Vladimir Lormann was the original member of the organizing committee of the first workshop on physical virology in 2012. He was also the member of the editorial board for the special issue on physical virology, which was published as proceedings of that meeting. He was also the member of the organizing committee for this meeting 2017. Actually quite a few of the participants of the speakers at the meeting were suggested by him. And as he passed away last year, we decided it would be appropriate to commemorate him and his contribution. The way we envision this section is that there will be one talk by Andrea Parmigiani, his colleague at the University of Montpellier, describing a little bit the scientific endeavors of Vladimir. And then the other three talks are just standard talks of the workshop, but in one way or the other connected with Vladimir. This is the plan, so I would ask you, Andrea, to tell us a little bit about Vladimir. Then we will have a break and proceed with the other three talks. Thank you very much, Rudi, for this introduction. So it's my pleasure to be here today because I have the possibility to speak about Vladimir that was a friend, a colleague, and a teacher at the University of Montpellier. Somehow also, as you will see later, he is, let's say, the head of the initiative to join physics and biology in Montpellier. And this for some historical fact that I will try to explain, and somehow also explain also the scientific evolution and the endeavor of Vladimir in science in general. So let me tell you first that the family greets you, and they appreciate a lot the fact that there was a session in his honor. We will try to organize also something in Montpellier in the next month. And on the other side, I would like to say also that when Rudi offered me this, proposed me this initiative, I was very happy about that, but at the same time to speak about the work of Vladimir was a little bit scaring for me. Because I collaborate with Vladimir, but I recognize two things. One is the fact that he did very, very good physics. But on the other side, also the physics he proposed is unconventional and unconventional are the systems that he studied somehow. It's a very high level physics. And technically, at least for people with my background, was not always obvious to catch what he was trying to explain to me and was repeating, repeating, repeating many times. So we'll try to propose you a panorama that probably is very incomplete and also suffer of some superficiality. And I think that scientifically there are other scientists here, like Rudi and even more Sergei, that could explain to you any detail of the theory that they developed with Vladimir up to now. Recently there are publications on that. And then of course in all these dynamics, I mean, we also collaborated and we show you also some very recent work that somehow is a very symbolic, very important because somehow join different theories in the same topics in Montpellier. So I would like to start with some pictures that are quite symbolic. I would say about Vladimir activities and life and events. This was the typical object that you could find in Vladimir's office. Unfortunately, I don't have a picture of the construction he made with some magnetic beads that he was used to explain a lot of physics of liquid crystals or assemblies of proteins. But usually the door of Vladimir was open and you could enter and start to discuss. He was taking his tea quite regularly every afternoon, right? And then he had this shape that he was helping to think about his research, but they were also actually used during courses because he was an excellent teacher. So in this, you find elements of what was the physics that Vladimir was developing. And I will try to enrich this feature and to show that despite the fact that he studied many different systems, somehow there was really a common denominator in all these studies. And this denominator was the use, intensives of symmetries, the study of phase transitions and the relation that phase transitions have, for example, with the geometry. And so this touch feels of mathematical systems and the work on catastrophe theory and so on and so forth. Another picture that for me is very emblematic of the work of Vladimir are this picture that he obtained, he published quite recently in collaboration with Rudy and with Sergei. And somehow they represent the accomplishment of the beauty of this concept of symmetry you have in physics. And this was massively used to study the DNA nucleosome assemblies at the level of the chromatin fiber on one side and on the other side to study something that is very close to your topics, which is the viruses assembly and capsids. This is a very emblematic picture for me because this represents the last discussion I had with Vladimir at the Blackboard. It was actually a discussion in which you can find elements of mechanics because we were fighting along with the problem in developmental biology. And on the other side I was discussing with other people about rotary flagella. So as usually in Blackboard of theories you have such kind of mix and maybe some inspiration comes from this kind of disorder. But when Vladimir was writing something it was, he knew where he was going. That was, he was not writing a lot but when he was writing something it was really essential. So he thought a lot before making any kind of computation and so on. This Blackboard by the way to make you a little bit the story is a Blackboard in which three Nobel Prizes wrote on it and also a almost Nobel Prize was actually, is actually the owner of this Blackboard. And this owner, which is Andren Agu, who is Andren Agu, played a very important role in the scientific development of Vladimir's career and also the interface between physics and biology in Montpellier. What to say about Vladimir from my personal point of view? These are my masters. Somehow the people that started from the PhD during Jacques Perot and Frank Schulischer and then during my postdoc Irving Frye and finally when I got an assistant professor position at in Montpellier with Vladimir, I mean these are the people that somehow drove me in science and I recognized that, I mean Vladimir in the last 15 years was really a source of inspiration and beyond the simple fact of publishing, I mean he gave me a different perspective of thinking about physics and the physics of biological systems. There are suggestions that I keep very secret about the system I'm used to study, for example problems in intracellular transport and Vladimir gave me suggestions that I don't tell anybody but I'm hoping to use in the next years and this comes from a field that I would never imagine that could be put in relation with such topics. To describe in some, to start to describe in some condensate way the Vladimir activity, to be honest is an exercise which is a little bit difficult because he studied really a lot of things and he had also a period of work especially during the time in Russia in which it's not so easy to find publication in English so unfortunately I don't speak Russian and I will let you know also what kind of situation I had to leave because Vladimir was Russian and Sergei was Russian, we'll give you a small anecdotic fact a bit later. But what they did was to recover more or less the ensemble of publication of Vladimir and they took the title and they tried to make a diagram of word counting and as you can see you can find the keywords that Vladimir and his collaborator choose for the title of their work so something that in the end is quite representative and it's very interesting to find that at the center there is theory and as a matter of fact Vladimir was a very very serious theorist and for the techniques he was managing and the way he was thinking was really a theorist and I will explain to you in a few minutes also the context the scientific context in which Vladimir started his activities in Montpellier and the fact that was a real theorist was very very important when I look at the publication plus the communication Vladimir did there are other words that emerge from these clouds and you can see here you have viruses virus of course but you have also terms like order so a very peculiar point of Vladimir activity was the study of the phase transition and especially all the very sophisticated mechanism to pass from a state of disorder toward the state of order characterized by symmetries of high complexity so it's not surprising that you can find this this kind of board when you put the you consider also the communication in the ensemble of title of Vladimir production because I think that it was a very serious real concern for him to transmit this notion of transition from this order to order state of course you find other word that for you are very familiar like was a draw or mezzo phase capsid and so on and so forth so now I would like to describe to you some scientific fact the kind of short life description of by dates of Vladimir but then I will try to reinterpret all this in some partially by making also some personal consideration so Vladimir got his diploma in 1981 at the University of Rostov on the dawn in Russia and in 1988 he took his state doctorate at the University at the theoretical physics Institute of condensate matter at the University of Rostov-on-Don and the AM Prokhorov General Physics Institute at the Academy of Science in Russia very few years later 1990 and it's a year in which you know in this in the Soviet Union there is a very serious political situation Vladimir decided to fly to France so in the end is not directly to Montpellier and the map I should point before Amiens and then Montpellier but it flies to Amiens and there he started an activity as a normal post doc while I think his level was for sure the level of researcher but he had the opportunity to go to Amiens and this was the first step of his career in France so if you want to see the date after that he got an assistant or lecturer position at the University of Picardine Amiens and then in 1999 get the position of associate professor and few years later as a full professor at the University of Montpellier this transition from Russia from Rostov to Amiens and then from Amiens to Montpellier correspond to a change of topics in Vladimir scientific evolution that I will try to describe to you in a few minutes in Montpellier