Optimizing a High-Traffic Web3 Wallet
During my internship at Robinhood, I implemented a new client-side data provider for the Web3 wallet, serving over 1 million users and achieving up to 85% lower loading times.
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problem
The Web3 wallet, serving over a million users, was experiencing significant client-side performance bottlenecks. Fetching on-chain data resulted in slow load times and a sluggish user experience, placing excessive load on our backend services.
solution
I was tasked with implementing a new, scalable data provider built around a multi-layered caching strategy. This approach was designed to dramatically reduce redundant network requests by serving frequently accessed data from an intelligent client-side cache.
Tackling Performance at Scale
The core challenge with Web3 applications is that on-chain data is inherently slow to access. My goal was to make our wallet feel as snappy and responsive as a traditional FinTech app. After using profiling tools to identify the biggest bottlenecks, I was tasked with implementing a new data provider based on an intelligent, multi-layered cache design. The idea was to proactively fetch data and cache it aggressively, serving it instantly to the UI whenever possible.
It was a challenging project, as I had to ensure data consistency and handle cache invalidation correctly, which is notoriously difficult. The most rewarding moment was deploying the new provider to production. Seeing the CPU utilization for our primary data service plummet by 7x was incredible. It was a clear, quantifiable validation that my implementation had not only improved the user experience by making load times 85% faster but had also made the entire system more efficient and scalable for its million-plus users.
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