Performance Characterization and Bottleneck Analysis of Hyperledger Fabric

TL;DR

This paper thoroughly evaluates Hyperledger Fabric's performance, analyzing each phase, ordering services, and bottlenecks to enhance understanding and future improvements of this permissioned blockchain platform.

Contribution

It provides a detailed performance characterization of Hyperledger Fabric's phases and ordering services, identifying bottlenecks and scalability issues.

Findings

Execution phase scales well under OR policy but not AND policy.

No significant performance difference among Solo, Kafka, and Raft ordering services.

Validate phase is likely the system bottleneck due to slow chaincode validation.

Abstract

Hyperledger Fabric is a popular open-source project for deploying permissioned blockchains. Many performance characteristics of the latest Hyperledger Fabric, such as performance characteristics of each phase, the impacts of ordering services, and bottleneck and scalability, are still not well understood due to the performance complexity of distributed systems. We conducted a thorough performance evaluation on the first long term support release of Hyperledger Fabric. We studied the performance characteristics of each phase, including execute, order, and the validate phase, according to Hyperledger Fabric new execute-order-validate architecture. We also studied the ordering services, including Solo, Kafka, and Raft. Our experimental results showed some findings as follows. 1) The execution phase exhibited a good scalability under the OR endorsement policy but not with the AND endorsement policy. 2) We were not able to find a significant performance difference between the three ordering services. 3) The validate phase was likely to be the system bottleneck due to the low validation speed of chaincode. Overall, our work helps to understand and improve Hyperledger Fabric.