after that he took he didn't do only research but he took a lot of complex responsibilities at the teaching and administrative level and up to become deputy director of the laboratory of physics and organizing the interdisciplinary axis and participating to initiative of excellence like the new MAV lab X so it was really working a lot and he was working a lot by taking care also of the community that let's say start to develop just few years later is arrival in Montpellier and the community is still growing up in these days and we try to follow a little bit the perspective that Vladimir gave since the beginning of the 2000s so now let me provide you the description of Vladimir activity and also some important point about his life his scientific life these are facts that have been told to me by Vladimir and partially I really experienced directly because I joined Montpellier in 2003 so a few years later and also this is also complemented with some thought about about this point so in 1997 it took the French habilitation to be a PhD supervisor why this is important because since few years was the University of Picardie and he start to work on liquid crystals intensively and is known by Jacques Pro that at the time was director of a laboratory species in Paris and Jacques Pro is also the president of the jury of the this habilitation title that somehow allows the researcher to become independent because he can follow PhD student he can build up a team and so on and so forth and this is a picture of the discussion between Vladimir and Jacques and for me this is a very important picture because Jacques at that time was my PhD advisor and I didn't know anything about liquid crystal I knew that there was a book that he wrote with the gen and that was a very important issue in science but for me was quite scaring object liquid crystals and of course Vladimir was providing very important contribution at that time so Jacques was a person that helped him in his career and he is supported him a lot so why this is important because in 1996 there is the first big initiative to develop the interface between physics and biology and is the date in which the laboratory of physical shimikuri was born and it was a unit in which we had biologists physicists chemists working all together in the same unit and it was something quite peculiar for the French system. Jacques Pro was called as director from this PCI and this was under the suggestion of François Brochardet-Pierre Gilles Degen that push a lot to help the people in the community of soft matter to get involved in biological physics issues for last year we celebrate the 20 years of this lab and you maybe know it as a very nice place and I mean they are doing very nice things at that time I had the opportunity to be a PhD student there with Jacques and Frank so in 1997 Vladimir got the habilitation and in 1998 he participated to a school the physical of the scale at the scale of the cell that was organized by Bertrand Foucault, Jacques Pro and also Arvange Derri and this year is very important because I met Vladimir there for the first time somebody smiling at you very open and but also somebody that was when was playing some physics for me was kind of foreign language because his way of thinking was very peculiar and I will try to explain to you why this why form this way in during the time so these are here that are very important why because in 1998 Vladimir get the position of professor in Montpellier why well the very important point is the fact that Andre Neveu as a wife in biology but Andre Neveu is as main maybe you know is a is a is a great theoretical physicist that developed theory of super strings but he knew that biology was one of the new frontiers for physics so he wanted to build up a very strong activity in biological physics and in the meanwhile he was also building a very strong community in mathematical physics in Montpellier I would say in the 90s he could he could he was was able to recruit Alexei Zardmologico, Vladimir Fatayev and this is these are kind of divinities in the field of in the context of field theory and integrable systems Mikhail Dyakonov that was a theorist of the condensed matter and the electronic systems that he did the different discoveries and the first person that was recruited in this field of really pure theoreticians from the Russian school by the way was Vladimir and Vladimir was appointed of developing because of his experience in soft matter in developing the interface between physics and biology and all the history in Montpellier start at that time so I think that in this time Vladimir developed the feeling that biological physics was really a direction yet to develop his research and I will focus in the following mostly on this point although I will try also to give you a perspective from the previous year so I described to you the scientific pathways from the 80s up to now and I try to divide them in this in these sub chapters so in the 80s Vladimir is is working on general aspects of the theory of phase transition and crystallization to study condensed matter of metals alloys magnetism but he's also doing something very specific which is the interpretation of the phase transition diagram via geometrical description and the use of symmetries in a way that it was much more natural inspired let's say from the theory of the geometrical theory of dynamical systems he entered in contact with Vladimir Arnold and the interesting point is that if you get this issue from the IOP website you find afterward that the IOP suggests also to watch this paper in which Vladimir is co-author so for me this is when I found this recently I was quite not say excited but it explained to me some kind of draw that Vladimir gave did on the blackboard and on the paper because he was really trying to apply very advanced method from mathematics to understand the physics of the phase transition by the use of of these diagrams and even at the teaching level we were exchanging about this point so this is a point which is very important because then more specifically Vladimir was working on the Landau theory of phase transition at that time and this is something as I told you that you represent a kind of backbone of all his research so after that when he moved to to Amiens he started to work intensively in liquid crystal and quasi crystals and of course he was working on the theory of structure of liquid crystal and phase transition and here you have some publications on this topic he did also a lot of work at that time in this remind to me when I was in some difficult period of my career he was telling me remember that there is there are periods in which you have to produce a very strong effort it's only you that can do it and he was explained to me what was his experience when he left Russia to move to France and then to get adapted to a new world and to work on different topics and in doing this he did a lot of work also with the experimentalist so he was a pure theorist but he was also very open to discuss with the experimentalist and this is key also for the rest of his career after that when he moved to Montpellier well there was this approach to very fundamental systems in biology and here you have the let's say the chapter of the study of DNA crystalline phases and the nucleosome so this assemblies of DNA and nucleosomic particle in the genome that regulate actually the structure of the genome genome and here you can see some relevant relevant contribution and inspired also by experimental facts like cryo electron microscopy produced by a nucleosomic particle produced by Franz Fazlivalon and as you can see here Rudy was very strongly involved in in this kind of topics and from this work these were produced this phase of the chromatin fiber I show you before so here there is a very interesting attempt by by Vladimir and his collaborator to try to describe this kind of assemblies in terms of soft matter systems and no more as a kind of macroscopic solid complexes at that time there was a lot of modeling at the molecular level but Vladimir was convinced that these phases were also the product actually of very low energy mode and the fluctuation of the system and somehow should be this kind of phases should be related to the intrinsic properties of symmetries of this molecular object a very important chapter that concerned this conference was developed just a few years after and here you you find that that I mean this fundamental contribution in physical virology about this new way to describe viral capsid and generalizing the theory of Caspar and Klu this was a work that developed mostly with Sergei Rochelle that is a historical collaborator Vladimir and what to say I think later there will be there will be talks on this subject I think that this is a very very beautiful illustration of I was Vladimir thinking about these systems and of course the physics behind that is is still is always highly nutrivial then in parallel Vladimir was also trying to break some paradigm in other field so the first example I provide to you is the theory of structural structured membranes and protein membrane interactions I think this is a very important paper because somehow Vladimir when he wants to to describe the viscoelastic fluctuation of a of a vesicle decorated with the cytoskeleton so something which is not only a lipid membrane but it's something that looks much more like a real cell he tried to describe this not with the standard language of people describing lipid membrane with the theory of cana madfresh but to use something which is very specific of the russian school of mechanics meaning the mechanics of thin solid shells and of course there were also other scientists that were developing this that at the time but by doing that he he showed very interesting features and somehow in also in this example but I mean also in in this paper yeah viscoelastic dynamics of I know sorry this one cytoskeleton influence on normal entangled fluctuation mode in the red blood cells he was able to explain contradiction contradiction contra dictionary experimental facts somehow he was able to show that the physics of a membrane together with the cytoskeleton cortical cytoskeleton is much more similar to the physics of a solid system than is just a lipid membrane which is always considered something as liquid ensemble of lipid molecules I