Title: Reflections on a Muddy Waters Era

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May 27, 2024. The tech world is like the aurora borealis, with an ethereal glow that’s hard to pin down, but undeniable in its presence. I find myself reflecting on this period of rapid change and how it’s shaping both my professional journey and personal perspective.

The past few months have seen a flurry of activity, driven by the exponential growth of AI/ML infrastructure post-ChatGPT. I’ve been knee-deep in the trenches, managing platform engineering projects that often feel like they’re in a perpetual state of flux. It’s the kind of environment where you’re always learning something new but also questioning what you thought you knew just days ago.

One particular project stands out. We were tasked with integrating a new AI model into our core product. The model was cutting-edge, using GPT-4o-like techniques to process vast amounts of data in real-time. Debugging the integration was like trying to catch a slippery eel; every time I thought I had it figured out, something unexpected would pop up.

The day-to-day struggle involved not just coding but also navigating the ecosystem of tools and services that came with it. From WebAssembly on the server side to Kubernetes clusters managing containerized microservices, the tech stack was as complex as it gets. We were using Istio for service mesh, Argo CD for continuous deployment, and various FinOps tools to manage cloud costs. The sheer volume of these technologies made me feel like I was drinking from a firehose.

On the lighter side, we also had our share of fun moments. Daylight Computer’s 60fps e-paper tablet caught my eye for its innovative display tech. While it wasn’t directly relevant to work, the thought of an e-reader that could update in real-time without draining battery was intriguing. It’s these small details that remind me why I love this industry so much.

But it’s not all about new technology. There have been ongoing challenges with DORA metrics and FinOps. Our team is always looking at ways to improve our DevOps practices, ensuring we can deliver value faster while keeping costs in check. We’re constantly wrestling with how to optimize our infrastructure without compromising on performance or security.

One of the most heated debates lately has been around GraphQL vs REST. For a moment there, I was over GraphQL, feeling like it had become too cumbersome and bloated for some of our services. But after a few discussions and real-world usage scenarios, my perspective shifted. Sometimes simplicity is underrated, and maybe we can streamline our APIs without losing the benefits of GraphQL’s query flexibility.

On a personal note, this era has also brought about significant changes in how we approach platform engineering. The term “platform engineer” itself is gaining traction as a distinct role within the tech stack. We’re seeing more normalization around staff+engineering tracks, which feels like a step towards better support for those of us who wear many hats.

As I look back on this period, it’s clear that the tech landscape has become increasingly complex and dynamic. But amidst all the challenges, there’s also an incredible sense of innovation and possibility. Each day brings new opportunities to learn, grow, and contribute to something bigger than ourselves.

So here’s to the muddy waters of 2024—may we navigate them with curiosity, resilience, and a healthy dose of self-deprecation.