Good afternoon. Howard Wig, Cold Green, Think Tech, Hawaii. I have a very, very interesting guest today, Trung Lam, who's the CFO of Latour Bakehouse. Now, what is an energy show doing featuring a bakehouse? Well, talk about energy efficiency. But before we get into the program, Trung is a very, very interesting fellow because he's second generation and both of his parents were boat people who had to escape from Vietnam. That's correct. Yep. And had a hard time of it, and they're in America, and this is a success story, a success story. It's been my observation that most of the time immigrants just go above us, head and shoulders us native born because we take America for granted. Immigrants know the alternative to America, and they really appreciate it, and they work like heck, and they make us all look good. So welcome to the program, Trung. Thanks for coming on board here. Thank you, Howard, for having me. So tell us, I'm always interested in immigrant stories. So tell us a bit about your mom and dad and how the bakehouse got started initially. Sure thing. So I want to make one point. You mentioned how you notice a lot of immigrants tend to work harder than a lot of native borns. And I'm native born, I'm second generation, and I see it all the time. And I talk to my dad because at work we'll have our corporate meetings and we'll try to make group decisions together. And he tends to be more on the risk taking side as more to risk adverse like me and I ask him dad, why are you willing to take these risks? And he always says, you know, when I was in Vietnam, so not only is my father in Vietnam, but he was actually homeless for a period of time when he was in Vietnam as a child, he was kicked out and he was on the streets. So he tells me like, no matter how much I lose in America, it still will never be as bad as I had it in Vietnam. Yeah. So definitely they had a really hard difficult life in Vietnam. Yeah, I was in Saigon many, many, many years ago and I would see these street kids begging or trying to shine shoes or something like that. That would be like my dad. Yeah, he was selling lottery tickets. That was his spirit. Wow. So yeah, my parents both came to Vietnam. They came in the late 70s, actually immigrated to California before they came to Hawaii. And my father, you know, he runs a bakery now, but he didn't start that way. When he came to the US, he picked up different jobs here and there. He actually worked for Intel for a period of time. Not as an engineer, just on the plant floor, helping with whatever odds and ends they needed. But he always wanted to have his own business. So he left that and he actually started a tour bus business that drove people from San Jose, which is where they live, to Reno. And that was his own business. He bought a shuttle bus and did that for a while. And during that time of his life, he met someone who owned a sandwich shop and they became good friends. And my father started offering sandwiches on his shuttle bus because there was more competition. So he said, how do I differentiate my business than someone else? I'm going to offer free sandwiches to all my writers. So he started doing that. And after a while, I mean, it was pretty good money. Like we managed to survive. So my father, my mother, and he has two children, two children, I have a younger brother. So we got by. But after a while, it became difficult to make a profit.  His name is Tan Tan Lam. So he told me, Tan, I have the sandwich shop. It's doing pretty well in California. I hear there's a lot of Vietnamese in Hawaii. So why don't you partner with me and we'll go to Hawaii and open a shop. Talk about taking a risk. He didn't know Hawaii from Shmai. No, no.  He flew over in October of 1984. And just to check out Hawaii. And by December of 1984, he already had a shop open. High cost of doing business and all the regulations that we have and everything. Yeah, he just took it. He was lucky, found a good landlord. He found good employees really quickly. And he was able to open in that 30, 34 years now. So he had to develop management skills on the fly then? Exactly. And some would say he still is developing management skills. We all are. We all are. But yeah, he was working 18 hour days, seven days a week. He would be there. He would sleep there. He would do it from baking the bread to cleaning up the shop. That is not uncommon for immigrants. 