Optimizing RPC Performance with Batch Requests and Caching Layers

High-traffic Ethereum dApps can drastically reduce latency and node overload by batching JSON-RPC calls with Web3.js and caching frequent data using in-memory or Redis-based strategies. Together, these approaches boost performance and improve UX.

Heavy-traffic dApps that query Ethereum's blockchain numerous times within a brief span are going to see latency and node workload congestion. Every user dashboard refresh load, token balance inquiry, or contract read issues make JSON-RPC calls to an Ethereum node – and the larger the user base, the more calls are made. This can lead to slow responses, higher fees, and a poor user experience. Here, we will learn two powerful methods of avoiding these issues: batch multiple RPC calls into one request, and introduce caching layers to reuse frequent data. With the help of web3.js batch requests along with caching (in-memory and through tools such as Redis or ...