will focus on this example because this is a very nice example in which also biology got a very important contribution from from theoretical physics this is a red blood cell that is invaded by parasite of malaria and here is described the sequence of the egress of this parasite from the red blood cell this was an experiment performing in my biology lab and and they could use a high speed camera to understand what was the mechanism and this mechanism is composed by three phases the first the formation of a pore by the parasite and then the parasite can escape from the red blood cells by using two mechanical instabilities the first is a curling instability that was described theoretically by Vladimir and Andrew color Jones at that time and then in the final part the parasite that you are in large number inside the red blood cells they somehow ejected in the viscous medium of the blood by a buckling instability like a solid object this mechanical effect is fundamental for the parasite why because the parasite can survive very short time in the blood the plasma it needs to attach to another red blood cells and then invade it again and this is the mechanism by which malaria is very dangerous right so it was very interesting to discover that the physics the mechanics of red blood cells and this still a very it's an ongoing topics in Montpellier but the mechanics of the red blood cells is fundamental for such kind of biological process and of course this all has also implication in from the point of view of therapies because if you can work on such kind of mechanism you can make red blood cells different with different chemical composition then you can you can expect also to reduce the effect of the spreading of this parasite inside the blood the other example and this is also a conventional system in which the theory of Vladimir and Sergei was very important also from the biological point of view is example of the study of the apoptosis life and apoptosis in non-proliferative epithelia so this is a topic that concern a creature that i'm going to show you in this slide is psionantestinalis it's essentially digestive tube that lives in the water but it's a very important as a model system for biologists because first of all from the evolutionary point of view is a system that is between the vertebrate and invertebrate in in the development of organism it's a system for which we know exactly the genome and of course all developmental biologists they they work on it they are quite curious system because from they have a descendant development because in the from the egg which is represented by this ensemble of cells there is a tadpole that escape but this tadpole does not develop as a normal organism but yeah it has a kind of regression and it becomes just the digestive tube that then fix on the on the on some rocks or the bottom of the sea so here you have a picture of this egg and then this you have a very white elaborate tissue you have follicular cells you have a cells that as a nucleus here there is another cells here that is at the base and then you have an epithelial tissue inside in which essentially for each cell at the surface you have 20 cells just below and these cells that can communicate they can exchange material as you can see here the symmetry is very similar to the object that Vladimir started to work on the same time which are viruses and they cause aedral viruses and so it was very interesting the the fact that they him and and Sergei they could elaborate knowledge from this system starting from what they did on solid viral capside capsids and here of course the physics is different because cells here are soft objects but of course by using property of symmetries and counting counting seriously the position of the nuclei of these cells and studying the intersection they could understand also by using statistical methods they could understand that the organization of these cells was not kind of casual one it was reproduced systematically in each egg and this organization was peculiar for the life of the organism why because actually the cells here at the base of this follicle they send an apoptotic message they die and they send an apoptotic message to kill all the cells below by this apoptosis the eggs open and the tadpole can get out if this sequence of messages cannot occur the organisms cannot leave so this was interesting because they provide an important contribution because they could verify that by by by studying the system they could verify that the signal was controlled by this cell here at the base of the follicle to to control the development of of this of this tissue and from that there was the development of a theory of apoptotic controllers which is of course very important from the biological point of view because people are thinking about the possibility that for example not only in developmental biology but also in cancer there could be cells that play a very key role in controlling the destiny and the fate of the surrounding cells if you can control these cells you can also have a way to control the development of the cancer so this contribution as you see they oblige to do some physical work some physics work sorry to discuss a lot with biologists but they are relevant contribution not only from the physical point of view but also from the biological one let me finish about recent work that we developed in Montpellier and here are all the expertise about protein assemblies in genome by Vladimir was very fundamental and we are missing a lot about this but nevertheless we we can accomplish interesting results this is a completely different problem we want to understand how the genome of a bacteria is divided and what is the mechanism which is a non-equilibrium mechanism allow the bacterium to segregate the two copies of the genome and not only segregate but also to position at the right place these genomes inside the bacteria so here you have an illustration of of this event of course this is very important also for application because if you manage to you don't see it so maybe I have to so you it's very important because people are thinking also to control the bacterial division by by developing new kind of antibiotics so you can see this this event that is reproduced very systematically and with Vladimir we could develop a model that reproduce well these kind of features concluding and I hope that I gave you some perspective of what was what has been the work by Vladimir and then you can understand how he could develop ideas that brought us to this beautiful pictures but particularly to these beautiful ideas on which we have to work on along with the time in the in the future but I would like to end this this presentation by making also very important point about Vladimir attitude towards science because Vladimir was not only a good teacher to physicists but was also somebody who was extremely open to discuss about all science and all cultural issue it was a fan of geography and history and and so I think that the best way to define Vladimir is that he was a humanist in the sense of the renaissance Italian renaissance if you let me say this so I leave you with the with the sentence that was sent to us by a colleague from the engineering robotics department that share with Vladimir councils in in the in the department of our science let's say and David Giraud wrote to us and saying a friend who taught us to love the beauty of physics and nature by the kindness of his personality but also by the firmness in the science in you perfectly I think this resumed very well Vladimir so thank you very much


The fourth official fourth this afternoon and take a look at the starting line-up for Foga Road. They are going with a 4-3-3 formation for Stated, Javan Wheatley in goal, Daley Galbert, Javay Cross and Burnett Clarke. They are the back four in the middle of the park, Delton Brooks alongside Captain Brady Reed and Javan McGee and up top. We have Javan Hales down the middle and he's flanked by Neon Clarke and Nevar Brooks. We're hoping to get amongst the goals for Foga Road. Look out for the player to watch Nevar Brooks. One goal, one assist to him so far, Hales and Armstrong. The other scores, of course Armstrong, seat on the bench to start this one. For Gavi Maseo, they'll be going with a 3-4-3 formation. Chris Marmaxwell is between the six, Orlando Lee Blake, Robinson and Wilton Williams are back three in the middle of the park. We have McKenna the number three, Devani McIntosh number two on the flank in the middle, Conroy Williams and Anthony Sinclair up top. Christopher Mundell, you'll know his name. He has a goal to his name so far this season. Clare Clarke has six goals to his name. He'll be playing on the right hand side and DeLana Thompson is the new boy in the number nine four. So the full match highlights, Gavi Maseo, the visitors in their full yellow on the front foot early. Christopher Mundell into the area. DeLana Thompson, the chance to finish, couldn't hit the target. Their number nine went for the acrobatic finish and kicked underneath the ball over the top. Clare Clarke got in his stride, then produced this kind of skill. Just needed a better finish here to keep it under the crossbar. But lovely how he created space and the opportunity for himself whoops onto the right hand side. The shot a bit disappointing from the leading goal scorer of Gavi Maseo. A strike from way out over the top from Robinson and then this free kick with the left foot. Clare Clarke, seventh of the season. And against Fogo Road this season into the back of the net weekly, not across in time. And that came after 21 minutes. This beautiful crossfield pass by McKinley. Their number three. And the first touch from Clare Clarke was very good. Then the strike on target and weakly got enough on it just to point over the bar. Fogo Road, they created an opportunity for themselves, probably the only one in that first half, but couldn't hit the target. They had zero shots on target after the first half. That one from Brady Reed and he just couldn't get it done. Then the start of the second half and they had two really good chances. This the first and it was cut down. Brooks into the area. Nice pass it was from Brooks and just took too long with the finish. Did Neon Clarke and eventually the chance went. Then Brooks again on the left hand side. This time decided to deliver with