Monday, March 16, 2020
Podcast: Hyperledger's Arnaud Le Hors on best practices for Technical Steering Committees
The Hyperledger Project is a group of related enterprise blockchain projects under the umbrella of the Linux Foundation. However, in this discussion, we didn't focus so much on the technology but, rather, on how best to manage a project from a technical perspective. Perhaps the most interesting part of this discussion related to how managing a project like this one is at least as much about process as it is about the core technology. Example. What could the TSC have done better? Document everything!
Some related links:
Hyperledger Project
Hyperledger TSC Home
Open governance insights from Chris Aniszczyk, VP of Developer Relations at the Linux Foundation
Blockchain reality check 2020: Challenges and winning applications (write-up from Hyperledger Global Forum 2020)
Listen to podcast [MP3 - 24:11]
Friday, August 23, 2019
Hyperledger's Brian Behlendorf on starting Apache, foundations, and blockchain
[Photo: Used with permission of the Linux Foundation.]
Show notes:
Podcast:
- Brian Behlendorf [MP3 - 28:42]
Transcript:
Tuesday, July 18, 2017
Red Hat's Mark Wagner on Hyperledger performance work
Mark Wagner is a performance engineer at Red Hat. He heads the Hyperledger Performance and Scalability Working Group. In this podcast, he discusses how he approaches distributed ledger performance and what we should expect to see as this technology evolves.
Podcast:
Listen to MP3 [13:45]
Listen to OGG [13:45]
Links:
Hyperledger Announces Performance and Scalability Working Group
MIT Tech Review Business of Blockchain event
MIT Sloan CIO Symposium: AI and blockchain's long games
Transcript:
Gordon Haff: I'm sitting here with Senior Principal Performance Engineer, Mark Wagner. What we're going to talk about today is blockchain, Hyperledger, and some of the performance work that Mark's been doing around there. Mark, first introduce yourself.
Mark Wagner: My name is Mark Wagner. I'm in my 10th year here at Red Hat. My degree, from when I started many years ago, was hardware. I switched to software. I got the bug to do performance work when I saw the performance improvements I could make in software, in how things ran.
Here at Red Hat, I've worked on everything from the kernel up through OpenShift and OpenStack at all the layers. My most recent assignment is in the blockchain area.
Gordon: A lot of people probably associate blockchain with Bitcoin. What is blockchain, really?
Mark: Blockchain itself is a technology where things are distributed. I like to think of it more as a distributed database at a really high level. Bitcoin is a particular implementation of it, but in general, blockchain ‑‑ and there's also a thing called distributed ledgers ‑‑ they're fairly similar in concept, but the blockchain itself is more for straight financial things like Bitcoin.
Distributed ledgers are coming up a lot more in their uses across many different vertical markets, such as healthcare, asset tracking, IoT, and of course the financial markets, commodity trading, things like that.
Gordon: As we've really seen over the last, I don't know, year or two years, there's still a lot of shaking out going on in terms of exactly what the use case is here, which of course makes the job for people like you harder when you don't know what the ultimate objectives necessarily are.
Mark: Yes. It's shaking out in terms of both new verticals are being added, as well as there's multiple implementations going on right now, in a sense competing, but they're designed at different verticals in many cases, so that, in a true sense, not really competing, per se.
Gordon: Now you're working in Hyperledger. Introduce Hyperledger.
Mark: Hyperledger is a project in the Linux Foundation to bring open source distributed ledgers out into the world. I've been involved in it since December of 2016. Red Hat's been a member for two years.
One of the things in Hyperledger, there are multiple projects within Hyperledger. The two main ones that people know are Fabric from IBM, Sawtooth from Intel. There's a bunch of smaller projects as well to complement these technologies.
Both Fabric and Sawtooth are distributed ledger implementations with different consensus models and things like that, and getting to the point where they can do pluggable consensus models.
One of the things that no one was doing at Hyperledger, and where I felt I could help across all the projects, is performance and scalability. People see out in the world that the Bitcoin and Ethereum stuff is not scaling. When it hits scale issues, things go poorly.
