Won't take that. You'll need it, questions. Hello everyone, so I'm going to have a discussion, hopefully, with you today. I'll rattle through some state of the world and open data, hopefully quite quickly, and then we can jump into some discussion. My name is Gavin Starks. I'm the Chief Executive of the Open Data Institute. The ODI is just coming up for its second birthday. We're an independent non-profit company set up by Sotirn Barasli y cyfan yw'r web i'r Ynwyddiol Shadbolt, a'r rhemyd i'r ddau i'n erioed o'r cyfan y gwasanaeth o'r ddau yw'r gweithio ar wel yn yr ymdeg. Mae'r ystod i ddweud i'r ymddangos i'n ddau yw'r problemau sydd yn credu'r cyfan yw'r ddau yw'r ddau. Yn ysgrifennu pysgau'r teiml i'r cyfan yw'r cyfan yw'r cyfan yw'r cyfan yw'r ddau yw'r web wych. Sefyd, y web yn y cwrs 25 yma ar y cyf script i ffodol, ac yn bryd y gwrdd hynny'n rhoi'r ffordd lleol yn ffordd 22 yn y bryd. A'r awrch oだithfeydd followers.gov.uk yn 5 lleol erbyn y cy concei'r ei dŵr opent data eich bod a'r awrch oed yn ddim yn dŵr, ond ei hun, yn ei dŵr ariod. Mae'r awrch o'r 5 o 5 o'r 6 oed yn y dŵr datblygu eu dŵr oed. A'r awrch o dŵr bydau o dŵr What's the web of data going to look like in 20 years from now? The amount of data that's being produced is doubling every couple of years at the moment. But let's be very clear what we mean by open data. It's not big data, it's not personal data. Actually explicitly, it's data that can be used by anyone for any purpose for free. So we explicitly exclude personal data, so your individual health records, for example, should never be open data unless you give explicit informed consent to that. And big data is a phrase that I think a lot of us would like to go away because it is a bit meaningless. It's bigger than yesterday, I don't know, bigger than you can put in a spreadsheet, bigger than you used to, et cetera. So the kind of question though that I'm very interested in is how are we going to scale society and how can open data actually help us tackle some of the greatest challenges of our time and what is that challenge? The challenge is to try and sustain more than 7 billion people on the planet. That's an awful lot of people, a lot of people who need power, who need energy, who need food, who need water.  And at the same time we've got this rhetoric that's almost like we've hit peak, peak. You hear about peak oil. We're also, you know, peak uranium 2030, peak phosphorus 2025. So that's quite bad for farming. Peak copper, although we can mine some of that back out of the landfill. So we're hitting sort of peak resource all over the place. And we're not very good at actually trying to work out how we can scale on a per capita basis. So the kind of rule of thumb here is if everybody had the same sort of lifestyle as the US or the UK, we need several planets worth of resource. So that's not going to work. We've also got cities scaling at a huge rate. So more than 50% of the world's population currently lives in cities. This is going to grow to 70 or 80% over the next 20 to 30 years. In China they're creating I think more than 100 cities that have got more than 10 million people in them over the next decade or something. It's some phenomenal rate. And even in London you have maybe 10% growth in the population every decade. So for London that's an extra million people over the next 10 years and the next 10 years and so on.  And at the same time, we've got this huge move towards open data. And that can be social data, it could be population, it could be health information, it could be transports, it could be your own user generated content that you choose to make open. It could be environmental data so you could be looking at weather, you could be looking at farming, you could be looking at pollution or resource scarcity as I mentioned. And you've got economic data being made available. You've got corporate information being published. Companies house in the UK is going to start publishing all of the corporate accounts in the UK as open data. So another level of transparency that we're not used to. Interesting that sort of social contract is companies were originally created to have limited liability in return for transparency. We seem to have forgotten that sort of along the way. And this applies to new forms of trade and commerce like peer-to-peer lending. It applies to where assets are and much more corporate stuff. At the ODI, we incubate startups. We've had 17 startups through the programme so far. One of them identified a potential £200 million saving for the National Health Service by looking at drugs, looking at prescriptions and how many prescriptions of a particular class could be switched from patented drugs to generics. The price difference is £20 versus £70 for the drug in question. And even taking out the clinical cases where you need those drugs, the patented drugs for the patients, you can still save hundreds of millions of pounds. And that was derived in a matter of weeks by a handful of people. The next stage of that obviously is what do you do about it? How do you engage with the 1.1 million person bureaucracy that is the NHS to make the change? Similarly, we've got a company called Open Corporates that are mapping all of their companies in the world. They've got data for 78 million companies now. And they can do things like beneficial ownership maps of banks. So with Goldman Sachs, this map, which you can just see on the screen here, resizes the countries based on where the greatest number of subsidiaries are. And the large blob in the middle at the bottom there is the Cayman Islands. So you can see a huge number. You've got the UK, Luxembourg, Cayman Islands in the US. If you look at this map, this is for Goldman Sachs. If you look for Bank of America, a very different picture, most of the ownership there is inside the US. And you can draw whatever conclusions you like from that. We also brought together the peer-to-peer lenders in the UK and analyzed £400 million worth of spend data. We looked at who was lending, who was borrowing. Unsurprisingly, most of the lending was being done from the southeast, but most of the borrowing was uniform across the country. And that really highlights that the high street banks are not lending to a huge chunk of the market here. And this helps the Bank of England to think about how it could be data intensive in policy light. So this is kind of open data hitting the financial world and helping them ask questions about how could we regulate differently. How could we use data to police rather than coming down with policy that may kill markets. Similarly, analyzing government and public spending across Europe, the UK is particularly bad at receiving money quickly out of Europe. There's roughly £22 billion worth of cash that takes nine months to get from Europe into the UK compared with about three months for other countries like Poland. So we don't fare too well there. Also, tools that can help policy makers and citizens make decisions about their public services. So this is an analysis of the fire station closures in London looking at the response times. The number on the top left there is the response time of a fire engine to your area. And what happens, you can go through and select which fire station you want to close and it will tell you what the difference in response rate is. So it gives you a different sense of engagement around how you can not only help the policy makers but how you can engage the general public to say actually closing this fire station isn't going to change the response time in your area. In this case, we also combine it with footfall data from Telefonica looking at the actual population densities in different areas in the city because they're radically different from the actual residential population. You might have 100,000 people living there but a million people that work there during the day. Skip through those. One of the big pieces here that we are very interested in is the cultural change. We don't really see open data as a technology problem. We see it as a behaviour change problem and a cultural problem. We've been closed by default for really since the beginning of the industrial revolution and our patent and IP laws have reinforced this notion that open data is better. There's a lot of evidence now that open is much better. I think we're all familiar with the open web. It's far more powerful and has had far greater impact through being open than through being closed. We are a very interesting inflection point here where we can choose to be more open or we can choose to maintain the status quo around whether we have open by default or closed by default. That's something we've embraced at the ODI, so these are some of the figures from our own accounts, so how much value we've unlocked, how much income we make, how many people we've reached, how many people we've trained, et cetera. I think we're trying to lead by example here in identifying how can we quantify impact from a triple-bottom line perspective, so looking at social impacts, looking at environmental impacts and economic impacts. Social impact could be just greater transparency, could be better services, could be better public engagement like the fire station story, could be open innovation in the economic sector, bringing operational efficiency like in the NHS example and environmental impact, so can we really pull together the different data sources? How would we find, how would we know exactly how much oil reserves, coal reserves, copper reserves exist and mash that into an application that you're making that interfaces them with a product design tool? So if you're going to make a new fridge and there's going to be a billion people across India and Africa that want a fridge over the next 10 to 20 years, how are we going to make those devices? Because there simply isn't enough material. Where's that innovation going to come from? And so from our point of view at the Open Data Institute, we think it's time to really build the Open Data Ecosystem at web scale. And I think what we've seen over the last 18 months of our own existence is a huge amount of interest. We've seen the G8 or now the G7 sign an open data charter mandating that certain datasets like mining, extractives, corporate information maps, and genome information is open. That's likely to be adopted by the G20 this year and that's going to likely then be followed through by the OECD. So you've got this top-down pressure that we didn't have during the web. We've got a lot of the engineering of the