a right boot. Look at that for a ball and what a miss it was. Very disappointing. Fogo Road could easily have been two and up within 10 minutes of the second half. It was not to be Clare Clarke, the best play on show today using a skill off the upright looking to bend it into the far corner. The right decision from a man who's played at the Premier League level with Cavalier, Clare Clarke. And it was enough his goal for three points. So yeah, five shots on target from their 14 attempts for Garvey Moseo, the two time champions. It was enough against the home team Fogo Road who just had two shots on target both coming in the second half but not good enough, not able to penetrate the goal of Garvey Moseo. Only one goal they have managed in eight attempts against Garvey Moseo. They had four saves, two corners as well, Fogo Road. The majority of the position went to Garvey Moseo and all the goals here at Fogo Road High, one nil Garvey Moseo after 90 minutes, they confirmed their position atop of the group. Let's hear from a water play of the match who is with Gerard, none other than Clare Clarke, the captain. Thank you so much, Chris. Yeah, Clare Clarke, the water man of the match, about to hand in the trophy. Congratulations to you, Clare. Yeah. And let me just ask you quickly though, how much would you rate this performance out of ten? I would rate it eight percent, eight percent. You did see though that you had a few chances that you would have created, of course you were satisfied with the goal that you would have gotten, but if you look back at the chances you created, what would you have done differently to ensure that you scored more? Well, I think I have more space in the ball, could have bring it further, I'm pick a better angle. Yeah, you have 42 goals now in your schoolboy football career, how happy are you with that, and how far are you looking to get? Well, I'm pretty happy because I can say I'm in the book because I have 42 goals in my undercaster cup. I think I can bring it further this season. How far do you think you can bring it? A lot. All right, Clare, congratulations to you all, congratulations on the win as well. So that was Clare Clarke, the water player of the matches here now from the coach of Fogger Road. Coach, not the result you would have wanted though, but when you look back at how your team would have played today, how good was it? It was fairly good. I think our goalkeeper made laps and cost us a one goal. However, we weren't brave enough. If we were just a little bit braver, we could have gotten something out of this goal, this game, but created quite a few quality chances that we should have at least scored one today. Yeah, you would have been forced to change keepers. What do you think about that substitution? How did that work in your favor? Well, the two changes, you know, we have quality players on the bench. So it wasn't as if we're sending out a weaker team with the change because those players are quality players. The goalkeepers kept like the first two games for us and he did extremely well. So it's just that he went on last week with the flow. So we just gave the other keeper another game today. But both goalkeepers are good goalkeepers. So we weren't worrying just that one got injured. So pull him out and put in the other coach. One more quickly. Y'all, three more games remaining in the first round. How do you go from here? Well, we are just focusing on the next game. And at three points in the next game is our most for us if we are thinking about qualifying for the next round.  Anybody can win on any day. So we really have to just focus on ourselves. And if we are able to win the next game, we'll move on from there without even thinking about the final two games. All right, Coach, thank you so much and hard luck today. Emma, you're most welcome. That was a coach from Fogaro. Now we have a chat with Marin Gordon as he embraces his opponent. Coach Gordon, 1-0. Of course, at the start of the game, you would have said that you would have wanted a better result. But are you satisfied with the three points? Definitely, every coach would be satisfied with three points. But I think Fogaro had a very, very good second half. Then they came out, you know. But when you're just leading my goal, especially in a current game, you know, it's going to be always tough. I think they did much better than us in the second half. They were more direct than us in the second half. They were more purposeful than us in the second half. I think we adapted to their game. And I think that was our downfall. First half, I think we had a little bit more control over the game. Second half, we allowed Fogaro to impose what they want on us. And I think they did well. But we were really happy for the three points. Yeah, do you think that you were able to create enough chances in this game, though? Yeah, when you're playing a game like this, you have to try winning from first half. And I think we created a number of chances in the first half where we should have won the game. But such is the game. These are youngsters, and I'm really proud of them. I think a captain today really led from front with how we played. I have a few chances that I think he should have buried with a player of his standard. But we're happy for the three points, happy for the team effort. How does move on? Yeah, you moved to 15 points now, very close to qualifying for the second round. To 13 points, rather. They're very close behind you. But do you think that's how it's going to stay now from here on in just three games for me? Yeah, man, I think that game that we drew against Kemcil really was our turning point in terms of letting the game get it in the table to be very close. But in this parish, though, any team can turn up and play. I always say that you have teams in this parish who don't come out of the round, which I think they would have probably won a different group. It's a tough place to play. It's very good for the boys, very competitive. And I really love what today looked like. And I think it wasn't the workbook for us. It was very, very tough for us. Fogarot really did well. All right, Coach. Thank you so much, and who about them today? Yeah, man. Thank you. Thanks for having me.


All right, so thank you. This is the final session of the canonical track. It's been an extremely interesting day, which we've had pretty much standing remotely the entire day. So thank you for coming along. This is also one of the most interesting sessions of the day. We're talking about architectures. But before we get into the canonical reference architecture, we wanted to introduce you to one of our customers that's using a reference architecture, an Ubuntu open stack reference architecture. And it gives me great pleasure to introduce Kanki-san. Thank you so much for coming from NEC, who's going to share some of the details about the implementation of Ubuntu open stack at NEC, and some of the tooling they're using, and some of the benefits they're getting. Thank you. OK, may I start? OK, hello, everyone. My name is Takashi Kanki, coming from NEC Corporation in Tokyo, Japan. Today, I would like to talk about our open stack-based product and service. OK, go ahead. Look at the picture located on the bottom of this slide. This part describes our technical activities for the open stack. We call it technology platform for the open stack. The left side shows our community activity. No, no, no. The left side shows our community activity. Our world-class engineers joining this open stack community and contributing. And the second one is alliance activities between open stack distributors. We have built very close, collaborative, relations with canonical Ubuntu team and utilize the Ubuntu distributions for our product. NEC has been stepping up these two activities simultaneously. I think we have established industry's top-class open stack technology platform for now. This is our advantage. So we utilize this technology platform to leverage our service and product development for our customer's benefit. Take a look at the upper side. This part shows our service and product. We have been started remote computing service on this April. We call it NEC Cloud Years. Our team has learned a lot of things through this years business. We had a lot of suggestions from our customers. So we accumulate the knowledge and we utilize it to roll out our on-premise years business. First one is NEC Cloud Years reference model, which is kind like a system integration service based on the difference implementation of NEC Cloud Years. The second one is a Cloud Platform for Years, which is a tanky appliance for years. That is abstract of our accomplishment so far. OK, next please. This is a concept of our on-premise years business. We will apply these two different solutions for the different market and different value proportions. We think the reference model should be applied to the large enterprise customers. And the tanky appliance should be applied for the small size years. OK, next please. I will talk about the future of NEC Cloud Years reference model. It is an on-premise system integration based on the difference implementation of our data center. It's quite impossible to deploy it on-premise with the same size as our massive scale data center. So we will deploy a downsized system of our data center with proven configuration with the same product. It's able to start small size for the customer's POC and able to scale out its production phase. OK, next please. Next, I will talk about the reference of our future of Cloud Platform for Years. This is a tanky appliance for years solutions based on the open stack. All components will be integrated in our factory before shipment. So it's able to reduce lead time for setting up drastically. It's able to start small size from seven nodes minimum set and able to scale out easily. OK, that's all my presentation. If you want to know about the detail of our service and product, please drop in on our NEC booth. I thank you very much for joining us. Thank you so much for sharing that with us. Good, so given a second time, a great pleasure to introduce Mark Shudworth to talk through a little of the Ubuntu Cloud, Ubuntu OpenStack reference architecture.  