I proposed in April that we have a Performance and Scale Working Group to go off, investigate this, and come up with some tests and ways to measure. It passed unanimously, but the scope was actually expanded from what I proposed, and they don't want it to just focus on Hyperledger but to focus industry‑wide.
Since that time, I've been in touch with the Enterprise Ethereum Association, with the person leading their performance and scale work. In principle, we've agreed to work together.
Gordon: I'm interested in some of the specific things that you've found in this performance and scale work. Maybe before we go into detail there, at a high level, where do you see the scalability and performance challenges with blockchain and distributed ledgers?
It's obviously early days. You've done performance work with the Linux kernel, which is about tweaking for very small increments of performance, where distributed ledgers are obviously in a very different place today.
Mark: The design of the original Bitcoin, and those technologies, is what was called proof of work. They gave you a large cryptographic hash you needed to go solve in order to prove that you actually did the work.
There were consensus algorithms based on that, and who got first and who got to build the chain and add to the chain. It quickly became people started using GPU offload or going off and fabricating FPGAs directly to give them an advantage doing this. There's a quick example of performance and scalability.
The other issue is, because it's consensus, everything gets shared. Everyone has to agree on it, or some large percentage has to agree on it. As the network grows, more and more nodes are involved in this, and it becomes a big scalability problem.
Gordon: Let's talk about the work that you've done so far. What have you been focusing on?
Mark: The Performance and Scale Working Group is really just getting started. Right now, we're trying to go through and identify three or four different vertical use cases. We're focusing more on distributed ledgers and their smart contracts, things like that.
We're trying to right now go through and identify use cases at Hyperledger. Another working group within Hyperledger has already defined. We can take those, and then say, "These are the key characteristics of those," because some of these vertical markets may not need the most transactions per second. It may be more how much you can scale.
The other interesting thing is there's two types of implementations, or deployments I should say. One is permissioned, where you need permission. That's called a private. The other is permissionless, which is public. Bitcoin is public. Anyone can join.
In the permission, you need to be invited so you can control the scale that way.
Gordon: Also, there's at least some discussion that in private distributed ledgers or blockchains, it's even possible you may not need proof of work.
Mark: Yes, a lot of it is working now towards proof of stake, where you prove that you're a stakeholder. It's less computation involved.
Gordon: Now, you mentioned it in the beginning of this podcast that you can almost think of a distributed ledger as almost a form of ‑‑ not to put words in your mouth ‑‑ distributed database. There's obviously very different performance characteristics, at least as things stand now.
How do you see that interplay of distributed databases substituting for, or instead of, or what do you see the relationship between distributed ledgers, blockchain, and distributed databases?
Mark: Distributed databases are more focused on sharing data, spreading it out. With blockchain and distributed ledgers, everyone has the same copy. People are looking at sharding now. You can go off and do just the specific set of transactions, or something like that with sharding.
It's also referred to as collections. Certain sets of nodes can go off and be involved in some transactions, others in different ones. That's one way to go around the performance and scalability.
Gordon: If you're looking back from, I don't know, five years from now or whatever, what do you think have been some of your toughest challenges that you've had to overcome in terms of improving the performance, usability, and so forth of distributed ledgers?
Mark: Five years from now, we'll look back, and we'll think how naive we were, in trying to solve some of these issues. Again, there will a big difference between public and private, but trying to come up with consensus algorithms, I think they'll keep evolving. The amount of work needed will change.
The other thing people will need to start thinking about is storage. How are you going to store all this data over time?
Gordon: What's Red Hat's interest in this?
Mark: Red Hat, right now, we have customers coming to us saying, "We like blockchain, but we'd like it to run on your enterprise‑class software."
One of the things I'm trying to do with Hyperledger is get things running on our OpenShift platform with Kubernetes with a RHEL base underneath it, looking at being able to contribute software so that it can become part of a CI environment once we get further along.
In general, right now our goal is to offer multiple blockchain solutions. Internally, we're figuring out what that means and how to do that. Right now, we're working with several.
Gordon: To your earlier "how naive we were" comment, that's one of the things we absolutely see today around blockchain, around distributed ledger, is really everyone's trying to figure out, "Where is this going to be a great fit?" Conversely, "We really thought we could use it for that? What were we thinking?"
