$ cat post/the-old-datacenter-/-the-deploy-went-sideways-fast-/-the-shell-recalls-it.md
the old datacenter / the deploy went sideways fast / the shell recalls it
Title: DevOps Wars, NoSQL Fever, and the Chaos of Real Work
May 31, 2010 was just another day for me, a seasoned platform engineer with 6 years in the trenches. But back then, it felt like I was living through a technological golden age, where every week brought new tools and ideas that promised to change how we build and maintain software.
The DevOps Debate
The term “DevOps” was still a bit of a buzzword, but its importance was quickly becoming clear. We were in the midst of a battle between Chef and Puppet for market dominance, with each side shouting about their superiority while I tried to find tools that fit our needs without getting stuck on the latest hype cycle.
Our team had just migrated from a monolithic Ruby application to a microservices architecture using Sinatra. The thought of orchestrating all these little services was daunting, but we were excited by the potential for better scaling and resilience. We started dipping our toes into Docker early on, but found it challenging to manage in production without a solid orchestration layer.
NoSQL Hype
NoSQL databases had taken the tech world by storm, and everyone was talking about Cassandra, MongoDB, and Riak. My team had settled on Cassandra for its horizontal scalability and eventual consistency model. But every morning, I woke up with new articles telling me why my choice was wrong, or better still, that a completely different approach would be the future.
One day, I found myself arguing with one of our senior developers over whether we should use Hadoop MapReduce to process logs or stick with something simpler like Apache Storm. Both were powerful tools, but neither felt quite right for us at the time. Our team was still figuring out what worked and what didn’t, and every decision came with a debate about best practices.
Debugging Production
Speaking of debates, I had just spent most of my day debugging an issue that popped up in our production environment. We were using AWS Elastic Load Balancers (ELBs) to distribute traffic, but we kept getting these mysterious timeouts where requests would hang for over 60 seconds before timing out completely.
After a few hours, I finally tracked it down to a misconfigured ELB health check interval. The default timeout was set too high, causing our application to appear unhealthy and get taken out of the rotation. A simple fix, but frustrating nonetheless. These little issues can really disrupt your day when you’re trying to focus on something more meaningful.
Continuous Delivery
We had just started exploring continuous integration with Jenkins and GitLab. The idea was to automate as much of our build process as possible so that we could catch errors early in the development cycle. It was a good move, but integrating all these tools together wasn’t without its challenges.
One particularly tough session involved setting up automated tests for our microservices. We were using RSpec and Mocha for Ruby, but it was tricky to get everything running smoothly. The team spent a lot of time arguing about the best approach—unit testing vs integration testing—but ultimately, we landed on something that worked for us.
Learning and Evolving
Reflecting on May 31, 2010, I realize how much has changed since then. DevOps is now an established practice, NoSQL databases are well-integrated into many architectures, and the term “Chaos Engineering” is a known concept in the tech world.
Back then, though, it felt like every day was filled with new challenges and learning opportunities. The rapid pace of change meant that there were always new tools to explore and problems to solve. I look back on those days with a mix of nostalgia and appreciation for the hard work and dedication that went into building and maintaining our platform.
In the end, it wasn’t about keeping up with every trend or adopting the latest tool; it was about finding what worked for us and sticking with it long enough to see results. That’s the real challenge in DevOps—turning theory into practice and seeing your efforts pay off in production.
Hope this gives you a glimpse into what life as an engineer looked like back then.