential to create more reliable code.