I was at an event about a month ago, and Irving Wladawsky‑Berger, who basically ran Linux strategy for IBM when they were first developing a Linux strategy, was up in the panel on blockchain at the MIT Sloan CIO Symposium.
I think he's fairly representative of a lot of people who think that blockchain can very possibly be a very big deal, but also recognizing, Irving said we were probably in the equivalent of the 1980s Internet. It takes a long time to build out these kind of infrastructures.
Mark: That sums it up pretty well. One of the other things I heard when I first started with Hyperledger back in December at a conference in New York, was everyone agreed we're at the peak of the hype cycle, but also that it's still going to be very big.
Gordon: Actually, somebody made a very similar comment to me. It might have been the same event. They asked me where did I think it was in the hype cycle.
I actually looked up a Gartner "Emerging Technologies Hype Cycle" report and guess where blockchain was in that report? [At the peak of the hype cycle.] It scares me a little bit, but I agree with Gartner, to tell you the truth, but that was certainly their opinion.
Mark: Through my interactions here at Red Hat, I'm seeing lots of interest from healthcare, insurance. You can use this to cut down on paperwork for insurance companies, things like that.
"Here's the list of treatments that you're eligible for." The doctor goes in, says, "I did these," and he just gets paid. There's no going back through the review process, things like that.
Gordon: There certainly seem at least a lot of potential use cases out there. You have to believe that some of those are going to pan out at least.
Mark: Right.
Monday, June 05, 2017
MIT Sloan CIO Symposium: AI and blockchain's long games
I wrote earlier about the broad transformation themes at the MIT Sloan CIO Symposium last month. Today, I’m going to wrap up by taking a look at a few of the specific panels over the course of the day.
Artificial Intelligence
Andrew McAfee and Erik Brynjolfsson are regulars at this event. Their bestselling Second Machine Age focuses on the impact of automation and artificial intelligence on the future of work and technological, societal, and economic progress. Their new book Machine, Platform, Crowd: Harnessing Our Digital Future will be available later this month. Another panel, moderated by the MIT Media Lab’s Job Ito, featured discussions on the theme “Putting AI to Work.”
Like blockchain, which I’ll get to in a bit, a common thread seemed to be something along the lines of AI and machine learning being supremely important but with much still to do. In general, panelists avoided getting too specific about timelines. Ryan Gariepy, CTO & Co-Founder, Clearpath & OTTO Motors put the timing on the majority of truck driving jobs going away as a “generation.” My overall takeaway is that AI is probably be one of those things where many people are predicting greater short-term effects than is warranted while underestimating the effects over the longer term.
For example, Prof. Josh Tenenbaum, Professor, Department of Brain and Cognitive Sciences at MIT highlighted the difference between pattern recognition and modeling. He noted that "most of how children learn is not driven by pattern recognition” but it’s mostly pattern recognition where AI is having an impact on the market today. He went on to say that "other parts like common sense understanding we are quite far from. We’re quite a way from a conversation.The narrative that expert systems are a thing of the past is wrong. You can't build a system that beats the world's best Go players without thinking about Go. You can't build a self-driving car without driving."
Users of common “personal assistants” like Alexa have probably experienced something similar. Like a call center reading from a script, these assistants can recognize voices and act on simple command quite well. But get off script, especially in any way that requires an understanding of human behaviors, and their limitations quickly become clear.
McAfee also pointed to the confluence of AI with communications technology as a major factor driving rapid change. As he puts it “two huge things are happening simultaneously: the spurt of AI and machine learning systems and, it’s easy to forget about this, but over a decade have connected humanity for the first time. Put the two together and are in very very new territory."
As they do in their books, McAfee and Brynjolfsson also touched on the economic changes that these technological shifts could drive. For example, Brynjolfsson highlighted how “the underlying dynamics when you can produce things at near-zero marginal cost does tend to lead to winner takes all. The great decoupling of median wages is because a lot of the benefits have become much more concentrated."
Both suggested that government policy will eventually have to play a part. As McAfee put it "times of great change are not calm times. There’s a concentration of wealth and economic activity. Concentration has some nice benefits but it leaves a lot behind.” With respect to Universal Basic Income, however, McAfee added that "a check from the government doesn't magically knit communities back together. There's a role for smart policies and smart government."