18 hour days, yeah. So you didn't really know him all that well for a period then? Because he just comes staggering after a while. I was a toddler around the time they opened. So I was a little more than two years old when we moved here. I was born in California. So they didn't have daycare. So they couldn't afford daycare. So I was at the shop. So even though he was working a lot, I was there pretty much every day with him and my mom. Wow. Yeah. Okay. So well, let's pull up the first slide here. Just to give you an introducing energy efficiency in food manufacturing. And we'll definitely get into the details. What motivated or what got you interested in energy efficiency? Well, a little bit of back story. So we started 84 with a sandwich shop. And that was actually called Bali sandwiches. Sure. And that grew from one sandwich shop in Chinatown to at its peak, more than 22 locations statewide. Good Lord. This is just you or your dad and mom. And you know, so we had a lot of employees. My father also has six brothers. And my mom has some siblings as well. So a lot of them came to Hawaii to live and they wanted something to do. So my father said, why don't you open Bali sandwich shops? So you know, like the Bali at Ward is family. And a lot of them, maybe not now, our family, but at some point they were family owned previously. And as we were growing, we realized, you know, we can't really make enough bread in our small shop in Chinatown. And we needed a new facility. So in the early 90s, we 94, my father moved our baking facility to Kalihi on Dillingham. It was an old tire factory. He built his first bakery there, which is about 5,000 square feet. And you know, we found a great home there. We expanded beyond just our Vietnamese sandwiches. We started servicing hotels, restaurants, airlines. And while we were there, we also picked up dough production for Papa John's Hawaii, which is really funny, because I always tell people like, you may not have heard of us, but I almost guarantee you you've had some of our products somewhere. Wow. And then we grew, we kept growing until we burst at the seams at that location. And we went from 5,000 square feet there. And we rented another facility, got up to almost 20,000 square feet total space. But we filled that. And in 2000, that's half an acre, 20,000 square feet. Yeah. But you know, bread takes a lot of space. You have a lot of equipment to make it a lot of employees as well. But in 2010, we moved to our current home, which is on Nimitz Highway, still pretty close by an Evalet, where we have 80,000 square feet dedicated to food production. Yeah. Wow. Let's do the next slide here. Sure. So who were these people? So that's my, you can't tell because we all look the same age, but the one in the middle and the one holding the sandwiches in the head, that's my father. You know, he had me when he was pretty young, so he was early 20. So he's not, we keep trying to ask him to retire. But he just turned 60. He's right around 60 right now. So he's not quite ready yet. Spring chicken. And on the other side of him, so I'm on his right. And on the other side is my younger brother, Brandon, who is the current president of the company. So family business, that's a picture taken in our current location with our Furukake Plus, which is something we sell at Costco. And we're hoping to get nationwide as well. Ah, Vietnamese family manufacturing Furukake. Oh yeah, it's Hawaii, right? Yeah, yeah, yeah, yeah. So, you know, we're a Vietnamese family, a lot of French, European inspired bread. We also do like Asian, Japanese products. We do Tower Rolls, Sweet Rose, pretty much A to Z. At one point, I always joke about this because we're trying to change this. We produce over 700 different items. Too much. Food items? Food items ranging from dinner rolls down to salads, to sandwiches, to tapioca, spring rolls. We are, I would say, a pretty decently sized food manufacturer here in Hawaii. And all this is in 80,000 square feet? 80,000 square feet, exactly. So you can see why 20,000 might not have been enough for what we're doing. That's mind-boggling. Let's go to the next slide. We're doing the family story here. Okay, now. So this gives you a story of how our utility usage was back in 84 when we started with the sandwich shop. Obviously, you can't really compare a sandwich shop to a food manufacturing facility, but it gave you kind of like our growth over the years. 96 is when we actually moved into that facility on Dillingham, the first facility. And we saw a modest increase in utilities. By the time we were looking at moving in 2004, we were getting about 13,000 square feet. $13,000 a month utilities. That's just for electrical, by the way. Oh, that doesn't include the gas. No, that is just electrical. And in 2010, when we moved to a new facility, it skyrocketed $28,000. And my background is actually in engineering. So when it comes to logistics, I do have a master's in business as well. So finance and engineering kind of background combined. I'm looking at these costs. I'm like, we have to do something about these utility costs. So we approached a few different vendors and we looked at different ways to try and save energy. Saving energy is good for the environment, but it's great because it saves us money as well. So the biggest project we did was a PV system. And that was about 300 kilowatt-hour system. Pretty sizable system. That's a good size, yeah. And you've got plenty of roof space. That's for sure. Right, right. So we were in the Onimets Highway, the dole boxing facility back in the day. So it's a big square box. And we had about half the roof to fill with PV. And we did. And we were actually one of the first people to do what's called the fit system, the feed-in tariff system. Yeah, yeah. Right, no, it's gone. And replaced by the NEM system, which we also had. But we were one of the first to do it. So we actually had to do an interconnect