Title: January 2022: A Month of Cloud Cost Woes and WebAssembly Musings

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January 3rd, 2022. The day after the new year, a fresh start on the calendar, but still a week into one of the most intense months I’ve had in my engineering career. We were knee-deep in the world of AI/LLM infrastructure—our team was busy scaling up our platforms to handle the influx of requests post-ChatGPT—and FinOps was becoming an everyday reality as cloud cost pressures mounted.

Cloud Cost Woes

One morning, I logged into my AWS console and saw a glaring red alert: our costs had spiked beyond what we budgeted. We were running containers in multiple regions with little regard for the long-term impact on our wallet. It’s funny how quickly you can go from “we’re a growing startup” to “budgets are tight, let’s cut non-essentials.” I spent hours digging through cloudformation templates and logging into each of our environments trying to find rogue services or containers that we could shut down.

It was a humbling experience. We had been so focused on feature development that we hadn’t paid enough attention to the underlying infrastructure costs. This led me to start thinking more about FinOps and how it should be integrated from day one, not as an afterthought when the bills come in.

WebAssembly on Server-Side

On a different front, our team was exploring the use of WebAssembly (WASM) for server-side operations. The idea was to leverage WASM’s performance benefits without having to run full-fledged VMs or containers. We set up a small proof-of-concept project where we offloaded some CPU-intensive tasks from Node.js applications into WASM modules.

It wasn’t smooth sailing. Debugging WASM is a bit of a pain, especially since there isn’t as much tooling available compared to traditional JavaScript development. I spent many frustrating hours trying to figure out why my functions weren’t being called correctly or optimizing performance bottlenecks. But eventually, we got it working and saw some impressive speed improvements.

The Day After ChatGPT

The AI/LLM infrastructure explosion post-ChatGPT was in full swing. We were looking at ways to scale our models more efficiently while keeping an eye on the growing interest from both internal teams and external partners. Our platform engineering team had been pushing hard for better resource management practices, but it wasn’t always easy to convince everyone that we needed to rethink how we approach scaling.

One of my favorite discussions was around the trade-offs between static and dynamic provisioning. We ended up settling on a hybrid approach where we dynamically allocated resources based on demand while still maintaining some level of static capacity for predictable workloads.

Developer Experience

Speaking of platform engineering, our focus on developer experience (DX) had also grown exponentially. With more teams relying on our infrastructure, it was crucial that DX wasn’t an afterthought. We started to see the benefits of tools like Terraform and Kubernetes in making deployments more consistent and repeatable, but we still faced challenges with ensuring that developers could quickly spin up environments for testing.

One particular pain point was dealing with different versions of dependencies across multiple projects. We worked on improving our CI/CD pipelines to handle dependency management better, which ultimately helped streamline the deployment process and reduced the number of issues caused by version mismatches.

Conclusion

January 2022 felt like a whirlwind of both excitement and frustration. We were tackling complex problems around AI infrastructure, cloud cost optimization, and developer experience, all while dealing with the reality of budget constraints. It was a month full of learning, debugging, and arguing about best practices.

As I reflect on it now, I’m grateful for these challenges because they forced us to be more mindful of our resource usage and pushed us to innovate in areas like WASM. And even though the days were long and sometimes overwhelming, there’s something satisfying about building a robust platform that can handle whatever comes its way.

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Stay tuned for more updates as we continue to navigate this exciting and challenging landscape!