What we need is a reference architecture for OpenStack and you'd see that. And now reference architectures are like standards. There's so many to choose from for every shape and size and the problem you have is which reference architecture is going to be right for me. So rather than present just another reference architecture today, we're presenting the architecture that we think is optimized, optimal for all kinds of sorts of deployment. Can I skip this? Are we on? Yes, yes, we're time limited anyway. So bye, all minutes, Steve. Hello, everybody. There was a great question earlier on in a session on Hadoop, where somebody noticed that Rabbit and Hadoop, I think, were co-located on a common machine and asked why, in that particular case, Rabbit and Hadoop ended up on the same machine. And the interesting thing for me is that architecture is not really at all about the bits themselves. It's about the way those bits are combined. And so one of the very strong sort of principles that drove us early on was to say, well, we want to encapsulate the bits in such a way that we can experiment very quickly and combine those bits in very different ways. And the reason for that is because there really is no single best architecture. When I look across the incredible variety of environments in which OpenStack or any other large distributed piece of software finds itself, you always find yourself in a situation where, for example, you have a test cloud or a test Hadoop or a test cloud foundry. You have a staging one and a production one. And so the question of what's the right architecture is a little bit tricky, right? Because the set of values that drives you to an architecture decision is in some cases extremely dependent on the context, tests, staging, production. And it may also be dependent on the workload. So even in the case of Hadoop, you can ask different kinds of questions that derive things in different kinds of ways. In the case of OpenStack, obviously, you can throw completely different workloads at it. So what I really want to do is start with a couple of sort of values and principles that I hope that have certainly come to guide our thinking, although one can't be dogmatic about them, right? There's no dogma, there's no ideology. And we have the great privilege of learning from many people. And I have to say, so Konkison spoke a little bit about NECs, the engagement that we have with them and we have learned much from that engagement. And similarly, each different environment teaches us many different things. We do believe that over time, clouds tend to the general, I don't know when I say that, tend to the general. By that I mean that if you're successful with a cloud, especially a public cloud, you essentially can predict very accurately the aggregate behavior of that cloud. Because of course, if you're successful, you get every kind of workload. And just as pollsters can predict the outcome of elections, but they can't tell you what a particular person is going to think, right? We can, in the aggregate, for successful large clouds start to make strong predictions. And a lot of what I say here is really applied to, because our focus is scale, our focus is the largest clouds. Our clients are building, you know, aspire to build and do build very, very large clouds. A lot of what I'm saying here is super relevant if you are building a really large cloud. And you have to figure out how to convince it down if you're working at a smaller scale. It's a little bit like saying, okay, well this is how a gas behaves.  And they behave a little bit differently, right? So a cloud that hums TM, like it's not a trademark, go out there and spread the word. A cloud that hums is like the one thing we keep saying to each other. How do we make sure that this will be a cloud that hums, not a cloud that squeaks, not a cloud that howls, right? And what I mean by that is that a nice cloud's like cooking, you know, the sound of a happy pot, right? And a cloud that is well-designed and is handling its workload hums, right? Everything's doing a little bit of work. And think about it, there's an economic principle to that, right? If something's not doing some work, then why did you buy it, right? And if you haven't sold it, then that's a problem if you're in a public cloud kind of environment. A lot of this sort of comes back to economics. There are a couple of key guidelines there. We want to make sure that, that this is the sort of overarching statement. We want to ask questions about, for example, the consequences of a failure, right? So a lot of people spend a lot of time arguing about HA and architectures for HA and some things. As you'll know, a million different ways to put an HA label on something. But the deeper question to ask is to say, okay, what are the kinds of failures I can have? I can lose a node, I can lose a switch, I can lose an AZ, right? Or I can lose a region. Those are the kinds of failures you can have. And the question really is, in each of those scenarios, what's the consequence? And the guiding principle comes out of here is, is to really think about the consequence of failure. Now I'll give you an example of that. We often see architectures where you put all the admin stuff on one node. So you've got the rabbit and my sequel and the, all the glue, all the sort of stuff that connects the stuff that happens. And of course, in an HA article, Cloud, you may have three of those. Now, even in an active, active sense, many of the components that you put in an active, active environment, they work in the sense that there's a leader, right? And in fact, everything's talking to the leader. Not on the super modern software, but let's be honest, there's quite a lot of not so super modern software that makes up a cloud. And so there is a leader and when there's a failure, you may well have active, active replicas of the data. All the data's here, all the data's here, it's ready to go, but everything has to be told. Stop talking to the thing that's dead and talk to the thing that's live. So even in active, active scenarios, in many cases, there's a period of distress when you have a failure. And imagine that you've put all of those services on a single node and that node goes down. All the things which were leaders are now essentially going through that period of distress. What do they have to do? They have to re-sync, reconnect, re-establish confidence. If you've got an external agent, 12-factor app, you've got an external agent looking at that thing, saying you're in distress or you're fixed or you're fixed or you're fixed, it's suddenly having to do that for five or six different things at a time. So simple rule. Try to minimize the consequences of a single failure. Here's another sort of guiding principle for us. Failure's non-linear. Take, you know, we had, on this machine, we probably still have OpenStack, Juju-deployed OpenStack on the bare metal, and then on top of that, Juju-deployed Hadoop. And what we did is we added Hadoop instances on top of the OpenStack until it started to hum quite loudly. And the interesting thing about it, you know, you take a machine and you add, you know, two VMs, great, four VMs, great, eight VMs, and you keep adding it, everything's fine, everything grows nice and linearly until it doesn't. And failure is non-linear, right? In other words, as you add resources, you'll get to a point where something fails. You certainly will. And the key thing to realize is that the first failure is your limit. And a lot of people spend time allocating resources, and they'll say, for example, I'll have my network for storage and my network for compute, great. How useful is a cloud? How useful is the compute when none of the storage is accessible? Not very, right? So if you design for compartmentalized things, typically, the thinking that's driving that is old thinking, right? What you've done is you've essentially said, one of these things will fail first and I don't know which one it is, right? And when that's failed, the other things that I provided may have plenty of spare capacity, right? But the spare capacity's kind of useless for me. And again, economics, if you're selling that cloud, great, you paid for all of that spare capacity, you're never gonna use it, because this part fails first, right? So a cloud that hums is a cloud that kind of everything's working. As you add a load to it, you increase the hum everywhere equally, and you try to make sure that if it's gonna break, it all breaks at the same time, which sounds terrible, but it makes sense, right? Don't try to predict the future. We see a lot of people spend an enormous amount of time, architects spending an enormous amount of time trying to design a cloud for a particular set of expectations. And I wonder where they've learned what that's gonna be, because I don't know, you know what I mean? The game is changing so fast, the apps that are coming to the cloud are changing so fast that especially when you're starting out, it's really difficult to know exactly what you should optimize for. And so this is one of those cases where it helps not to think about it too much in advance, right? You wanna create pools of capacity. Your success is really gonna come from attracting developers, and if you think about it that way, you're more likely to be successful over time. And then this point about that successful clouds tend to the general. So it's a slightly tricky thing. You want to build a cloud that's gonna be really successful for the application or the team that you're building that cloud for, but if you're successful, I guarantee you, all of the optimization that you did for that particular workload will become less and less relevant because those developers will push more and more diverse things to that cloud. So some high level kind of guidance. So where does that leave us? So here's one thing that's driving a lot of our design at the moment, hierarchical storage. How many folks are actively using hierarchical storage? Good man, excellent. So hierarchical storage. Storage comes in all sorts of shape sizes and prices and performance characteristics, right? SSDs, rotary. And lots of people sort of say, well, I guess I'll need to have a pool of SSD and a pool of rotary. And we're quite used actually to sort of thinking about stuff that should be on SSD and stuff that should be on rotary.  And you know that the more you buy, obviously the better the price will be. So there's a big economic story there. So you're kind of thinking, trying to think in advance, how do I plan for what I'm gonna buy?  