Blockchain
The tone of the Trusted Data: The Role of Blockchain, Secure Identity, and Encryption panel was similar to that at Technology Review’s all-day blockchain event the prior month that I wrote about here. I’d sum it up in three bullets:
- It’s potentially very important
- Cryptocurrency existence proofs notwithstanding, as a foundational technology it’s still very early days
- Use cases and architectures are still fluid
Sandy Pentland, who moderated the panel, laid out some of the reasons why blockchain may be both useful and challenging. For example, he noted that "Data sharing is really difficult. You need to combine data from different sources that you may not own” On the other hand, "auditability is increasingly important. Are you being fair? You need to show decisions made. Existing architectures are just not up to it. Probably need consensus mechanisms like blockchain."
Hu Liang, Senior Managing Director Head of Emerging Technologies Center, State Street pointed out how some of the basic architectural elements of blockchain are still being debated. He went so far as to say that blockchain is just a fairly vague concept.” For example, he wondered whether "some things that made bitcoin popular may not be needed in an institutional world. Banks exist and regulators exist. Still get eencryption, auditability, but do you need proof of work?"
Finally Irving Wladawsky-Berger, Fellow, MIT Initiative on the Digital Economy (and long-time IBMer), framed blockchain as a transactional mechanism. He noted that "the internet never dealt with directly was transactions. Transactions are things that when they go wrong people get really really really upset. When transactions are part of interactions between different institutions it is a pain. The promise of blockchain over time is to be a record of transactions. benefits are gigantic.It could do for transactional systems what the internet does for connections."
But it will be a slow process. “The internet of the early to mid 90s was really crappy. The internet we are really happy with today took another 15 years to get there. We're at the toddlers stage. Foundational technologies take a long time."
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Photos:
Top. Jason Pontin, Andrew McAfee, and Erik Brynjolfsson [Gordon Haff]
Prof. Josh Tenenbaum, Professor, Department of Brain and Cognitive Sciences, MIT [Gordon Haff]
Irving Wladawsky-Berger [Gordon Haff]
Thursday, April 20, 2017
Cautiously optimistic on blockchain at MIT
Blockchain has certain similarities to a number of other emerging technologies like IoT and cloud-native broadly. There’s a lot of hype and there’s conflation of different facets or use cases that aren’t necessarily all that related to each other. I won’t say that MIT Technology Review’s Business of Blockchain event at the Media Lab on April 18 avoided those traps entirely. But overall it did far better than average in providing a lucid and balanced perspective. In this post, I share some of the more interesting themes, discussion points, and statements from the day.
It’s very early
Joi Ito, the Director of the MIT Media Lab, captured what was probably the best description of the overall sentiment about blockchain adoption when he said that we "should have a cautious but optimistic view.” He went on to say that “it's a long game” and that we should also "be prepared for quite of bit of change.”
In spite of this, he observed that there was a huge amount of investment going on. Asked why, he essentially shrugged and suggested that it was like the Internet boom where VCs and others felt they had to be part of the gold rush. “It’s about the money." He summed up by saying "we're investing like it's 1998 but it's more like 1989."
The role of standards
In Ito’s view standards will play an important role and open standards are one of the things that we should pay attention to. However, Ito also drew further on the analogues between blockchain and the Internet when he went on to say that "where we standardize isn't necessarily a foregone conclusion” and once you lock in on a layer (such as IP in the case of the Internet), it’s harder to innovate in that space.
As an example of the ongoing architectural discussion, he noted that there are "huge arguments if contracts should be a separate layer” yet we "can't really be interoperable until agree on what goes in which layer."
Use cases
Most of the discussion revolved around payment systems and, to a somewhat lesser degree, supply chain (e.g. provenance tracking).
In addition to cryptocurrencies (with greater or lesser degrees of anonymity), payment systems also encompass using blockchains to reduce the cost of intermediaries or eliminating them entirely. This could in principle better enable micropayment or payment systems for individuals who are currently unbanked. Robleh Ali, a research scientist in MIT’s Digital Currency Initiative notes that there’s “very little competition in the financial sector. It’s hard to enter for regulatory and other reasons." In his opinion, even if blockchain-based payment systems didn’t eliminate the role of banks, moving money outside the financial system would put pressure on them to reduce fees.
