by Peter Chawaga, Jul 11, 2017

Hyperledger’s Fabric 1.0 Is Ready to Change the World


When the Linux Foundation introduced Hyperledger, an open-source blockchain project, it aimed to propel distributed ledger technology across the world.

The project took a major stride in that effort today when it announced the general availability of Fabric 1.0, a production-ready blockchain framework that allows users to develop full-fledged distributed ledger applications to solve whatever problems they identify. It is a culmination of more than a year of public collaboration among over 150 participating developers. Engineering was contributed by the likes of the DTCC, Digital Asset Holdings, SAP, IBM and more.

For Hyperledger, this marks a milestone in blockchain technology’s journey toward widespread adoption.

“This is now a signal from the developers themselves that they are ready for the next order of magnitude level of interest from the user community,” Brian Behlendorf, the executive director of Hyperledger, told Distributed. “Our hope is that it really opens the doors to a lot of new users and visitors.”

Fabric was one of Hyperledger’s first initiatives and the first to achieve “active” status after a year held in “incubation” development. Its newfound general availability is an indicator of its readiness to support wide-ranging applications.

“This is certainly an inflection point for Fabric, for Hyperledger,” Behlendorf said. “We think that if one has been holding off on going further with Fabric because of a thinking that this was a research project, an experiment, it is now ready in my mind.”

Hyperledger feels that Fabric 1.0 is very much “plug-and-play” ready for potential users, offering a flexible architecture that can be built upon to bring blockchain technology’s biggest promises into the framework of any industry. As a starting point for potential developers, Fabric’s code is designed to be easy to utilize, reducing the learning curve that keeps many from equipping their industries with distributed ledgers.

“I think it’s incumbent upon anybody in this space … to make the learning curve as diagonal as possible,” said Behlendorf. “It’s incumbent upon us to reduce the learning curve wherever we can [and] this will really help proof-of-concept and pilot adopters move to production.”