What you will almost certainly find is that you were wrong about one of them. You guessed a ratio and you'll be wrong. And that means that one of those will be full long before the other is. Problem there of course is that you paid for that stuff that's not full and it's sitting there unused. So we try to invert things around. We try to make everything look like SSD. And the way we do that is using there are a range of Linux capabilities, DM cache, B cache and so on. And what they allow you to do is say, essentially stack those block devices in such a way that to the application, to the kernel, to the system it looks like there's just one big one. The size of your cheap rotary disk. In fact, you've got a little SSD sitting in front of it. And when you write to that big rotary disk what happens is it first gets written to the SSD and then it comes back and says, okay, I'm written. That means your application can get on with life. In other words, you've reduced the latency of that write. At that stage the kernel will say, okay, great, we said we were done. We actually have a copy on disk if we lost power, we're fine. But I'm just gonna write again to the rotary disk. And that way, hopefully I've got time to do that. That way I've now freed up space in the SSD again. And so what do we do on storage? We tend to say, well try to estimate, because one can do this pretty accurately, try to estimate the ratio of SSD to rotary. And then just by the rotary that you need, knowing that you can keep adding up to a particular kind of ratio. And so you're able to essentially provision storage as you need, make it all look fast, right? When people talk about fast storage, nobody ever goes and reads the entire library all at once, right? People are reading a bit of this, a bit of that. And mostly applications slow down when they're trying to write. So hierarchical storage everywhere. There's another clue in there which is that everywhere piece. We see a lot of architecture where you have a storage cluster, one form or another, and a compute cluster of one form or another. And what you're guaranteeing in that environment is that you're almost certainly never talking locally to storage. Now local storage conversations are many, many times faster. I love Ceph dearly, right? But there's latency, there's laws of physics, right? We've got to, if we're gonna write to the network, we've got to go out to the network to one of three nodes right, right, and right again. And only when the last one of those is done, typically am I gonna be comfortable that that has been written, right? There's latency, it's gonna take time. Local storage is a beautiful thing, right? So again, with hierarchical storage everywhere, what we're doing, we're saying, okay, just put a reasonable set of disks into every node, put a SSD in front of it, carve that up with some for Ceph, some for Swift, some for local, right? But all hierarchical. So everything looks fast, right? Your local storage looks as fast as an SSD, but it's as big as a CheapSlow big rotary disk. And your Ceph, yes, you still have to go over the network to write to your network storage, but at least the writing doesn't take very long, right? It comes back as soon as the SSD says it's written. So this is a really big driver for us. The economics of this are fantastic. We added Bcash support, there's DMcash and Bcash are the two to look at. We added Bcash support to 1410, and it's been immediately adopted very, very widely. It's great, clean, and robust code. The performance on NVMe SSDs is unbelievable. You're now up to 900,000 a million plus IOPS. And so the acceleration that you get by one of those devices in front of 20 terabytes of rotary is fantastic. 20 terabytes of rotary now is cheap. And that SSD may be quite expensive, but it looks now suddenly like 20 terabytes of SSD instead of half a terabyte or one terabyte. So that's one big story. Oh, look, I had a picture. What a very pretty picture. But the interesting thing on this is that you can see perhaps that in fact that's a compute node. So when I say storage everywhere, I really mean storage everywhere. We are increasingly able to isolate and pin workloads to CPUs and guarantee IO latencies and so on and so forth. So what's the difference between Cep running on one of your compute nodes where you've allocated it and can defend the allocation of just enough CPU to make sure that that doesn't stutter, right? Okay. Distribute all the work widely. Again, if we're going to hum, then we want to be as distributed as possible. And the controversial part of this is that that includes potentially the admin work that's running the cloud, right? What's the difference between a 36 core server which has four cores running MySQL which happened to be providing database services for a cell, which will never get bigger than a certain amount, right? And a dedicated server which has the same essentially ratio of cores and storage. Very little. The difference is if you've fragmented your device types, right?  And if they're special, that means you've had to provide a special set of things for that. Whereas if you've said, okay, look, we've got as flat a configuration as possible. We have lots of cores and lots of RAM and hierarchical storage in as many places as possible. You can grab that resource to recover that service as fast as possible anywhere. You don't have to go anywhere special to do that. And this is the bit that I think we're gonna see the most evolution on in the next 12 months, right? So we've talked a bit about storage and principles there. We've talked about compute principles there. This is the bit where I think everything's gonna change in the next 12 months. People often think about networks and throughput, you know, one gig, 10 gig, 40 gig and so on. To me, the key thing to be thinking about is latency because for so many cloud operations, whether they're administrative operations, start a node, right? What does that mean? That means a cascading series of HTTP calls and AMQP messages, right? Every single one of those laws of physics has latency associated with it and they add up. Launch a hundred nodes and you may be generating tens of thousands of messages, right? And all of the latency of those adds up. So the latency of the network, we think, is far more important or much more important than people have necessarily given it credit. So the intersection of HPC and cloud, I think is gonna be a huge focus over the next 12 months. I may be wrong about this, but where we've seen low latency networks, the cloud feels much faster. Right? There's also really interesting generations of generational change happening. We went through a phase of convergence where people sort of took a rack and put it in a box, but it was still essentially 10 gigi with all of the same latency type properties. I think we're about to see a phase change essentially in the network and that's something to watch really, really closely. If you're in a position to get early access to that, if you're in a position to evaluate that, then I would really urge you, because my sense is that, you know, again, where we've seen low latency networks in Finneban, not FNNET, or other technologies, there's a material impact on the whole performance of the cloud. I mean, imagine CIF where all of those round trips are now a third or a tenth of the time, right? It really starts to change the dynamic of the network storage versus locally connected storage. So in a terribly ugly picture, right? What do you want? The flattest and fattest network with the tightest fabric, in other words, the lowest latency, right? Again, see a lot of people spending a lot of time trying to look at their network and say, well, I'm on a spine with this kind of bandwidth and then edges with that kind of bandwidth. Well, how can you predict which VM is talking to which VM, right? If you can, magic, I don't know how to do it, right? And I know that if the cloud is successful, I definitely won't be able to do it because everything's gonna be everywhere. Now over time, I think we will see annealing technologies in the OpenStack controllers. By annealing, what I mean is that when somebody asks for an orchestration, an application to be spun up of 50 Hadoop nodes and a bunch of other analytics and blah, blah, blah, blah, blah, what we'll do is we'll spin that up as fast as possible, right? Then what we'll do is we'll look at patterns of traffic. We'll say, what's talking to what here? And we'll look at patterns of isolation, right? What's not supposed to be on the same failure zone however we've defined that? And then we'll anneal. In other words, we'll say, well, if I just move this part to here, now two of its conversations become lower latency or local type conversations. And I haven't broken any rules of isolation or separation. So I think we will see that, but for the moment at least we don't have that and it's not predictable. So everything's gonna be talking to everything and you may as well essentially go as flat as possible in your network. In compute, the real question there is the RAM core type ratio. And then as admin, as I said, the real question is whether you're willing to go as far as distributing admin widely, obviously, but actually interweaving that with compute. Okay, Mark. Thank you. Thank you. So I think, thank you for that overview Mark. The, when we were looking at the architecture and indeed drawing this out on whiteboards and other areas, it's very easy to fall into the trap. And I'm sure others have done this of drawing a logical architecture and then mapping that to a physical architecture. I have my storage resource, I have my compute resource, I have my controller nose and separating those, putting those on different boxes. Certainly we do it. We'll have fall into that trap before, but logical doesn't need to equal physical, right? Just because you have storage on the diagram as a separate pool doesn't mean it needs to be on its separate box. And as an example, in our reference architecture, we're sharing with you, we put storage on the compute node by design, right? Not necessarily in a dedicated pool. The bits that everybody cares about, of course, in an open stack cloud, are the key services, the cloud controller services. So it's, you know, obviously horizon, the teleometer, the database services, to believe MySQL, messaging services, but Keystone, all of these Nova services, right? The cloud controller services, plus the messaging, plus the database. When you lose these, then you can have problems, right? This is when problems start. Just to refresh on terminology, a region of course, different areas of essentially, it's a bit across data centers, if you like, completely separate infrastructure apart from the shared Keystone environment for your authentication. Cells where you allows you to be able to scale out your open stack environment by having compute, having the messaging rabbit and the cloud controllers located with compute, but using an API, cell, in fact, service, if you like, to be able to interact with that environment, having multiples of those. And then an availability zone, where essentially your compute resources, and sorry, apologies for the diagram, continuing the poor diagram meme here, but the Nova compute services, essentially sharing the same block and object storage, plus the same cloud controllers.  