web, I think, right because the political establishment simply didn't understand what was happening. This is very different in that context and that this is being driven by a political agenda as well as a grassroots agenda. We found that there's a huge amount of interest from governments, from NGOs, but also from companies. We've trained about 400 people actually over the last year and a lot of them have been lawyers or executives in telecommunications companies, et cetera, who are really trying to understand what does this mean for their business and how can they actually engage in it and be part of this kind of revolution around open data. We've also been blown away by a lot of international interest. We've got 20 international open data institutes now in 13 countries right across the world, including Moscow, including Seoul, Osaka, Dubai, places you wouldn't necessarily think as being particularly open. And we've got a programme of the World Bank. Again, it's all very top-down stuff of saying how can we train the world's political leaders to develop open data policies? We've done work in Burkina Faso, which has helped them map all the schools and release that as open data so parents can make better choices about where the schools are and how well they're performing. Like I say, there's a lot of corporate engagement here as well. I'm going to finish on a couple of points before we break to questions. One is that in order to try and link together all the open data that's being published, there isn't a particularly good mechanism or hasn't been a particularly good mechanism to do that. One of the things we've created is called an open data certificate. It's free, it's open source. You can use it as a data publisher to say, here is my URL. It has an open licence and I will commit to it being available for a year. And questions around the metadata about what you're publishing that enable that data to be discovered by data users and used more by those users. And so we're very keen to see people experiment with this to adopt them. The UK government has adopted them and we're starting to see now people like the Met Office on surveys, et cetera, publishing data with open data certificates. We're also starting to see private companies publish data with open data certificates as well. And what this enables is the ideal here is that Google will start to be able to index these certificates and therefore enable the discovery of data much more easily than it is today. And the other call to action is if anybody is working in open data, we invest, we have substantial amounts of funds to invest in communication. And we invest heavily in telling the stories. Some of the examples I gave earlier, we've had national coverage in the UK and around the world. We've been on the front page of the Financial Times and so on, really trying to raise the visibility of open data's relevance to everyone, not just the fringe activity that's happening in the geek or sort of web community. This is really front and centre in the political community and really front and centre in the business community. So lots of challenges there. The main one is how do we scale? How do we get millions more people into cities? How do we do that in a sustainable fashion? How do we provide food, energy, et cetera, for everyone? But also how do we make sure that this remains open? So how do we avoid this net neutrality debate around open data? How do we convince companies that open is more powerful than closed? These are really big challenges and we are in this again, to just finish where I started, on this inflection point. We have the grassroots community who have been working on this for decades. We've got the political sphere who sort of understand the principle, but they don't understand the technology. Companies who largely are confused or threatened by change and are quite cautious, but will default to close unless we really help them be more open. So lots of open questions there about how can we make this a global movement? How can we really engage in a broad ecosystem and what sort of problems do we think we could solve to demonstrate and provide the use cases for the power of open data? Thank you very much. I know I did that very quickly indeed. OK, we're just going to open the floor to questions now. So if anyone has a question here, just please raise your hand. If not, I'm going to answer. Yes, hello sir. OK, just two seconds, just going to bring this to you. So what are the main groups like companies, organisations against this open data concept and how do you deal with that? Is it a problem? Are you trying to get new open data or are you just using the data that already exists? We're both trying to demonstrate the value and what already exists because that helps demonstrate what's possible as well as open up new data sets. I wouldn't say companies aren't really against it, so to speak. It's more of a cultural thing of like we have just closed by default as a way of operating. And it'd be really interesting if I was standing here saying, let's imagine a world where everything was already open. Like when we published our accounts, it was already open, when we published our research, it was all completely open. Let's imagine that was already the case when we were standing here from the closed data institute saying we should really close all this information down. You don't think I was completely crazy, right? But we have developed this over the last couple of hundred years as a way of working largely down to our intellectual property laws. So I think the challenge for companies, particularly big companies, is that they're very risk averse. Actually, they might feel like big companies are very kind of beamoth who will try and own everything. But they're not going to do the innovation because it's too risky. So we need to bring together the start-up companies, the innovators, the NGOs and the rest of the community to say actually the sky isn't going to fall if this happens. What are the benign use cases we could start with and then gradually get more confident as we go forward? So I think that's really the challenge. So that's one category. The other category of people which is the vast majority of the world has no idea this is happening. So that's the bigger challenge. It's almost just raising awareness at all. And one of the big challenges I think we face is when you mention data to people, they either think of care dot data or personal data and the kind of bad PR you get around that or Snowden or WikiLeaks or Facebook or something that actually is quite different from what we're trying to achieve here. So there's a real threat I think of poisoning the well for a lot of the good work and good outcomes that open data can bring. So many, many challenges. It's one of the problems, not just a kind of a moral thing that people want to be closed or whatever, but if it's a bit of a hassle or maybe perceived as a hassle and expense to release data for a public body or for a company and then either perhaps people don't necessarily use it much or that there might be value that accrues to society and the use of that data, but the value is not accruing to the organisation that's got the hassle of releasing. Yeah, so the hassle and the cost question is something we encounter all the time. And there's some really interesting evidence now to say open is cheaper, it's better quality. So as soon as you start engaging with people who might be interested in the data that you've got, they start to care more about the data they're getting because they can provide direct feedback and fix things if it's broken. Same as Wikipedia. And the people who are producing the data in the first place suddenly realise that they have an audience rather than just having a spreadsheet on their desktop which is remarkably common still today in the academic world and in the public sector and the private sector is the information simply isn't captured and if it's captured then and put into a closed system, that closed system eventually atrophies bitrock sets in and we just lose the information forever. So it's a major challenge, again it's back to behaviour change to say open is cheaper, better and more usable than closed and that's a huge thing to try and communicate through these sort of existing barriers. A lot of people are terrified that when they publish their data people will find mistakes and we need to cultivate a culture of failure being okay. Mistakes being okay because the mistakes are already there. We just don't know them and if we don't know that the mistakes are there then nobody's going to fix them. So we're already using bad data or we might be using good data, we simply don't know but data isn't going to get worse quality and have less utility if it's open. My question sort of follows on from that which is don't you think that the technology such as RDFs and Al2, I'm talking about the semantic web end and say RDF and Al and all those sort of things which don't really have a problem. So in other words there's no real language so people don't want to invest in it because there's not a standard in which you can sit there and go well I can write all this in Al or Al2 and probably have to write the compiler and then next year it will all be changed and I'll have to do it all again. A bit like every software language that's ever existed maybe but I think now the principle here from my point of view would be put the data online, put it up there as a CSV file but give it an open data certificate so we can find it. If it's online and it's licensed the key question here isn't about the format. The format is an important question but it's almost a secondary question right now. The major challenge we face is simply getting the data published and licensed as being open in the first place and it's that licensing piece that is the big gap right now. In the US there is no open government license there's no equivalent of crown copyright. If you dig into it public domain in the US means public domain inside the US. So they're actively looking at CC0, CR0, license as a way of actually licensing some of their own public domain data. So the licensing piece is one of the big anchor points here because a company isn't going to invest in using data if they don't know for sure that they've got the license to use it. So if it's online I don't really care whether it's a CSV file or an RDF or an XML or whatever the thing is as long as it's addressable and that's one problem that we have resolved because we have URIs. If