$ cat post/tail-minus-f-forever-/-i-git-bisect-to-old-code-/-packet-loss-remains.md

tail minus f forever / I git bisect to old code / packet loss remains


Title: Debugging My First Big Ticket Problem at Work


July 9th, 2007. The year of my first real software engineering job as a platform engineer for a fast-growing startup. I was excited but also nervous—this was the real deal. No more school projects or side hustles. Today’s problem wasn’t about lines of code; it was about shipping something that actually worked and kept users happy.

The issue at hand? A critical bug in our application that had been lurking for months, causing a significant number of our customers to see error messages when trying to access certain features. It was affecting both user experience and revenue, and we needed to find the root cause quickly.

We were using AWS EC2 and S3, which were still relatively new but already essential tools in our stack. The buzz around Hadoop and its potential for big data processing was growing, but it hadn’t quite hit us yet on a practical level. GitHub had just launched, but we were still primarily using Subversion for source control.

Debugging this issue was like trying to find a needle in a haystack, compounded by the fact that our application logs were not as robust or granular as I would have liked. Every request could go through multiple layers of our architecture before reaching its intended destination. This made it incredibly hard to trace the exact point where things went wrong.

To make matters worse, our team was spread across different time zones, making coordination difficult and slow. We relied heavily on IRC for communication, which wasn’t always the most efficient medium for complex discussions or detailed debugging sessions.

I spent days poring over log files, tracing requests through our system, and trying to understand how each piece of code interacted with others. The more I delved into it, the more layers there seemed to be. It was like trying to find a bug in a giant Rube Goldberg machine—a series of interconnected gears that, when something went wrong, led to a cascade of failures.

One night, after working late into the evening, I decided to break away from my usual methods and try a different approach. I started using strace on one of our application servers to trace system calls, hoping it would give me more visibility into what was happening at the kernel level. It turned out to be a game-changer.

With strace, I could see exactly which file handles were being opened and closed, and when they failed. This gave me a clearer picture of where our application might be hitting issues with permissions or file access. As I dug deeper into these logs, one particular message kept popping up: “Permission denied.”

It was then that the lightbulb went off. I had been so focused on high-level application logic and user requests that I hadn’t thought to check basic filesystem permissions. Once we adjusted those, the errors disappeared like magic.

Reflecting on this experience now, it’s clear how much has changed since 2007. Today, tools like ELK Stack or Splunk would make debugging such issues much easier. We also have better logging practices and more robust monitoring systems that can alert us to problems before they become major issues. However, the core skills—of tracing a bug back to its source, breaking down complex systems into manageable pieces, and never giving up—are timeless.

That night was both a nightmare and a learning experience. It taught me the importance of not only understanding the code but also how it interacts with the underlying infrastructure. More than that, it underscored the value of persistence in problem-solving—sometimes you just need to step back, try something different, and not be afraid to ask for help.

In the end, we shipped a fix, and while there were still bumps on the road ahead, I felt a sense of pride in contributing to a solution that improved our platform. It was one of those moments where you realize that all the late nights and endless debugging sessions are worth it when your hard work results in something meaningful.

Debugging this big ticket problem may have been my first major challenge at work, but it certainly wasn’t the last. And looking back, I wouldn’t have traded the experience for anything else.