This is standard architecture stuff. I'm just ensuring that we have the same terminology here. Conventional wisdom, right? I'm sure if you've been to reference architecture sessions this week or at other summits, there's a lot of conventional wisdom around how you build a reference architecture, what a typical reference architecture looks like. And often it'll be a load balancer, 80 proxy for example, talking to those cloud controllers, you can have two or more multiples of those with the services on those boxes. Likewise, the rabbit, sorry, messaging and database services, set up on the same server with high availability type of technologies, whether you're using DRBD or Coruscant pacemaker type setups to be able to fail over your mask or environments, even if you're using Galera and other pieces. This is kind of standard motherhood and apple pie type of reference architecture for open stack. All goodness. And then of course, dedicated storage, those storage arrays that are running your block and or object storage to be able to manage those control points. That's conventional wisdom. And indeed, there's a lot of goodness in that that we use, that we have implemented at places like NEC. So as an example, we do use the Galera libraries for active active, right? But we're very cognizant of the fact that those changes are synchronized across the node. So a right to that environment is only as fast as the slowest node, right? So people use Galera here, a few, good, good, good. It's good practice, absolutely we endorse it. Likewise, in the other areas, rabbit and queue. So we use mirrored queues with rabbit and queue to be able to scale that environment out. It's new active active, right? So there can still be some limitations. You don't wanna just keep adding an infinite number of rabbit nodes. But you know, it's definitely good practice. And likewise, MongoDB, if you're using Solometer, use MongoDB and replica sets to improve high availability, right? And redundancy. MongoDB giving of course a scale out, a great scale out data technology. Finally, Sef monitors. If you're using Sef, as Mark said, we love Sef. We would certainly recommend it as part of reference architecture. Using three of those, this is good practice, right? We're not gonna tell you to do things differently. But cloud thinking requires the use of shared pooled resources. So having those islands, having the island of storage, having an island of compute, having islands of cloud controllers, islands of databases matched with rabbit and queue or with a messaging rather set up in HA configs. We don't think it's the right route to be going. So as Mark was saying, what we want to do is spread our environment across as many servers as possible. So on the compute nodes is locating MySQL, messaging services, the Sef block storage and the Swift, but spreading it across that compute environment. And you'll see the CC, because I didn't have enough space because I'm a very poor artist, to write cloud controllers, right? Of course, we're setting these up in a way. I've got the diagram right. Yes, we're setting these up in a way that each process is not going to gobble up the vast resources, the available resources of that unit. So using containers, we love containers. If you've been in our sessions today, it's containers, containers, containers. We did a lot of work with LXC. We announced LXD this morning to be able to provide live migration of containers. Still the best demo of the day. Thank you, Tyco. So the database messaging service in LXC containers, where we're managing what resource they take using the C groups and nameswaces, right? So we can allocate four cores, 16 giga ram to MySQL, likewise the rabbit, right? Typically we wouldn't use more than three of each because that's kind of optimal unit, but we can still spread the cloud controllers because they scale extremely well with HAProxy in front across very many machines. Smart of you all noticed, okay, well, if we're only using three, at what point is that MySQL environment gonna start getting hit too hard? Is it gonna become a bottleneck? What about rabbit? For those of you who saw James Page's talk wherever James is this morning, talking about some of the challenges scaling to 500 nodes, right? Which he did in the performance test. Great details and you should definitely look that talk up if you're interested in that level of scale. So we'd suggest limiting this in cells, not suggest we limit this in cells. Cells are still emerging, but limiting in cells means that we have great control over the amount of resources, the number of nodes, the number of, it's ultimately VMs that are gonna be placing the demands upon those units. So it makes it very controllable, but very scalable and creates a cloud that hums, just hums across that cell, hums, TM. So for networking, again, motherhood and apple pie, we recommend the standard types of network separation. So a service network, public network, I won't read them all out, you can see them. And in fact, hopefully I've got the pretty diagram that shows us, a flat diagram. So separate out your different types of network requirements. But these are, again, don't confuse the logical with the physical, right? These can be VLANs, absolutely. But we suggest is stick a neutron gateway on every host. This is new capabilities, new features. This is a Juno-led feature, I believe. I'm looking for James to nod at me at the back. So this is new, and this is, you know, we are on right at the forefront of thinking here, how we can architect in a long day, architect and optimal architecture. So putting a gate on every host means we're limiting a bottleneck that previously existed within Neutron where everything had to go via the one unit. That's why everyone was putting Neutron on the bare metal, on a big box, with lots of CPU, with lots of RAM, because that could be the limiting factor. James, again, to steal some of James's from earlier on, he was talking about some of the vast improvements that have been made using Neutron gateways in Juno. The fact that it was able to get an order of magnitude faster jumping between Icehouse and Juno at the networking layer. So spreading across our pooled resources is the way that we believe we can make this successful. So how do you get there? So I'd like to ask Tycho and Dan at the back, just to come up and show you very quickly one of the ways that you can get towards creating a scale out cloud that uses these pooled resources. Yeah, so while we're handling that switchover, I want to do two things. First, I really want to have a session here that's not Ubuntu and not tied to any Juju or Maz or anything like that. This is really about principles. You should be able to replicate this on any platform. Great to see some red hats in the house. And go make the most of it, right? And what we'd really like to do is learn from each other. We learn a tremendous amount from customer engagements. And sometimes these architectures don't turn out to be right, depending on hardware selections or workloads and so on. Also, the point of this exercise where we will use Juju and Maz is actually to make a key point, which is that the way you learn is by being wrong. And the way you find just the best way to be wrong is to be able to make that cheap, right? If it's gonna be cheap and quick to be wrong, then that's okay, you learn something and it didn't cost you much. So I mean, the right approach to architecture is always to have a good idea of where you're going but then be able to iterate really, really quickly, do experiments, bake teams off against each other. At one stage, we were having kind of pizza competitions to say, okay, teams have ideas about what we can do and then we can, as long as we can try them cheaply, right? Whoever gets the best benchmark keeps the pizza. So if you take that approach, right, a very, very rapid iteration and very cheap iteration, then you are in a very strong position to end up with the right architecture for your particular use case. How are we doing? So the tool we're going to use here, the tool we're going to use here is actually the what we call the unmanaged installers, all open source, it's all in Ubuntu. And one of these orange boxes, the center one, is basically set up to go.   