you have a URI and a license the data formats can then be machine read and machine manipulated after that point and it will be messy but it will at least be a mess that we can find. Hi there, thanks. I just wanted to go back to the point earlier about value of cruel really. When you were talking I was thinking about a recent book by Thomas Piketty and Capital in the 21st Century and one of his theses in that book is that one of the potential dangers for us in the 21st century is that more and more value gets accru to a smaller and smaller section of society and I was wondering do you see open data as a way of countering that? So that's the first question and then if so, is there a group of people who are actually against this or when they understand it likely to oppose this shift? Okay, so that's a great question and I think to answer the first question broadly yes I do see this as part of the general web culture which is more of a socially driven movement it's more about many parts loosely joined than aggregating and centralising power however we see that, we see this in everything that we've ever created and you see it in the web right now is that we are creating centres of power in Google or Facebook or the CIA or whoever happens to have the connection point so will this happen with open data? Yes it will in some way because once we make all the data indexable Google will and Bing and all the others will create great search engines which means we can find it so my question then is what's the additionality what problems are we able to solve after that? Again, central to this is actually the net neutrality piece so we have to have an open web and if we lose the open web we will lose all of the value not only of the web but all the potential value I think for open data so I think there's a really interesting tension there and your second question about who will oppose it well companies typically are opposed if they feel threatened they will maybe try and acquire as is often the case they'll try and acquire the small startup who's going to disrupt their business model but then we've got a good one thing that's different from say 1995 looking at the web is we can look back at the web and say well this has happened before we've done this in every sector we've done it in the media and entertainment industry we've done it in the newspaper world we're doing it across a whole range of different sectors and it's almost ironic in some ways that it's taken us 25 years to come back round to data and treat it as a category of information it's all right so I think certainly there will be incumbent organisations that will feel threatened some of them may go down in acquisitive and more aggressive type roads I think the more progressive companies will look at this and go I think we could probably save half a billion pounds if we did for example open clinical trials in the health industry rather than doing closed trials which cost fortunes to do and produce quite small sample sets there's probably better research and there's better outcomes and actually everybody wants those kind of better outcomes the question then is what happens around the IP and I think there's a lot to be learned from the open source movements to say what transition did we go through to say that the software IP isn't important but software as a service is the business model it's separated out the licensing from the paying for the service and in the long term open source has won it's kind of my view anyway has won a lot of categories because the sheer force of numbers and that's where we have a lot to really think about because as I've been trying to outline this is different to the early days of the web in that it includes the companies and the governments already that they're already looking at this and the government's already legislating for this so it's a really interesting balance I guess it's led by governments at the moment I think it's led by governments and grassroots in the same way the web has been and I think the governments are paying attention because of the grassroots piece and we look at the work that Government Digital Services has done in the UK and the history of that from the late 90s activists through a pause of while people digested what the hell was happening to Government Digital Services now existing as reinventing what the web looks like for governments in a very significant way and being able to point at that as an example this is the transition you've been through over the last 20 years is really useful to say well there's another transition we're going to go through here so I think it has been driven by the grassroots community the political sphere has adopted it because it ticks certain transparency in public good boxes but there's also if anyone remembers Yes Minister if you watch the very first episode of Yes Minister it's actually about open data and they get to a point in the episode where there's some data being released which will make the Minister look bad and of course the Minister then says no we shouldn't publish that data and you see that pattern in governments when governments come into power the first year they love the open data because it points out how bad the previous guides were and the second year they don't like it as much because it shows how bad they're doing and that just requires brave politicians and we need to really support our politicians in their push to keep the data open and actually Francis Maud in the Cabinet Office has been a massive supporter of the open data movement and I've been very genuinely surprised by that No one else have any other questions yet? No, I think just one more and then we'll probably just wrap up after that Is there anything from history that says why we have gone down the path that we currently are on? The open data path or the closed data path? Industrial revolution What's about my favourite line is the one thing we learn from history is that we don't learn from history so I think the cycle here for me is very familiar it's centralisation, decentralisation, aggregation, disaggregation we're seeing that in... you could look at the British Empire and the way that it's sort of trying to hoover up massive amounts of power and then disaggregated you could look at it in the way that now even Scotland wants to become independent you could look at the huge number of electricity providers that existed in the UK at the early 1900s that then aggregated and now we have six some of which are not in the UK and now we're seeing a transition to renewable energy where actually we can redistribute the energy generation and we can do peer-to-peer energy and we've got a start-up at the ODI called Open Utility who's trying to do exactly that so we can look at these sort of cycles and I think we're seeing the same thing with personal data personal data currently is centralised in Facebook and Google it can be decentralised through the personal data store initiatives and the sort of my data initiatives where you could get the control of your data and then you choose to licence it back to Facebook rather than the other way around so I think we just see these patterns all the time across everything we do whether it's international trade whether it's energy or whether it's the web it's just happening faster and I think that's the big change is when it comes to open data if we think back 20 years the web took quite a long time to reach where it is today because the technology wasn't quite there we didn't have ubiquitous broadband and we didn't have one of these in everybody's hands now everybody has a supercomputer in their pocket they have access to multiple supercomputers in the clouds for pennies a minute they can connect with everybody else in the world at a fast speed so the pace of change is going to be faster than the web in my view there's a lot of other caveats around that but I think the cycles continue they just shorten in frequency if that helps OK I think that's pretty much it I'm just going to shill one question on my own if I can actually please so you've spoken about open data in some ways it's almost like a gift from government here's how you can hold us to account better that's not the same as having a right so when it stops being convenient to you what's stopping the government's closed data back down again when it stops making them look good really well this isn't one of the most important things about getting companies involved in using that data because if companies are totally dependent on government publishing open data then there are jobs that are dependent on that data and governments really don't want to be responsible for shutting down innovation and shutting down job creation just to give one extreme example of that in the US some ex-Google folks went and set up a company called the Climate Corporation and they used US data around the environment around weather, climate around soil etc and they created a micro insurance industry for insurance industry for farmers so farmers could get very micro specific insurance policies for their farms across the US that business was almost entirely based on open data they didn't actually publish any open data they consumed it and made stuff Monsanto bought them for $930 million that's a very strong argument in terms of open innovation job creation and economic value creation for a government to actually say here is a tick now the specifics you may have different opinions on maybe it would be nice if they published open data as well and maybe that will come back around as we realise that everything becomes better if we're open everyone ladies and gentlemen thank you very much thank you folks now


