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Exam Number : C5050-384
Exam Name : IBM Cloud Platform Application Development v2
Vendor Name : IBM
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IBM v2 testing

Evaluating Hyperledger Composer | C5050-384 PDF Questions and test dumps

Key Takeaways
  • only a really slender subset of use situations is acceptable for this technology.
  • the style that Hyperledger material makes use of MVCC (multiversion concurrency handle) when validating write batches is protected ample for economic functions in a decentralized ledger but may not scale efficiently satisfactory to be able to be eye-catching to B2C startups.
  • evade this expertise if you can make your entire transactions idempotent.
  • This expertise is still a bit immature.
  • even if here's an open-source undertaking, there are presently some obstacles in alternative of cloud company when relocating to a production atmosphere (that may exchange).
  • I have been following the three-yr-historical Hyperledger fabric open-supply assignment because its code base moved to GitHub about two years in the past. The Hyperledger tasks are hosted by means of the Linux groundwork and subsidized more often than not via IBM. They promote the use of what are referred to as private, or permissioned, blockchains. With a public blockchain, the primary nameless miner who solves a cryptographic puzzle gets to commit the next block of ledger entries to the chain. private blockchains resolve the consensus difficulty among authenticated peers the usage of algorithms reminiscent of Raft or Paxos.

    With a blockchain, you get CRUD-style entry to the ledger. You also get the skill to store mini classes called smart contracts on the ledger. When a transaction is submitted to a wise contract, all ledger state-mutating operations completed within the chaincode are atomic — both all operations get dedicated or none of them do. If the underlying ledger statistics accessed by the chaincode has been modified by the time that the operations made by the chaincode are to be committed, then the transaction is aborted. This happens automatically and is a large a part of the value to writing smart contracts.

    The identical individuals who released Hyperledger material also launched another open-source undertaking, Hyperledger Composer, which makes it handy for developers to jot down chaincode for Hyperledger fabric and the DApps (decentralized functions) that can call them.

    Why now? connected subsidized content

    Thoughtworks is a technology consulting company (received via Apax companions) that markets itself as "a neighborhood of passionate people whose intention is to revolutionize application design, introduction and start". Twice a 12 months, they unlock a know-how Radar record that recommends definite technologies be placed on grasp, assessed, put on trial, or adopted. quantity 18 of this expertise Radar (pdf), posted in may additionally 2018, placed Hyperledger Composer in the trial ring, which they outline as "value pursuing. it is critical to bear in mind a way to build up this skill. enterprises may still try this technology on a task that may handle the risk."

    In my role as a application architect, I consider emerging technology, and Hyperledger Composer made it onto my very own radar. anytime I evaluate an rising know-how, i use it to put into effect a rudimentary news feed microservice. each of these microservices are feature identical and are load-confirmed within the accurate identical manner. during this method, I can make not pricey statements concerning the performance traits of any specific know-how in evaluation with the different applied sciences. I selected the difficulty domain of a news feed on account of its familiarity and ubiquity in social networks and since it is complicated sufficient to require non-trivial options yet primary ample to take note without getting misplaced in implementation trivia. I post the source code for these microservices, together with the supply code mandatory to load-check them and to assemble and analyze the efficiency outcomes, in a freely attainable repository on GitHub. within the spirit of scientific peer evaluate, I motivate you to clone the repo and reproduce the outcomes for yourself.

    constructing the look at various microservice

    Hyperledger Composer permits you to write smart contracts in server-aspect JavaScript. It makes obtainable a local customer library in which Node.js functions can access the ledger and publish transactions to those wise contracts. For the purposes of this scan, I used an already developed Node.js microservice (see server/feed4 in the repo) as the handle. I copied the source code for that microservice to a brand new folder (see server/feed7/micro-service in the repo) then I changed all references to MySQL, Redis, and Cassandra with calls to the Hyperledger Composer client API. it's the feed7 undertaking that serves as the examine in this test. both tasks use Elasticsearch as a result of one of the most necessities of each news-feed provider is a key phrase-based mostly search, and a blockchain isn't applicable for that. Like many of the other microservices in this repo, the feed7 microservice makes use of Swagger to outline its leisure API. The specification can also be present in the server/swagger/information.yaml file.

