Hands-on with Hyperledger Fabric

  • Peers : Most active elements operating in the HLF setup. These are nodes connected to clients (SDK) and responsible for hosting smart contracts.
  • Certificate Authority : Dispenses digitally signed certificates to different actors to verify ownership in the network. These certificates bind the actor and the actor’s public key.
  • Orderer : Orderer is responsible for ascertaining that all the peers in the network have committed a transaction. Whenever a transaction is proposed or committed by a peer, orderer is notified about the new transaction. Then it forwards and commits this block to all adjacent peers.
  • Channel : Wondering what defines channel? Well, members (organizations), anchors peers per member, the shared ledger, chaincode application(s) and the ordering service node(s) sums up the channel. Every transaction on the network is executed on a channel.
  • Chaincode : Written in Go or Java, Chaincode is a programmable code that is instantiated on a channel. It is the ‘smart contract’ that runs on the peers and creates transactions.
  • A transaction proposal is submitted by an application to an endorsing peer (Admin peer).
  • The Endorsement policies give a brief of how many and/or what combination of endorsers are required to sign a proposal. The endorser executes the chaincode (smart contract) to simulate the proposal in the network peer, creating a read/write set.
  • All endorsing peers send the signed proposal responses (endorsements) back to the application.
  • The application submits the transactions and signatures to the ordering service, which creates a batch, or block, of transactions and delivers them to committing peers.
  • Each time a committing peer receives a transaction batch, it validates that the endorsement policy was met for each transaction. It also checks in the read/write sets to detect any conflicting transactions.
  • When both checks pass, the block is committed to the ledger. With this, the state updates for each transaction and are reflected in the state database.
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  • Reducing the tedious paperwork
  • Developing a sophisticated system where some claims can be verified & handled in less time
  • Potentially checking fraudulent activities
  • Improving the data quality which is used during the underwriting
  • Enhance the efficiency across the insurance value chain, for instance creating processes for automated claims

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