Welcome folks. This is Tom O'Brien of TFNN. We have five days a week. We go seven hours a day. We go 24 hours a day on the internet at TFNN.com. Always remember folks, what if you think about, you bring about whatever you focus on, grows up, everyone's having a great day, safe day. It's making a great night, folks, except others the way they are. You cannot change other people to try to change them to fit what you want them to be. It's like trying to change a dog into a cat, or cat into a horse. They are what they are, and you are what you are. Mugging wise, let's take a look at it out here. We have the Dow Industries down 33, NASDAQ up 56, S&P's up 10, S&P's up 7, Gold Contract up $4.90 traded at $19.79 an ounce. We have Silver up 3 cents, $23.67 an ounce, Light Sweet Crew down 51 cents, $71.64 a barrel, notes and bonds. A 10-year note, down 2 ticks, trading $113.26, the 30-year up 1 at $127.30, and $KingDollar. $KingDollar right now trading up $132 ticks, $104.136, the Euros at $106, the Yens at $139, the British Pounds at $124 to $1 US dollar. iPhone numbers 877, 9276648, give us a call, folks. One note's going on in your world, and the world of the S&Ps, let's take a look at them. What do you have? Well, it looks to me like we're building cars to the next swing point, folks. The swing point I'm talking about is higher, too. Take a look at this market. What you're going to see in the S&P out here today, the spy. Yesterday, you didn't do any volume. We only did $70 million yesterday. Today, it's going to be less than that, but what you did today, you went down to $4.25 and rejected it. So what you actually have is you're going against $91 million now. And we take a look at this. We're so close to the next swing point that it's like, you know, this thing wants to get hit. So you take a look at it, you're going to see that swing point right there at $4.31. It's not going to be much to do that. $4.31.73, that's the number. We go into the NDX 100. We take a look at the NDX 100, same type of setup. Now, the NDX has further to go. There's no doubt about that. But the NDX did the same thing. You know, right now you're at $0.31, $0.355.21. What we did is that we get down to $352, rejected lower price. You're going to have lighter volume and you're going into, on this one, you're going up to $72 million. Okay. So we take a look at this, put this baby up here. Now, this swing point is definitely much higher. And, you know, that we're talking $371. IWM. Now, you can see, let me put the S&P up again for a second so I want to show you something here because when the S&P, oh, you got to go back so far, it really doesn't matter. No. The IWM folks, that, the IWM, now the IWM broke, okay? One by one of the IWM normally is the, you know, well, not normally. The last two times, it took a long time for it to get going, but guess what? It broke today and it broke with, it actually had the sign of strength on Friday. On Friday, it took out the consolidation. You get the fall of two today. It's going to have the volume. That's saying now the IWM is going to make its way up to the $191. And, of course, inside that IWM, and that's what you're seeing out here today, is that you're going to see that money is there. They're saying, okay, they're going into the banking sector, bottom line, see the KRE, they're going into that sector, man. And we start talking about that sector. What gets so intriguing, of course, is that you can see that the SEC went after Coinbase today. Now, it's so intriguing about the Coinbase one versus the Binance. Binance, I can see in a second. The Coinbase one gets interesting because of the fact that, let me see when they went public, because you can't go public unless the SEC says it's okay to go public, folks. Issue information. Let me just see this. Oh, that's interesting. So they might have did it. Oh, that is interesting. Oh, they might have did that through, see that says public offerings are not available? I wonder if they did that through a swap. Anyway, so that changes the, I don't know if it changes the concept, but the bottom line is that what is intriguing, especially with Coinbase is that going after the, I can pitch a Bitcoin in a second. After the exchange, that's kind of intriguing and kind of shaky, I think, because of the aspect of people, the way markets are supposed to be set up, they should be, they're supposed to be able to do what they want to do. They haven't gone after any of the banks that went down the tubes yet. That's the thing is you're going to see kind of a continual basis that it's going to be pretty wild, meaning that they protect the banks, but they're worried about this central finance. That's the real bottom line. Okay, so yeah, one of my targets says he's saying that they did do an offer in 2021. I don't know why I don't have it, but anyway, if that's the case, that's what's really kind of weird about it because they said, okay, here it is. Yeah, you can go public. Nope, they know what they were going to do. And then all of a sudden they say, hey, we're going to change. Now they've done that before. They did that to the large banks in the crash of 2007. When JP Morgan took over Washington Mutual, they basically were getting nailed and they spent a huge amount of money for something they didn't need to do and they were actually almost forced to buy Washington Mutual. Some of the higher volume equities out here today was going to be a low volume day. And yes, there was a low volume day also. You get Tesla up $2.5, we've got Advanced Micro up $5.90. Well, let's go into the NDX first. So inside of the NDX, the move is out here. You get Pindo, do up 7%, AMD's up $5. You get Warner Brothers up $4.5 and JD.com's up $4. Taking away from it. Aluminum is down $3. T-Mobile's off $3. Broadcom's off $2.5. Inside the Dow Industries, what do we get? Straight versus the weakness, point-wise, inside the Dow Industries. You have Goldman putting 35 positive points, American Express 27, Goldman 22. Taking away from it. UnitedHealth 85, Big Mac 35, Merck 23. We'll go to the bond market. Bonds, folks, they might take higher price, lower yield. I think we're topped out in the rates, man. That's the bottom line. We'll see how this shakes out. Kind of sideways moving out here today. Low volume, rejected lower price out here. Right now, the 10-year is yielding 3.6. Stay right there, folks. Coming back with the CEO of Vista Gold, Mr. Ed, and Mr. Fred Ernest. Stay right there, folks. Coming right back.


Good afternoon to everyone here in the Boston area and welcome to the August 21st peer insight where we'll be discussing harnessing crowd wisdom for the future of virtualization. I'm very excited today to be joined by Noemi Graysdorf who is VP of strategy for Cambridge Computing Services, Computer Services. We also will have today Nathan Smith, Senior Citric Engineer at Centered Networks, Yaqum Hepner who is Senior Manager at Sanofi, as well as Duncan Epping and Frank Denerman from VMware, and John Blumenthal from Cloud Physics. So the title for today's peer insight, Harnessing Crowd Wisdom for the Future of Virtualization, is really all about bringing a big data approach to analyzing VMware environments and making them easier to manage. Just a couple of logistics before we get started. Remember that it's a pound, sorry, star six to mute the line. Is that right? Yeah, star six to mute and star six to unmute your line. If you're not speaking, please mute your line so that we don't have feedback on the line. And if we will be pausing throughout the peer insight to give folks on the line an opportunity to ask questions of our participants today. So with that, let me get started. I want to start with you Nathan. Nathan again, thanks for joining us, Senior Citrix Engineer at Centered Networks. Nathan, first tell us a little bit about your environment. So we provide hosted virtual desktops and hosted applications. Our environment is about 95% virtualized. And it's a blend of VMware and Zen server. And we host on NetApp Storage. Okay. And tell me a little bit about some of the problems that you've been trying to solve on the management side. I don't know if it's management necessarily, but where we've run into a lot of issues is trying to make sure our performance is good and we mix our SLAs. We've run into some issues with the root cause analysis of performance problems in general, but specifically when we get down to the VM storage level, we were finding we had a kind of blind spot there where we had a feeling that we were heading towards the right direction. But once we started looking for some data on VM storage, we had a bit of a blind spot. We could see from the Windows guest devices that things were fine. And the NetApp performance advisor was also telling us things were good, but we couldn't really understand how the hypervisor was viewing the storage. And that's where we started working with Cloud Physics to try and get some metrics around that and then also be able to interpret those metrics in a useful way. What were some of the metrics that you were able to capture using Cloud Physics that you couldn't capture before? I'd have to decide the problems from Cloud Physics to really get into the details, but there were these good statistics. And one of the advantages to others of working in this way kind of utilizing other people's knowledge and experience as well as other people's data is that we were able to get some relatively simple views of some very complex numbers. So the way that when we were working with Cloud Physics that it presented back to us kind of simplified a lot of that, which is why I don't have a very clear view of the specifics. I just know the way it was interpreted. I was able to get a feel for in more kind of layman's terms whether our storage was in a good place or a bad place. So what did you do as a result of the analysis? At this point we haven't done anything differently. We're still working through it's obviously in this kind of process and this approach is in its very early stages. So we're still working closely with Cloud Physics to try and drill in a little further to figure out what we can do to improve things. Yacum, can you describe your environment there as Sanofi? Yeah, so we are a VMware based environment with all VMware as far as virtualization goes with EMC storage. The environment today is roughly 70% virtualized globally. Okay. And what kinds of challenges were you having? Are you having in your environment? Well, I think again for me, in my opinion, just going forward in the future, we're going to have to start looking at things a little differently, especially when we start looking at Cloud based computing, all the appliances that are out there. Again, these are things that are going to change the way we manage the platform. Just as a reminder for those on the call today, if you could please mute your line if you're not speaking, it would be helpful. That's Star Six to Mute. Again, Star Six to Mute, thank you everyone. And Cam, I hope you get back in the office soon. So are you sending data up then to Cloud Physics? How does that work? Yeah, so we just started participating in a data program and we've been sending our data for about a month now. Okay. And one of the things that's always sensitive in corporations is sending data about your environment off site. I'm curious as to how you approach that, who had to be involved in