    With Hyperledger Composer, you create a enterprise network that contains an information mannequin, a collection of transactions that manipulate the data model, and a collection of queries during which those transactions can entry information inside the mannequin. Hyperledger Composer works with Hyperledger fabric, whose simple community includes CouchDB, the default peer, the company network peer, a certificates authority service, and an orderer. The feed7 microservice accesses Hyperledger cloth within the context of this business network, which which you could find in the server/feed7/enterprise-community folder.

    figure 1: Feed7 components (the look at various).

    in the mannequin for this enterprise network, the broadcaster is the participant. There are friendship, inbound, and outbound property. The friendship asset captures the friend relationship between two broadcasters. each inbound asset is a news-feed merchandise intended for the linked broadcaster. The outbound asset is a information-feed item that turned into despatched by using the associated broadcaster. There are two transactions in this company community: broadcasters can friend each other and a broadcaster can broadcast a information-feed item to its friends. The best question obligatory interior the enterprise network is for the broadcast transaction to access the broadcaster’s friends.

    async feature broadcastParticipants(tx) const manufacturing unit = getFactory(); const created = Date.now(); const now = new Date(); const ok = tx.sender.participantId + '

    Code trial 1: a sensible contract.

    The Hyperledger Composer API that's supposed to be called inside a sensible contract closely resembles the API that's meant to be referred to as via the Node.js DApp, but there are some exciting modifications. within the wise contract, you have to use the async/look ahead to mechanism, but inside the DApp, you had to use guarantees. wise contracts all the time had to use predefined queries however DApp code may build a question dynamically and run that. When querying or retrieving both a participant or asset from the DApp, you had to consist of the regular "PID:" as a part of the key however not when gaining access to the equal information from chaincode.

    function submitTransaction(bizNetworkConnection, transaction, from, subject, story, callback, retry) const elastic = require('../repositories/elastic'); bizNetworkConnection.submitTransaction(transaction) .then((result) => const retVal = "from": from, "came about": Date.now(), "discipline": area, "story": story ; elastic.index(from, story); callback(null, retVal); ).trap(() => setTimeout(() => submitTransactionRetry(bizNetworkConnection, transaction, from, field, story, callback, 2 * retry); , retry + Math.flooring(Math.random() * Math.flooring(1000))); ); exports.addOutbound = function(args, callback) const BusinessNetworkConnection = require('composer-customer').BusinessNetworkConnection; const bizNetworkConnection = new BusinessNetworkConnection(); bizNetworkConnection.join(procedure.env.CARD_NAME) .then((bizNetworkDefinition) => const manufacturing unit = bizNetworkDefinition.getFactory(); var transaction = factory.newTransaction('info.glennengstrand', 'Broadcast'); transaction.sender = factory.newRelationship('data.glennengstrand', 'Broadcaster', 'PID:' + args.physique.value.from); transaction.subject = args.physique.value.field; transaction.story = args.physique.value.story; submitTransaction(bizNetworkConnection, transaction, args.physique.price.from, args.physique.cost.area, args.body.value.story, callback, 2000); );

    Code pattern 2: A DApp calling a sensible contract.

    within the DApp supply code, you may observe all this retry common sense when submitting a transaction. that is because Hyperledger textile makes use of MVCC (multiversion concurrency manage) when validating write batches and may without difficulty throw a study battle error. What you do to get to the bottom of it's to sleep a a bit of randomized period of time then retry the transaction.

    checking out the microservice under load

    both the control and the verify use the equal load-test utility, which you can locate in the customer/load folder of the repo. the load look at various creates 10 contributors in an eternal loop, and gives every participant any place from two to 4 pals. It has every participant broadcast 10 news-feed gadgets, each of which contains one hundred fifty randomly generated numbers. the burden-look at various app spins up three threads, every doing this system 90% of the time. The different 10% is testing the hunt performance.

    as an alternative of calling the news-feed microservice directly, the weight-look at various utility calls an open-source API gateway referred to as Kong, which proxies each and every request from the burden-test application to the news-feed microservice. Kong is configured to use the http-log plugin to be able to ship request and response logs for each name to yet another microservice, which in flip sends the efficiency-connected elements to Elasticsearch in batches. that you can find the supply code for the Kong logger microservice within the customer/perf4 folder.

    I used Kibana to imagine the performance records, including throughput, commonplace latency, and percentile latency. each time feasible, I all the time accumulated summaries of performance metrics from two hours of statistics.

    figure 2: Per-minute throughput of outbound submit requests for a examine (i.e., Hyperledger Composer and textile) scan.

    figure three: Per-minute commonplace of latency of outbound submit requests for a test (i.e., Hyperledger Composer and cloth) test.

    I deployed the control twice, both instances in EC2 the use of m4.xlarge instances; one time when the feed4 carrier was running in a Docker container and another time when it wasn’t. The Docker version skilled 6% much less throughput and practically no change in latency. I additionally deployed the examine twice, each times in EC2 using m4.xlarge situations for Kong, Cassandra (used with the aid of Kong), Elasticsearch, and the load-check utility. the primary look at various deployed Hyperledger textile, Composer, and the feed7 enterprise network and microservice on an m4.xlarge and the 2nd test used an m4.2xlarge, to see the performance modifications in scaling up.

    figure four: Feed7 deployment (the verify).