A couple of other well-worn blockchain examples involve supply chains. Everledger uses blockchain to track features such as diamond cut and quality, as well as monitoring diamonds from war zones. Another recent example comes from IBM and Maersk who say that they are using blockchain to "manage transactions among network of shippers, freight forwarders, ocean carriers, ports and customs authorities.”
(IBM has been very involved with the Hyperledger Project, which my employer Red Hat is also a member of. For more background on Hyperledger, check out my podcast and discussion with Brian Behlendorf—who also spoke at this event—from a couple months back.)
It’s at least plausible that supply chain could be a good fit for blockchain. There’s a lot of interest in better tracking assets as they flow through a web of disconnected entities. And it’s an area that doesn’t have much in the way of well-established governing entities or standardized practices and systems.
Identity
This topic kept coming up in various forms. Amber Baldet of JP Morgan went so far as to say “If we get identity wrong, it will undermine everything else. Who owns our identity? You or the government? How do you transfer identity?"
In a lunchtime discussion Michael Casey of MIT noted that “knowing that we can trust whoever is going to transact is going to be a fundamental question.” But he went on to ask “how do we bring back in privacy given that with big data we can start to connect, say, bitcoin identities."
The other big identity tradeoff familiar to anyone who deals with security was also front and center. Namely, how do we balance ease-of-use and security/anonymity/privacy? In the words of one speaker “the harsh tradeoff between making it easy and making it self-sovereign."
Chris Ferris of IBM asked “how do you secure and protect private keys? Maybe there’s some third-party custodian but then you're getting back to the idea of trusted third parties. Regulatory regimes and governments will have to figure out how to accommodate anonymity."
Tradeoffs and the real world
Which is as good a point as any to connect blockchain to the world that we live in.
As Dan Elitzer, IDEO coLAB, commented "if we move to a system where the easiest thing is to do things completely anonymously, regulators and law enforcement will lose the ability to track financial transactions and they'll turn to other methods like mass surveillance.” Furthermore, many of the problems that exist with title registries, provenance tracking, the unbanked poor, etc. etc. aren’t clearly the result of technology failure. Given the will and the money to address them in a systematic way that avoids corruption, monopolistic behaviors, and legal/regulatory disputes, there’s a lot that could be done in the absence of blockchains.
To take one fairly simple example that I was discussing with a colleague at the event, a lot of the information associated with deeds and titles in the US isn’t stored in the dusty file cabinets of county clerks because we lack the technology to digitize and centralize. They’re there for some combination of inertia, lack of a compelling need to do things differently, and perhaps a generalized fear of centralizing data. In other situations, “inefficiencies” (perhaps involving bribes) and lack of transparency are even more likely to be seen as features and not bugs by at least some of the participants. Furthermore, just because something is entered into an immutable blockchain doesn’t mean it’s true.
Summing up
A few speakers alluded to how bitcoin has served as something of an existence proof for the blockchain concept. As Neha Narula, Director of Research of DCI at the MIT Media Lab, put it, bitcoin has "been out there for eight years and it hasn't been cracked” even though “novel cryptographic protocols are usually fragile and hard to get right."
At the same time, there’s a lot of work still required around issues like scalability, identity, how to govern consensus, and adjudicating differences between code and the spec. (If the code is “supposed” to do one thing and it actually does another, which one governs?) And there are broader questions. Some I’ve covered above. There are also fundamental questions like: Are permissioned and permission-less (i.e. public) blockchains really different or are they variations of the same thing? What are the escape hatches for smart contracts in the event of the inevitable bugs? What alternatives are there to proof of work? Where does monetary policy and cryptocurrency intersect?
I come back to Joi Ito’s cautious but optimistic.
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Photos:
Top: Joi Ito, Director MIT Media Lab
Bottom: Amber Baldet, Executive Director, Blockchain Program Lead, J.P. Morgan
by Gordon Haff




