Scaling a system as vast as GitHub involves intricate processes to manage the complex stack effectively and mitigate potential ripple effects from small changes. GitHub employs various tools like Datadog for monitoring event metrics, Splunk for analyzing context details, MySQL for data storage, Scientist for testing changes, and Flipper for controlled rollouts. An example of their optimization efforts includes improving SQL query performance by testing alternative code blocks, which significantly reduced timeout issues. This practice is supplemented by a focus on removing or optimizing unused code, as demonstrated by their work on simplifying Rails controller actions to enhance request latency. The strategic use of observability tools, such as Datadog and Splunk, and a methodical approach to testing and implementing changes, allows GitHub to proactively address performance issues before they escalate into major problems, ensuring a more stable and efficient system for developers and users alike.