But in this exercise, you can create whatever architecture you want, right? It could be a stroke of brilliance that teaches us all something or it could be Darwinianly futile. But the point is to be able to iterate very quickly and try a particular architecture. You guys good to go? All right. So I was setting up, I know Mark said a lot of things, I actually didn't hear what he said, so. We spent the last session talking about building big scalable clouds. That's something that we do a lot. We're very good at it, we're very proud of that. But how did we get there? We got there by actually building small clouds. And like Mark was saying, being able to iterate very quickly in order to do that, we needed ways to actually get to the big ones and obviously you can't iterate as quickly on very big clouds. So you all saw today that we launched the OpenStack installer and the autopilot program, which is our embodiment of the reference architectures that Mark has been talking about. So when you want to build big serious clouds with our reference architecture, that's the way to do it. When you want to actually iterate very quickly on a small scale, you can do that as well. And as you see, it's as easy as sudo apt-get install OpenStack. Control plus. Oh, no, it's not. So we got the OpenStack package. Now it's as simple as sudo install. Okay, so this is our small scale, iterate very quickly installer. It's also the path that'll bootstrap you to the landscape installer. So basically it's just asking you for an OpenStack password. Okay, so then you have a couple of options. You can do a single system install. So everyone probably uses DevStack. DevStack is great, we love DevStack on Ubuntu. But DevStack is basically running from tip. What if you want the DevStack experience but you want it with our supported packages and you want it basically using our tooling? We can do that now. Single system install will actually create a container on your laptop, on the system you're running on, whatever it is. So it's completely safe. It's non-destructive to anything on your system. Within that you'll actually install a complete OpenStack. It takes about 10 or 15 minutes, depending on the system you're running on. And you're good to go. The second one is that we actually have the ability to run a multi-install, which will actually talk to a NAS. So you'd have a pre-existing NAS. You can just point to the NAS. If you don't have a pre-existing NAS and it's all net new for you, it'll actually give you the option to install NAS so you can see one with existing and one without. The landscape path, obviously, we want everyone to give this a try. So you have to get install OpenStack. Give the landscape path a try. It'll install landscape for you. Publish the URL for you to go to and landscape will take over from there. So I'm actually gonna kick off the single. The network here is pretty bad so it's not gonna be all that exciting. But you'll see that it's actually creating container. That's gonna take a long time because it's actually downloading the image. But just so you get a feel for what that's about. So I have a multi already set up here. So if you chose the multi-install path, and this is one with a pre-existing NAS, so the center orange box there actually has a NAS on it right there. So that's the NAS that's connected to. You can see a bunch of nodes there. Node five is actually the node that I was just on where I was showing you the actual OpenStack installer. Node three is a juju bootstrap server that we already did just because we wanted to get you to the actual experience. Just so you know too, if you went to our website, these are the instructions for installing what you're seeing here. It's as simple as adding a couple of repos and you can see there is the sudo apt-get install OpenStack. So we try to make it as easy as possible in that it just works. So then if I switch over. So what you see here on your Lapt or all the services needed to install a base OpenStack on the right or all the systems that are currently in our NAS. And basically nothing's assigned right now. So, oh, apologies, hold on a second. Part of my cheat sheet. Okay, I'm not on the right network, apologies. Yeah, so while he's doing this, I can tell you a little bit. So one of the things that we did with this is we built this entire install path with our tooling. So even if you try the non-landscape branded version, you will still be using juju, mas, all of those things. So if you're interested in, like we say, the single install, build an OpenStack on my laptop using juju, this installer will do that for you. What else can I say? I guess we have the multi-install will set up a mas for you like do all the sort of mundane things, like you have to sync down images. You have to sync down images from the cloud and all this stuff you have to set up and our install path will do all that for you. So anyway. So then what you see here is by default all the services are unassigned. We have the option to auto place the services if you want, so hit auto place. You can see what I did here is, I can speak loudly, but on node six it auto assigned in eight containers, all those core services, and then you can see on node eight it auto assigned neutron to bare metal because neutron doesn't work in a container today. Same with compute. Compute requires either KVM or bare metal. So by default, if you just want it to do it for you, it has very simple logic and it'll choose the best fit. But if you want to play around with it like my market said and you want it to iterate, you can clear all the default placements. Then I can go down for instance to open stack dashboard of the horizon. And it'll actually give me the option to go one by one for all the nodes that are available and assign it to either as a container, as bare metal. So I'll just pick for instance node one and I'll put it as a container. So you see it actually went from one side to the other and it's assigned to node one in search on node one. You can see it's assigned as a service on node one. So there's lots of flexibility there. I know I don't have much time, so I'm gonna clear all the placements again. You'll see that they all go back. We're gonna do auto place, which auto place them all and I'm, yeah, clear my filter. We'll be done in one sec and then deploy. Guys, thank you very much. Thank you very much for your patience for sticking with us. I hope you've had a great day and I hope some of you will join us at the Musee de Sey. There are buses leaving from the Hyatt lobby at 6.30. Starting at 6.30 and continuing on and then buses going on from there to some of the other functions and parties. Thank you very much. I hope this was useful. I hope that's useful. There's a nice quick, cheap way to do quick, cheap experiments and learn tons of stuff. Please come and tell us what you find. Cheers.


Nancy Burke is a past NEA Foundation grantee and has worked for the last 20 years as a special needs educator at Haverhill High School in Massachusetts. She's a leading proponent of farm-to-table school gardens and has created two gardens at her school, a learning garden and an outdoor science center and orchard. It was originally meant for our special needs students to have the opportunity to learn where their food comes from and for them to make healthy choices. Nancy is a paraprofessional educator and works with students with a wide range of disabilities. I work there with the kids and help them do everything from academic classroom work to float around with them to cooking class to art class to sewing class. Whatever they need me to do, I fill the void and help them. The other thing I do is if they're in a wheelchair, I teach them how to access every part of being able to get out into the world. In other words, use a chairlift, how to use an elevator, how to use and manipulate and get themselves around a building. So I teach them all that sort of stuff. That sounds like you're helping them try to be more independent. That's what I'm doing. I'm trying to foster 100% independence wherever they go later on in life because my story I always tell the kids is when you're 35 years old, I'm not going to be in your back pocket. So you have to do this yourself. You know, you got to learn how to do these things. In 2012, Nancy realized her kids needed to learn about food. At a farm to school workshop, she heard that most children didn't know where their food came from. She couldn't believe it. So when I went back to school on Monday, I made it a point to ask all the kids that I work with, which we have like 77 students give or take. And this is at lunchtime. I said, you know, where do potatoes come from? Where do potato chips come from? And where do carrots come from? And they all said, oh, Miss Nancy, you're crazy. Everything comes from market basket. And I said, no, really, how do you think market basket got it? And none of them knew. And I was blown away and I was shocked. And I said, oh my God, I've got to do something. So I started out small. I first went to the principal and asked if I could have an abandoned courtyard at the end of the hallway where our classroom was.  So I got this courtyard and I ended up having to get it cleaned out. It was disgusting. I got the junior ROTC kids to help out the football team to help out the wrestling team. And they cleaned, helped me clean out the entire courtyard.  And it was just gross. And then after that, I started with one raised garden bed. And it was called the salsa garden, which is tomatoes, peppers, cilantro, and a few other herbs and spices. And it's a raised bed. So anyone who sits in a wheelchair or has a walker or even just regular typical students go out there and they help plant everything. They help water and care for everything. And then they also help with harvesting everything. The second year we did the stew garden, which is potatoes, carrots, and other herbs and spices we grew, and onions. Because those are all fall harvesting vegetables for us where we live. So you started with one garden, then you had a second garden. And now you have an orchard? I have 20 apple trees, 10 pear trees, 10 plum trees. And I have one cherry tree because I couldn't get any more. They were out of stock. And then the school built us an apartment now for us to teach them how to be independent at home. And it's half of the room is a classroom and the other half is an apartment. And we teach them how to cook. So they've learned how to make pasta salad, garden salad, blueberry muffins. You name it, anything that I could think of. Last summer we made our own homemade raspberry jam. When I see the kids digging for potatoes in the bags that we dump out the dirt and they're finding potatoes, or they're digging up the carrots, when they find them, they get so excited. They're like, oh my God, look what I found. And it's like the most amazing Kodak moments that you feel like they just found gold. The other thing is they just love being out there. I'm extremely grateful for everyone's help over the years that has come forward and has done a great thing.


This is Abby. Abby was raped. She told her Aunt Kim about the rape. Aunt Kim thought Abby was lying and looking for attention. Since Aunt Kim did not believe Abby, she decided not to tell anyone else and never received the help she needed. Don't be like Aunt Kim. Believe victims of sexual assault.  When someone tells you they were sexually assaulted, please start by believing.