Chromecast can be a notoriously difficult platform to develop for. Over the years, the hardware has evolved significantly; while recent models are powerful, early versions are easily overloaded and struggle with modern web overhead.

At Bedrock, we faced a specific architectural challenge: our Chromecast project was living as a single route within our massive main web repository. While this “monolith” approach worked initially, our rapid growth eventually turned it into a bottleneck.

📉 The Trouble with the Monolith

As the project scaled, we hit a wall with two primary issues:

User Dissatisfaction: Performance wasn’t meeting our standards. One of our major clients has massive Chromecast traffic, and the laggy experience was becoming a significant pain point.

Developer Dread: The team grew to worry whenever a Chromecast ticket appeared in the sprint. Because it was tied to the main web project, it meant dealing with long, complex and painful developer experience.

🛠 The Challenge: Breaking Free

We couldn’t change the hardware our users owned, so we had to change how our software interacted with it. We identified two core areas for improvement:

  1. Bloated Dependencies: Because the Chromecast app was part of the main website, it was loading tons of irrelevant Javascript. We were essentially forcing a low-power device to carry the weight of a full desktop site.

  2. Deployment Velocity: Our build and deployment processes were tethered to the main web project. We needed a workflow that allowed us to move fast without being slowed down by the main site’s release cycle.

🚀 The Solution: Chromecast Standalone

Following Bedrock’s Request for Comment (RFC) process, our Tech Lead conducted a deep dive into our options. The verdict? It was time to move to a dedicated, standalone repository.

This wasn’t just a change of address; it was a total refresh:

  • Modern Tech Stack: We adopted updated tools better suited for the platform.
    • BiomeJS
    • Vite

  • Transformed Developer Experience: By moving to a standalone project, we completely overhauled how we work. We built custom simulation tools to replicate the Chromecast environment locally, drastically increasing feature velocity.

  • The POC: To prove our theory, we built a Proof of Concept. It was a very simplified version of what would become the Chromecast Standalone, however we could do so much with so little that we were all convinced.

📊 The Results: Impact by the Numbers

The results didn’t just meet our expectations—they shattered them. By decoupling the project, we saw a significant and measurable increase in both stability and speed.

Core Performance Metrics

  • Video Join Time: Reduced from ~5.8s to ~2.8s 🚀 (A massive 52% improvement!)

  • IDLE / Pairing Page Load: Dropped from ~7s down to ~4s ⚡

  • Stability: We have witnessed significantly fewer critical performance variations, leading to a much more consistent user experience.

    Note: We are still in the process of migrating our entire user base, but the data from the new implementation is already showing all the benefits.

💡 Lessons Learned

Decoupling a core feature from a monolith is a major undertaking, but this project highlighted several key principles for success:

  • Validate via POC: Building a Proof of Concept was crucial. It provided the data needed to prove that a standalone architecture would solve our performance issues before we committed to a full rewrite.

  • Platform-Specific Needs: Low-power devices like the Chromecast don’t just benefit from lean code—they require it. Tailoring the environment specifically for the hardware is often more effective than trying to optimize a shared codebase.

  • Autonomy Drives Velocity: Removing the dependency on the main web project’s build and deployment cycles did more than just speed up our workflow; it removed the “developer dread” by giving the team full ownership of their release process.

  • Data-Driven Buy-In: Highlighting clear KPIs, like the 50% reduction in video join time, made it easy to demonstrate the ROI to stakeholders and justify the time spent on refactoring.

By focusing on these areas, we successfully transitioned from a technical bottleneck to a modern, high-performance application that our team is proud to maintain.