$ cat post/packet-loss-at-dawn-/-i-typed-it-and-watched-it-burn-/-i-miss-that-old-term.md
packet loss at dawn / I typed it and watched it burn / I miss that old term
Title: A Day in the Life of Ops: Chaos Engineering vs. DevOps
November 15, 2010 was just another day for me at my job as an infrastructure engineer, but it felt like a lot was going on in the tech world. The term “DevOps” was starting to gain traction, and I could feel the buzz around it—though I still had my doubts about whether it was really just another management fad. Chef and Puppet were duking it out in the config management wars, with Netflix making waves in chaos engineering. OpenStack’s launch, Heroku being sold to Salesforce, and continuous delivery books like “Continuous Delivery: Reliable Software Releases through Automated Build and Test” were all part of the tech zeitgeist that day.
But what really had my attention was when I found myself arguing a heated discussion with one of our development leads about how we could improve our deployment processes. The conversation turned to chaos engineering, a concept pioneered by Netflix, which seemed like a no-brainer for us. We were still dealing with the occasional outage due to human error or bad configuration changes—why not use some of these techniques to shake things up and see what breaks?
“Brandon,” my lead asked, “what do you think about running some chaos experiments?”
I hesitated. I had seen Netflix’s approach in action, but it felt like a risky proposition. “Well, we can’t just start randomly breaking stuff without a plan,” I said, trying to sound authoritative. “We need to have some fail-safes and monitoring in place.”
“Agreed,” he replied. “But the goal is to catch these issues before they become real problems, right?”
I nodded slowly. “Okay, let’s do it then. But we should start small. Maybe we can test our database replication or network redundancy first.”
Over the next few weeks, I worked with my team to set up a basic chaos engineering experiment. We began by periodically shutting down one of our database replicas and observing how the application behaved without it. To our surprise, everything seemed to handle the failure gracefully, but there were some minor performance issues that we hadn’t anticipated.
The lessons from this experiment were invaluable. It forced us to think more proactively about system resilience and made us realize just how much manual testing we had been relying on. We started implementing better monitoring and automated alerts, which helped us catch issues before they escalated.
As the days turned into weeks, I found myself spending less time firefighting and more time improving our infrastructure. Our deployment processes became smoother, and incidents decreased significantly. The team morale also improved as everyone felt like we were making real progress towards a more robust system.
Looking back, that day in November 2010 when I first started to dip my toes into chaos engineering was the beginning of a journey that would shape our operations for years to come. It wasn’t just about writing code or setting up servers; it was about understanding how systems behave under stress and continuously improving them.
The tech world moves fast, and sometimes you have to take risks to move forward. That day taught me that embracing new ideas—like chaos engineering—even when they feel scary, can lead to significant improvements in your work.
That’s the story of a day that felt ordinary but turned out to be quite extraordinary in retrospect. Hope this resonates with anyone out there who has faced similar challenges!