your organization to sort of make decisions regarding sending your environment data to a third party? All right. So we've looked at what our current policies have and we've actually already participated in something similar. We were part of the V-benchmark program from VMware. So we've done something similar in the past. So again, looking at what Cloud Physics actually collects. They don't collect any local or sensitive information. It's basically just performance stats coming out of each center, which is fine. Okay. And do you control access to that data or does it just... You've decided up front what data you're going to send and it just goes. Right. Based on the account we used for the privileges, we didn't give it admin rights. So again, it's using some basic privileges to collect the information. Just enough to collect the information it needs and send it up to Cloud Physics. Duncan, you've been acting as an advisor to Cloud Physics. So in the context of your role at VMware, how is VMware and how is Cloud Physics working together? Duncan, star six to Unmute. I was being unmuted at the moment. I'm indeed an advisor for Cloud Physics, but that's more from a community-slash-blogging perspective. Okay. And it has been my primary focus, at least from working together with Cloud Physics, to give early product feedback and product direction. And I guess that what I've been focusing on most is the community aspect of things, the usability of the product, and the potential of the data set itself. Hey, allora, Daniele. Prottini seti. Noemi, you've got some experience here with Cloud Physics as well. Can you talk a little bit about that? One of the reasons that I sort of started getting involved with Cloud Physics and having those conversations is a lot of our customers who are running relatively large VMware environments are struggling to identify performance bottlenecks to really get, as I think it was Nathan who mentioned, really getting down to the smallest increment in terms of... ...what the Automated Self-Service Directory... ...what the environment is doing in order to optimize it in order to get better performance, in order to support more applications in virtualized environment. And so we have had Cloud Physics introduced to a number of our customer accounts in order to help them sort of get a better understanding of what's happening. I have not yet talked to a single account where there aren't either challenges in managing storage in virtualized environment or who are not in need. So everybody needs something to either troubleshoot what they already have, to plan for the future, or to get a better understanding of where they are based on where they want to go. One of the things that we've been looking at is how introducing changes into the environment and impact the overall environment. So it's been a lot of discussion regarding SSDs and impact of SSDs in VMware environments. Can you talk a little bit about that from your perspective, what you've seen? So there is a sense to some extent in the marketplace that if you have SSD or SSD is the answer to all your problems. So if you put in SSD, it automatically solves your performance challenges, especially in the VMware environment. We're finding through conversations with customers that oftentimes adding SSD into the environment, you solve one problem, the bottleneck moves elsewhere. That's always the case, but when you're adding something that is so exponentially faster than what we have today, the hard disk drives, that bottleneck can be significant and cause significant issues. So you can't just blindly put in SSD to accelerate the performance and expect that the rest of the ecosystem is going to function perfectly well. You're going to either in the long term or in a very short term or likely run into bottlenecks along the data path, whether it's in primary storage, whether it's in data protection, replication, or something else. So I think one of the hopes here using a data analytics approach to managing VMware environments is that you can benefit from the experience of other users who've gone before you and tried similar things. So can you talk a little bit about what you see there? So it's a combination. In the presentations that I've sat through with Cloud Physics to the end-users, it definitely resonates the idea that somebody out there in the large VMware communities is either implementing SSDs or implementing a slew of storage systems that we have on the marketplace or doing something that is relevant to you. And so having that feedback loop is very, very valuable to them. Also being able to post questions to a large dataset is very valuable. What's really valuable about that is the fact that it's sort of anonymous. Anonymity is a big issue for many organizations, especially if you get into government, a lot of research labs. They're very conscious of the security issues. Even though they're only collecting operational data, there's still some issues around security. The other part of Cloud Physics that I think is valuable or is interesting is that there always has to be somebody who's first. If you're the follower, then there's plenty of people who have done certain things that you can take a lesson from it and implement in your environment or use it to troubleshoot your environment. But if you're the first one trying to do something like when vSphere 5 came out, if you were going to migrate to that, you don't necessarily have the experience of the crowd to leverage to see how to do it or what the best practice or what are going to be the gatchas. But the information that is collected by Cloud Physics inherently is also useful to model and to understand sort of what might be the gatchas in your environment as you try to implement certain things. Duncan and Frank, I know you have both been involved in looking at high availability. You've written extensively on the subject of high availability. And often when we make changes in an environment, it impacts high availability. Can you talk a little bit about what you are hoping to see out of this sort of big data approach to analyze environments and improving high availability as there are changes? Well, one of the things of big data is that we can actually validate if our best practices or the industry best practices are actually applied. And we can also see that if other settings are more common in most environments. So essentially identifying the best practices across a large community of environments and understanding which of those are able to maintain high availability. Yeah, let me add to that. Another thing that we're working on with Cloud Physics is specific simulation models for HA and DRS clusters. And those will basically allow you to try out changes in your environment without actually introducing them in your production environment. So that's a very effective way of seeing how a specific change to your environment can actually improve the resiliency or, for instance, improve the availability of workloads but also the availability of resources. All right. And I know for most IT shops they're relatively thinly staffed and they don't have a lot of time to do proof of concept so anything that will shorten that cycle is a huge benefit. Identifying what might improve the environment before you actually implement it in a what can be very expensive POC. Expensive not only for the customer but expensive for the suppliers. There's also a significant value in comparing different offerings in the marketplace more comprehensively. You could identify and create a workload set and then you can give that workload set specific to your environment to the various vendors and have them even run it in their lab because it's, you know, there's the conversation around, you know, we handle sequential loads well or we handle random workloads well, small file, large block, small block. But every environment has a different mix of those different parameters. So actually capturing a workload and making it possible for a vendor to test that workload against their system gives the customer some kind of, it empowers them because when the vendor then gives you the configuration it's the configuration that they should have tested and it says exactly it's going to work for your workload and this is what you're going to get out of it versus what a lot of times happens today. There are some basic calculations that may happen in terms of how many IOPS or how much latency you're going to have on a system and then when you actually implement the system it may or may not give you that because, again, the variability of workloads are significant across environments. John Blumenthal, I'll give you a second to unmute your line but I'm interested to hear from you. Again, John is the CEO of Cloud Physics. I'm interested to hear from you how much data you're actually going to collect. I'm sorry, I hope you guys can hear me. Right now we have 50 working data sets that we're using for aggregation. The number this week is climbing incredibly given the launch of our website. Yeah, you just came out of stealth mode yesterday, right? We did. We were working with larger data sets mainly to prime the back end of our system to start understanding how to load balance it. Now we have, we're in the process of onboarding nearly a hundred of what we call observers, useful appliances that are the data collection mechanisms that users download as an OVF and simply installed and from there anonymization occurs before the data is chipped up to our cluster that we run as our back end. So the total data set has grown into the hundreds of terabytes already. We're actually using aggregations of data that we've been collecting over the course of the last year while we've been operating in stealth mode to test a lot of the analytics that we've been writing and some of the cards or small applications that you can see on our site currently especially things related to high availability that Duncan and Frank have also taken. Again, star six if you can mute your lines if you're not speaking and appreciate it. I've seen a number of mentions of cards. Can you talk a little bit about what cards are and what that means to the community? Yeah, so cards are our visual metaphor that represents the user experience and orientation of our product, our service approach. Our service is a task oriented approach where users can derive very specific benefits from applying a card to a very specific problem and our service is not meant to manage or necessarily provide real time monitoring of a