HyperLedger Avalon

For many of my readers, if you have not read my previous posts on Blockchain, kindly do visit them for some interesting reading. This will give you some idea on what technologies are there in blockchain. In this post we will learn about the HyperLedger Avalon project.

HyperLedger Avalon

On Oct, 2019, the popular Linux collaboration foundation for blockchain technologies, HyperLedger announced a new project called ‘HyperLedger Avalon’. The underlying collaborative development however is not new since it was already known as TCF (Trusted Compute Framework). This collaborative development was between Hyperlegder, EEA (Enterprise Ethereum Alliance) and other cloud providers. Hence in terms of sponsorship, Avalon is the most widely sponsored project as its main sponsors are Microsoft, Wipro, Oracle, IBM, Intel, Alibaba Cloud, iExec Blockchain Tech. Baidu, BGI, Chainlink, Consensus, EEA, Espeo, Monax and Banco Santander.

But why do we need another blockchain project Avalon?

It is important to know the significance of this project given the huge number of sponsors which include both big and other players in the software industry. In blockchain, there are a couple of challenges currently. The two main are confidentiality and scalability. Traditionally, in blockchain we have a network of interconnected nodes also called as a ‘chain’. Hence whatever transactions, validations and data occur, they are done on-chain i.e. on every node in the network. Now there are advantages and disadvantages to this approach. The advantage is that the network can have consensus via integrity but this integrity comes at the cost of confidentiality and performance.

Solution

One solution to the above problems is to segregate some of the work outside the network i.e. ‘off-chain’. If some of the workload is done outside the main network, this can work like a trade-off between integrity and performance. Enter trusted computing or confidential computing (make link to your previous Azure confid. Computing post). Confidential computing guarantees confidentiality while giving additional performance. With the help of Trusted Execution Environments (TEE), confidential computing ensures the transactions are done secretly but with accuracy.

I have already written a post on confidential computing using Azure Kubernetes. Do check it out.

Currently there are various Trusted Execution Environments like Multi-party Compute (MPC), Zero-knowledge Proofs (ZK) and Intel®Software Guard Extensions (SGX). The Hyperledger Avalon project will include the above TEEs implement confidential computing as ‘worker types’.

A Short History of Avalon Project

  • Avalon begins to implement Off-Chain Trusted Compute which was an EEA specification
  • iExec builds Ethereum components for Avalon’s proxy mode for its heart disease evaluator prototype based on the above EEA specification
  • Mic Bowman finds ways to use trusted execution in ‘Private Data Objects’ which was a Hyperledger Lab.
  • IBM created a prototype of integrating Hyperledger Fabric with Avalon

Useful Links

https://github.com/hyperledger/avalon – Hyperlegder Avalon Project GitHub

Summary

The Hyperledger Avalon project is all about how to scale out and make off-chain workloads consistent by making use of confidential computing. Avalon is just one of the projects under the entire Hyperledger foundation. For the entire list of projects you can visit the official site https://www.hyperledger.org/projects. If you do not have any idea on blockchain related terms and technologies, this post might not be entirely clear to you. This is one of the reasons why I have created this blog so that I can make difficult technologies simple to understand. If you are interested in learning more about blockchain, please visit this link. Hope you have liked this post, do come back and share with your friends.

Hitesh Boricha

I have a little over a decade experience in the IT industry. Having worked in various roles in this industry, I am passionate about technology.

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.