Configuring Hyperledger Fabric For High- Throughput Enterprise Applications”

Abstract

Blockchain technology, particularly Hyperledger Fabric (HLF), has become a key tool for enterprise applications due to its security, scalability, and flexible architecture. Unlike public blockchains, HLF operates in permissioned environments, allowing for fine-grained access control and privacy. However, optimizing its performance is essential, as inefficient configurations can lead to reduced throughput, increased latency, and lower transaction success rates. This study focuses on evaluating the performance of a Hyperledger Fabric network by adjusting key configuration parameters—block size, batch size, and batch timeout. The research aims to determine how these adjustments impact critical metrics like throughput, latency, and transaction success rates, offering valuable insights for optimizing the platform’s deployment in various enterprise environments. The performance evaluation was conducted on a controlled network setup, systematically altering the configuration parameters to assess their effects on the system. Results indicated that increasing block size and batch size significantly improved throughput, with the network achieving up to 142.9 transactions per second. These changes, while slightly increasing latency, maintained high transaction success rates, with a block size of 14 MB and a batch size of 45 or more achieving 100% success. Similarly, longer batch timeouts contributed to higher throughput, although they also resulted in marginally increased latency. The findings suggest that carefully tuning these configuration parameters can substantially enhance the performance of a Hyperledger Fabric network, making it more efficient for high-throughput enterprise applications. The study provides actionable insights for future deployments, ensuring that the system can meet the demands of enterprise-level blockchain implementations.