system. There are plenty of solutions like that in the marketplace and nearly all the solutions in the marketplace are focused on kind of an inventory oriented approach where you are presented with the environment and the environment is navigated by the end user to find an object on which to operate or execute a task. Our entry point is more task oriented where the user comes to cloud physics with a specific problem. The problem is rendered or represented as a card as a narrowly focused tool and you use that card to apply a specific solution to that problem. In this challenge that we have hosted this week on the FireCupium World you can see hundreds of cards that have been suggested in ways that are actually quite remarkable and representative of the power of the community. Literally there are hundreds of these things already just in the 48 hours that we've been live that describe very specific problems that products today just don't address or render and it's our ambition to continuously provide end users with these on-going solutions and as a consequence of this on-going community involvement in the development and delivery of these solutions this very massive data set will arise in these places. Again if you're not speaking please press star six to mute your line. Which one is my... Excuse me. Anyone on the call who's not speaking please mute your line star six. So I want to pause here for a moment and see if there are any questions from the community. Okay so... Hi John. Yeah. This is Mike Alvarado. I didn't have one question. Hi Mike. If there's a view into aggregating resources or making available a some kind of shared model where resources are actually tapped into. John can you answer that question? Yes it's a great question. We have built and are in the process of implementing you'll see this very soon a secure data sharing model that looks a lot like what you may have experienced in social networking already where for example with Google circles you can light list people to look at different portions of what you've created as your profile and effectively your portion of the file system tree. Similarly what we are working on and will have already very soon is the ability for you to share a key with the third party and that key can be revoked at any time. It can be fired and the idea is that the third party can then render and view your environment in an unmasked fashion and they could if you wanted to look at the association of who you are with that unmasked view but you as the end user have entire control of who views and who can access your actual unmasked state of your data and the technique is actually very well known in the way that social media works with privacy controls so we've borrowed from that very heavily to implement a very similar type of data sharing mechanism. We have a storage partner already who is using this process for the purposes of pre-sales and someone on the call today mentioned this already where a vendor in cooperation with the end user can request the key and allow for an analysis of an environment prior to sitting down with the end user to talk about their environment and the actual value proposition that a vendor's product might bring to that environment. In fact the call today we hope in the very near future to work with Wikibon to deliver this type of data sharing mechanism such that participants in the call like Nathan and Joachim could simply provide you the participants in the call a temporary access to look at their environment in a kind of schematic way for you to securely review and analyze what your environment might look like as a trusted third party. It's a core piece to what we're doing. It enhances and I think congeals a technical community and it's a core focus of what we're delivering. Mike did that answer your question? Any follow-up? Hi this is David Slyer. I have a follow-up question for that. Obviously the more people that you have in your database would seem logical to me but the more people that you have in the database the greater the advice and information you can give out to your users. Is your business model to allow users to value the data and then a subset of those users to purchase your services from that data? That's a great question. The power is really in the statistically meaningful size of the database as you indicate. Our business model is really twofold. The first is to deliver directly to end users value through a subscription service that is comprised of an ever-increasingly rich set of cards like the ones you see on our site as well as what has been suggested by the community. In fact, the idea here is that the community itself will be able to develop cards and off of a platform access that will be exposing such that third parties can develop their own cards somewhat like an app store in which these focused solutions could be distributed on an ongoing basis for a variety of cloud type infrastructures. And then the second part of our business model is focused on the product vendors who are constructing and delivering products to those same end users consuming our services. And so these product vendors consume really three types of modules that we're putting online for the vendor community. One is a sales module that increases the effectiveness of the sales force and customer satisfaction in the sales process. The other is a support module that addresses the multi-vendor environment you typically find in a virtualized environment in a way that allows for coordinated reviews of the user's environment in a secure fashion using this data sharing technique I described earlier so that the time to resolution of a given problem is accelerated and the VMware admin is not left as an administrative assistant trying to schedule vendor coordination and vendor calls. So that's our kind of two prong approach to the fundamentals of our business. And is the plan to expand this beyond the VMware environment? You're covering Citrix as well, Hyper-V, non-virtualized environments. What's the plan? Yeah, because of the domain expertise of the team coming out of VMware. But the other half of our team is actually drawn from Google and a lot of the big data community in the Bay Area. We are first and foremost focused on vSphere. We will be constructing data collection and analytics on other hypervisors as well as working with several cloud, public cloud providers that we're already engaged with. So the ability then to model your environment, understand your environment as you extend it out into cloud service providers? That's right. So the public cloud service providers have a variety of performance APIs that they expose for the purposes of monitoring the performance of instances you instantiate in EC2, for example. What's critical though is the ability to also understand what's happening behind the virtualized veil that the public cloud providers provide access to. So we are in the process of engaging several of these larger-scale public service providers to help with the modeling of how their back-end physical infrastructure responds to the demand coming from the logical side, from the virtualized side of their business. This is David again, just coming back on your business model. Again, this seems to emphasize the more potential users you have, like members and support people, that the more people you have in your system the better. Again, I was asking specifically whether you were planning to pay people for their information even though they don't actually want your services. Oh, I see. We haven't approached that type. We haven't approached that business model as a way for generating a revenue stream. Instead, the approach that we have taken is to really create a very simple API into the expanding data set so that by contributing to this independent platform, you could also build potentially your own business or your own product in many cases off of the data that we're caretakers for as an enablement platform. So it's a little bit the inverse of what you're asking. Instead of paying people for the data stream, we instead take the data stream and place it in a way that would allow you to build a fundamental application or report that would be of high value for others in the community to consume either free or under a revenue sharing model that might arise from that. So Yacum and Nathan, I'm interested to hear from you if you feel like either centered networks or Sanofi will go down the path of trying to generate revenue from applications or if we're really targeting a different sort of customer here. This is Nathan. I don't think for us we'd be looking to add revenue by using cloud physics. I think we would sit on the other side of the equation that John's talking about, where we look for value by using the subscription service and getting these very simplified views of a great complex environment with the added benefits that we're also able to leverage other people's data to get a more accurate view of how we're performing or how our environment is set up compared to other environments or best practices. And I suspect Yacum that in a pharmaceutical company the focus is going to be on improving your development of new medicines and not new apps. Correct. So again for us it's going to be more about maybe peer comparisons. Are we, from an IT point of view, are we at the same cost model as let's say one of the other competitors? Something along those lines. I could see it more useful on that category in the future. It's interesting if I roll it back 20 years ago or so when I was on the customer side we looked at different benchmarking tools to see how we were compared to similar kinds of companies of similar size. But you couldn't do a direct comparison between State Street Bank and Fidelity for example because neither company would want the other to have that kind of visibility. What kinds of comparisons to other people's environments are you going to be able to provide? And what kind of protection are you going to be able to provide relative to, you know, I'm target and I don't really want Walmart to know what my environment looks like. John, that's for you. Yeah, so this is Yacum. Are you asking us? Actually, I'll ask you, Yacum. What about a Sanofi? I mean you probably don't want Mark knowing a lot about what you're doing. Sure, but at a high level that information is public, right? So in the information week 500 and all those, you know, other similar magazines they do publish annual IT budgets. So you can kind of calculate your number based on the number of employees, which