    To allow for legitimate comparative analysis, and since creation configurations had been now not without problems purchasable, both the manage and the test used developer configurations for every little thing. There exists an AWS CloudFormation template for Hyperledger material, however it is deploying the primary network, which is Hyperledger-speak for a developer configuration. The handiest online documentation for a construction configuration that I could find, outdoor of advertisements for IBM Cloud, have been a few blogs on Hacker midday by means of some folks from VMware. those blogs claimed a production configuration and a diagram indicated that the orderer changed into backed with the aid of Kafka, but the configtx.yaml file in the referenced GitHub repo suggests an OrdererType of solo, no longer Kafka. that suggests a developer configuration. A remark within the source code says, "The solo consensus scheme is very simple, and makes it possible for just one consenter for a given chain. It accepts messages being delivered by way of Order/Configure, orders them, after which uses the blockcutter to kind the messages into blocks earlier than writing to the given ledger."

    performance outcomes

    there's both decent and unhealthy information for Hyperledger when it involves performance under load. right here is the bad news: the Hyperledger version of the information feed proven over 300 instances less throughput and was three orders of magnitude slower than the average version. however the good information is that doubling the hardware means for the Hyperledger version yielded a 20% growth in throughput and almost halved the latency.

    The handle sustained over 13,000 outbound post requests  (i.e., a information-feed broadcast) per minute (RPM). common latency became 4 ms and the 99th percentile turned into 9 ms. The verify skilled on regular 29 outbound put up requests per minute for the m4.xlarge and 38 for the m4.2xlarge. The normal latency was 4.7 s for the m4.xlarge and 3.2 s for the m4.2xlarge. The 99th percentile latency changed into 10.2 s for the m4.xlarge and four.9 s for the m4.2xlarge.

    determine 5: Outbound-put up comparative performance abstract. Latency numbers are in milliseconds.

    There are every other inefficiencies that I should cover right here. The CPU and efficiency-related metrics on the control directly reached regular state whereas the identical metrics on the examine got worse and worse over time. The greatest culprit with CPU changed into the default peer procedure in material. This become magnificent because the microservice all the time accessed the news-feed enterprise network whose corresponding peer container was no longer as CPU intensive. most likely the default peer is used to suggest transactions? I may discover no approach to eradicate it from the configuration. In a production configuration, you could possibly have varied friends, in any other case the ledger would no longer be decentralized.

    For each the check and the handle, the microservice will at last crash, once the SSD for the database runs out of accessible storage. For the handle, that occurs in the Cassandra database after just about 30 million outbound posts have happened. For the look at various, that occurs in the CouchDB database after about four,000 outbound posts have passed off. The SSD storage for each the control and the verify have the equal capacity, which is 20 GB. naturally, storage efficiency is not presently a major difficulty of the developers contributing to the Hyperledger fabric project.


    originally, I believed that the information-feed utility could be an outstanding use case for a blockchain. The fundamental motion of the weight-test software is appending friends and appending news-feed objects, which sounds very akin to appending to a ledger. Now, however, I agree with that analogy to be superficial. The primary difficulty for blockchains is to evade what is regular because the double-spend problem — what decent is a blockchain that can't keep away from individuals from spending the equal money twice? For public blockchains, that problem is dealt with the usage of unspent transaction outputs, or UTXO. Hyperledger textile addresses the issue by means of MVCC on the read units when validating write batches. material does have inefficiencies that will also be addressed as it matures, however I trust that this use of MVCC with a purpose to keep away from double spending is an inherent cause for the low throughput and high latency. For all intents and purposes, the news-feed transactions are pretty much idempotent. There aren't any tremendous consequences if two individuals pal themselves in a distinct order or distinct times, or broadcast objects to every different in a special order or diverse instances. textile is allocating loads of CPU time and reminiscence to steer clear of an issue that has no significant influence on a information feed.

    This evaluation leads me to trust that the way forward for application development usually are not eaten by using blockchains. There is simply a really narrow subset of use instances that justify the high computing charges inherent in computerized, certain, dispensed concurrency control and validation. in fact, you need to require a consortium market where idempotent transactions aren't a possibility. while evaluating Hyperledger Composer at this time has some benefit, the existing level of maturity makes committing to a creation release in the close future tremendously troublesome. The Hyperledger initiatives are all open source but at the time of this writing there appear to be limitations in option of cloud company when progressing to a construction atmosphere.

    in regards to the writer

    Glenn Engstrand is a application Architect at Adobe methods, Inc.. His focal point is working with engineers in an effort to bring scalable, server side, 12 aspect compliant software architectures. Glenn changed into a breakout speaker at Adobe's internal promoting Cloud developer's conferences in 2018 and 2017 and at the 2012 Lucene Revolution convention in Boston. He makes a speciality of breaking monolithic functions up into micro-services and in deep integration with precise-Time Communications infrastructure.

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