we do today internally, right? We always look at that. Okay. So it would be interesting to see maybe some other information. Again, you know, everybody's different, everybody uses it a different way. I don't know if you can gain one is more efficient than the other. I think from anything else it might be more of a, okay, that's interesting. Now we understand where we fit in this. Not so much, oh, we really got to get to that. Right. So it is more important to sort of look at, to satisfy your management that you're operating a very efficient environment relative to the competition. There's a lot of variability in that from organization to organization in terms of their, how risk averse they are, how conservative or not, where their focus is in terms of IT, you know, how they manage their information. There are some things that are very standard, but there are some things that are very specific. Again, you know, even if you take two research labs and their HPC environments, they could be all in life sciences, but they could be completely different workloads and how the data is stored and how the scientists are using the data is going to be very different. So the value of the aggregates is really more around the infrastructure and how do you optimize the infrastructure against the kind of workload. So it might actually, for Sonofi, it might be more valuable for them to see or to compare themselves against somebody else who's running a similar infrastructure. It could be in a different industry, but they might be doing something that could help Sonofi improve either VM density or performance. Or whatever it is that they're trying to achieve. So it's not just benchmarking against your industry peers, but against the larger peer community. It's good.  What kinds of organizations do you imagine having an interest in developing the apps for the community that they might sell? I think this begins, as we're already seeing, as a grassroots initiative within the very active community that Duncan and Frank are particularly strong in their leadership. I think it begins literally down at the people on the front lines of managing these systems. So it's really at the individual level. You can imagine some individual deciding to, hey, I've got an idea here and I've got a way to make some money. Yeah, I think, I mean, in a way, first of all, I think the community, and I deferred to Duncan to speak, and Frank to speak authoritatively about this. But I believe there's a heritage here that goes back to the UNIX utility days where you have very focused utilities that were the core philosophy of how you manage UNIX back in the day. And that if you wanted to create something of utilitarian value, you did that in a very narrow focus way. And then people invented ways to type these things together to build increasingly rich solutions. I've drawn from that experience in, I think, that trend that led to a lot of success in managing open systems. And I see that happening in the community today. I think Duncan and Frank could comment, I think, about the kind of demand in the nature of the community in terms of either looking at their work as a means of deriving revenue, or whether there's more of the spirit of sharing an openness that is driving some of the things that we're already seeing at Cloud Physics. No, good. Frank and Duncan, why don't you flesh that out for us and give us some of your perspective? How do you think it's going to play out? Is it going to become a charitable organization, a charitable approach, a big open source group hug, or is it going to become everybody trying to build their own portfolio for fee apps? Let's hope that it's going to be a big open source group hug. That's what I would prefer. And by the looks of it, if I look at the current backend of Cloud Physics, there's been many cards submitted already by the community. And I'm guessing that it's going to be the same in the upcoming months. A lot of people actually see the value of this platform. And we had some early blogger calls, and they also saw the value of this. And they also see where they could actually benefit from getting access to a data set like this. So they're all happy to contribute to the platform by feeding in desk practices or some sort of monitoring, logging reports. They're all really happy about doing this. And I think Frank and I started doing that with the HA scorecard, which is already in there. And Frank is currently actually working on a DRS scorecard. And that's also going to be a community effort. So maybe Frank can explain the part that he's working on. Yeah, Frank. So like Duncan mentioned, the DRS scorecard. So one of the most brilliant things of this is that we can use the analysis of the program to actually understand that if you change a certain setting, for instance, a VM reservation, what impact does it have on the performance of the virtual machine? And if I change it, if I increase it, what will happen? Not only to the performance of that virtual machine, but also on the rest of the ecosystem.  And I think it's easily comparable to the PowerSheelite community in the environment. Everybody's just working on creating cool scripts. And I think the similar thing will happen, creating cool cards and cards which no benefit from.  It seems like this would be a great resource of best practices for them as they're trying to not only build out their practice, but improve the customer experience. I think it actually goes into the larger shops as well. We've talked to a number of, you know, a number of our clients who are even larger environments and what would be considered a relatively large VMware shops are struggling with getting the information and being able to work with the settings. DRS being a great example. I remember one meeting we had where the admin is going to try to modify the default settings of the DRS. But there are so many variables that it's very difficult for one individual to optimize the whole environment and, as Frank mentioned, consider all the implications of what they do on the ecosystem. So it's not just I'm dealing with this one single VM because of the abstraction and the shared infrastructure. You really have to understand the issues that are going to cascade out of what you're doing. And for even a larger shop, it's actually even probably more valuable to have the ability to leverage a community and to get that kind of information as they try to optimize and use these tools. Yeah, I keep coming back to the notion of SSD, which has been so, it's gotten so much visibility. I mean, IBM just bought the oldest solid state disk company, I think it exists in Texas memory. In recognition, they had, and Texas memory has a variety of different formats, different offerings. But there are so many different places where you can interject solid state disk or flash into the environment, and each one has its own sort of implications, right? And each one has, and may have downstream benefits or may have downstream, create downstream problems. Absolutely. And if you could marry that up against sort of pricing data, it starts to, customers should be able to make much more informed decisions. I think this is all about making more informed decisions. Yeah. Let me open it up again for questions to the community. Anyone else have a question for Yacum or for Nathan? This is Scott. Well, I've got pretty much my standard question these days is how are organizational CIOs that you talked to, how are they looking at this product and what kinds of activities in their environment are they hoping that will be streamlined or negated? And basically, what's their goal for an ultimate outcome? So this is John. What we're finding is a reflection, I think, of Noemi's statement, which is by having access to more of a global set of data and data scientists who are trying to continuously interpret the data as it relates specifically to your environment, it leads to just better decision making where the notion of relying on market-wide operational insights and how that might affect your environment in terms of cost, risk, and waste, I think that's the ambition of cloud physics and I think it bubbles up to the CIO by seeing greater efficiencies and greater effectiveness in the overall operation of the infrastructure. And by operation, I mean that comprehensively from dealing with vendors and how you efficiently understand and procure the right products and then how you implement those products in the best possible way and do that in a rapid cycle driven by a kind of collective intelligence that doesn't mean you have a reliance just on the one overloaded individual who simply doesn't have the time and is operating under intense pressures. The CIO, I think, just sees just greater effectiveness and speed out of what he commands. So this is a more efficient use of IT resources, but it's faster time to market things like that. It's essentially faster time to market. Okay. Any other questions? So John, a couple of times you've mentioned the cards and the submission of cards and the uploading of massive amounts of data. If someone wants to share their data with you or wants to suggest a card, what do they do? So today you can register on our site. You can use a limited set of cards that we have developed in conjunction with the community. So these are community big hug cards that anybody can have access to? Yes. Okay. So we have this online. We can see that there are hundreds of cards being suggested that we're in the process of sorting through with the assistance of the community as to prioritization and code development. We have not announced any of our pricing or packaging around any of this. We're going to be doing that in the course of next week with VMworld. Which is where we're really publicly presenting the company and the work we're doing. The data sharing mechanism I mentioned has not been implemented at this stage. And instead what happens is your data is anonymized so that neither cloud physics nor trusted third parties at this time actually share data with one another in its unmasked state without explicitly engaging cloud physics as an intermediary. That is the process of doing that we are working on and will be implementing so that cloud physics is removed as that intermediary for the purposes of sharing your data with another third party. And for what we're doing with that primarily is working with a small number of storage vendors to allow for the pre-sales process to operate far more effectively. So in this case, let's say an entity vendor is wanting to engage an end user of cloud physics. That storage vendor has to talk directly to and call up their prospective customer who grants access to their unmasked view in which case cloud physics then receives the key from that end user and allows the third party the storage vendor to then look at that customer's data set in its unmasked form. We're in the process of removing that manual step in between to allow access to the currently anonymized data. And so where is all this data kept, John? So physically it all runs out of EC2 and it sits in a massive HBase cluster that runs out of EC2 at this stage. Okay. And you're keeping multiple copies of the data? Yeah, by HBase standards you can define within HBase how many copies will redundancy are kept. There's actually a running debate that we're engaging the community with as to how many copies are necessary as well as how much history people want to deeply access because the back end storage system is in and of itself a major systems challenge that we've worked on that involves a tiering mechanism such that the user experience for analyzing more recent data can be delivered in rapid form with very low latencies. And data that goes back in history needs to be moved off that more performant tier onto a not an archive but a slower less expensive tier. We're challenged by many of the same challenges that our end users are. Well, I appreciate the perspective. Just as a reminder, we're here talking about harnessing crowd wisdom for the future of virtualization. And we have Duncan Epping, Frank Denerman from VMware on the phone with us. We have Nathan Smith from Centered Networks and Jakim Hepner from Sanofi as well as John Blumenthal from Cloud Physics. And Noemi Graysdorf VP of Strategy and Alliances at Cambridge Computer Services. So we've got quite a group here, but I'm going to give sort of the last word or last comments to Jakim and Nathan because they're the practitioners there in the field. What do you hope to see from the likes of Cloud Physics or other organizations in terms of helping you improve your operating environments? What are the next steps? This is Nathan. Sorry, go ahead. Go ahead, Nathan. Then we'll go to Jakim. I was going to say, really, I'd probably echo the things that have been said already, which is, for me, it's really three things. One is being able to stimulate those changes so we can look at the outcome of the change before we actually have to touch on any production. The second one would be, you know, to carry out proof of concept without actually doing a proof of concept. I think, as Noemi mentioned earlier, even if you can run a proof of concept, trying to get that to match your real-world data is impossible. You don't know how many hours you spend trying to simulate that workload, but you just can't simulate it. So being able to take a real workload and run it that way is huge. And then for us, particularly, this idea of simplifying everything down to the cards that we keep talking about, where we can very easily, not just someone who's technical, but even someone who isn't technical, can log into a portal and see a kind of almost traffic light system of green and red.  And you can just check through, or rather, you know, the card will look for you, that's the way you mention it. So they would be the three things that we're most excited about. Great. And Yakom? Yeah, I agree with Nathan. You know, again, some of the big things in the future as the virtualized environment gets larger and more complicated, it's going to be much easier to go to an external resource like this and try to simulate changes we might make in the environment, or, you know, if we want to grow it even further. Also, from a troubleshooting point of view, you know, I see that being helpful again as, you know, as other people run into this issue. Are we unique with this problem, you know, before we go down the road of opening a case? Again, the whole notion of self-service and looking at the community for help with some of the more complicated items is a good thing. Great. And just as a reminder, so Cloud Physics website did open up yesterday to the world. Cloud Physics is going to be at VM world. And you're exhibiting, what's your booth number there, John? We'll actually be exhibiting from the Fusion IO booth. Fusion IO is one of our strong partners.  Okay. And so submit your cards, submit your data, and help influence the community and make this a giant group hug. So, again, I'm John MacArthur. I'm here with Noemi Grey's Dwarf. Peer in sight in advance of VM world, harnessing crowd wisdom for the future of virtualization. I want to thank Scott Lowe, Mike Alvarado, David Fleuer for their questions. Also, Nathan Smith and Yacum Hepner, thank you very much for your time today. Noemi Grey's Dwarf, thanks for making the trek into the studio with me. Thanks. Nice to see you again. Duncan Hepping and Frank Denerman. You get the late night award. Well, I guess it's not that bad. It's six o'clock. So, there's seven o'clock there. So, thanks for dying in and being part of today's Peer in sight. With that, if you can, at VM world, please watch the live streaming coverage of VM world on Silicon Angle TV. The Cube will be live there at VM world and have a number of Wikibon analysts there on site doing lots of executive interviews. So, please join them on Silicon Angle TV. We will have research notes up by the end of the week on today's call and you can replay the audio on the Wikibon site or watch a restream of the video on Silicon Angle TV forward slash Wikibon. Sorry, on Silicon Angle TV, my apologies. We keep moving things. So, again, thanks very much for joining us today. I'm John MacArthur at Peer Insights here at Wikibon. Have a great day.


I am George Cao, and I'm courting this the day before Black Friday, which is the day where and the weekend before Cyber Monday, which is where lots of companies give deals and encourage you to buy things at a great deal.  There are two thoughts that create big money leaks in our lives. The first thought is, I might need this later. The second thought is, this is such a great deal. I have to buy it because this deal might not come again. And I will tell you marketers will do everything they can to implant those thoughts in your head so that you'll spend money on something that chances are you're not going to use or it's not going to make you as happy as it was promised. So a couple of examples that are prevalent in my industry is software or coaching programs or training programs or info products. Oh, I might need this training later, so I better buy it now. The thing is, the training that you think you need to buy or the info product you think you need, the guide, the course, it's going to be available later and it's probably going to be updated or it's probably going to be available online for free if you just are willing to take another 15 to 20 minutes to Google it or post a comment underneath this video and say, George, I'm tempted to buy this course, this training program. Is there a free or cheaper alternative for it? And I'll let you know if I know of any, chances are there are. The second thought that's so dangerous is, this is such a great deal. And I would tell you there's a reason why something is a great deal and oftentimes it's because it's going out of style. And that's why it's such a great deal. So please do not buy. Think twice and do some online searching to find and know this. And I'll kind of end the video with this. Know that number one, if you actually need something, you'll be able to find it later at a great deal. You will. Trust me. I mean, just spend 15 minutes doing a Google search or an Amazon.com search. You will find a great deal. Okay. Number two is if you wait to buy, chances are you realize you don't actually need it. And number three, remember that even if you need it later and you regret, oh, I wish I would have bought it. I wish I'd ignored George's advice and bought this thing. Chances are in another few weeks, you'll be just fine and realize, oh, I didn't really need it. I didn't really need it and I can find my happiness within myself or in relationships with others or in experiences rather than buying more things. So stop and plug this money leak in your life of I might need this later. This is such a great deal. Plug those money leaks and I think you'll thank me for it in the future. So with that, I wish you clarity and patience and inner happiness. Until the next video, be well.


I just need Pam to get it. These are my kids. This is their future. Amber, what are you talking about? I don't even understand. I mean I'm talking about how unfair affirmative action is. That has nothing to do with your kids and family. You really, you really don't see it. You don't see how the unfairness is like for the job. The best candidate for the job. I mean that's what is important. Do you not get the history? Do you not get the legacy we are up against that we need to change? You're not getting it, are you? I'm just yelling at oh my friend, my friend. I just don't see any point in watching the news or knowing what's going on. I just believe what I think and that's good enough. Oh my gosh, I just want to shake her sometimes. Wake up, listen, look, learn. Come on, I need to be my buddy in this. I need you to help my, hey, you are so perceptive. I, yes, I am sad sometimes. I want the best for you. Thanks for noticing. Love you mom. I love you so much and I want this world to open up and to welcome you for exactly who you are. You are so needed and beloved and precious and powerful. Okay, that's enough. I'll see you later. Okay, bye. I'll get back to the call. Village to know that we all need to help out. I don't know if I did the right thing, but I insisted as your, your kid's whiteness to make myself discreet in them just to give a little bit more room to their blackness and I know that now you feel like you're thrown in the unknown but I insisted to keep myself very discreet. I did it intentionally. I hope you'll understand one day and you'll be not scared. I welcome you. I welcome all aspects but sometimes I I'm fear. I'm fearing for my children. I know, but I'll stay discreet. That's how it goes. Standing side by side and looking and being and seeing what we need to do together. Opening up our eyes for all the children, for my children, for their beautiful skin to be welcomed in. I need you, my friends. I need MewPam and all of my friends out there to see real. Let their voices be heard. Let my children's voices have been heard.