study, which HECA required, just to make sure the grid could handle the size of the system we were putting in. And your engineering background. Oh, I didn't do it. But we outsourced that. But I was in charge of the project. So it helped that I had an engineering background to see, you know, what are they requiring? Why are they requiring? Because it costs a significant amount of money to do the study, almost $30,000, just for the study. But at this time, there was some really incredible tax incentives. With the, it wasn't even just a tax credit. You could get a cash back option. And it took the, I think the next slide shows it as well. Yeah, let's do the. There you go. Yeah. Ended up saving 50% cash with federal and state incentives combined. So taking something that would have been, you know, almost a 10-year payback to about five years. And, you know, for our size, it was about a $2 million savings over the lifetime of the system.  I think it was, this was a while ago, but I would say between 10 and 15 years, actually. Yeah. Actually, if you maintain the system well, it could be easily be 20 years. That's what we're hoping. I mean, paid a lot. So we do quarterly maintenance on the system, and it's been performing very well. Oh, good, good, good. Yeah. And the 50%, the last time I looked, the state offered 35%, Fed's offered 30%. Right. 30 plus 35, 65. It was 35 for the state. It was a tax credit. Oh, oh, credit, credit, credit. Sure, sure, sure. And I believe when it was cash, it was a little bit less. At that time, we were not generating enough profit to realize that tax credit in a timely manner. So we chose instead of the tax credit, or the cashback. We were also building a new facility and trying to grow that. So we needed the money. Wow. Well, let's take a look at the next slide here. So, yeah, you started off with your PV system. Right. And incidentally, a little side benefit is your shading. The PV systems are set off the roof surface. So you have that shaded area. That shaded area is having zero heat gain. Which is great. And we did put a cool roof technology on the roof just to reduce the amount of energy used for cooling. But that system, which would have cost us about $2 million, ended up costing us about $1 million to install. And after a while, it was great savings, but we were looking, okay, we had our tastes of energy saving. What else can we do? So we looked at other different technologies to help us. So we had replacing all our lights with LEDs. When you're trying to light 80,000 square feet for production level lighting, it needs to be pretty bright. You have areas that are going to need a significant amount of light, aren't you? Exactly. And obviously not everyone's been to the facility, but it's pretty high ceilings. It's about 20 feet high inside as well. So to get enough light. That's a lot of foot candles to get that down. And the surface you're working on is probably four feet high. Exactly. A lot of tables, mixers. So you need a lot of light hitting the ground. So we spent a significant amount of money on lighting. So replacing all that with LEDs was pretty significant. On the slide, we also looked at a few other options as well. We need to take a break and then we can really get into the meat and potatoes here. Sure. So our big Think Tech Hawaii, back in a minute with Trung Lam, CFO Latour Bakehouse. Hello. My name is Stephanie Mock and I'm one of three hosts of Think Tech Hawaii's Hawaii Food and Farmer series. Our other hosts are Matt Johnson and Pamai Weigert. And we talked to those who are in the fields and behind the scenes of our local food system. We talked to farmers, chefs, restaurateurs and more to learn more about what goes into sustainable agriculture here in Hawaii. We are on a Thursdays at 4 p.m. and we hope we'll see you next time. Hello and welcome to Out of the Comfort Zone. I am your villainous host, Arby Kelly.  Truth number one, this is a real mustache. Truth number two, I want you to watch my show on Tuesdays at 1 p.m. So tune in and let me know which is the truth and which is the lie. I'm Arby Kelly with Out of the Comfort Zone and show up next Tuesday to see my mustache live. Good afternoon again, Howard Weig, Code Green, Think Tech Hawaii, Trung Glam, CFO of Latour Bakehouse and we're just getting in to the Mixed Metaphors Meat and Potatoes of the energy saving measures that you've taken if we could bring that slide back up. Quite thoroughly fascinating. So LED, probably the old lamps were 12 watt fluorescent tubes. Yeah, we had a lot of fluorescent lights so we looked at replacing them with LEDs, putting motion sensors on a lot of them so if someone, you know, people weren't in the room the lights would turn themselves off. And also D-lamping which is like looking at with these LEDs which are brighter and using less energy. Do we need as many lamps? So they were also looking at window film and the list is on there and the reason why those are the things we were looking at is they were actually incentives from Hawaii Energy to implement them. You were very, very wise to hook up with Hawaii Energy. The State Energy Office works really, really closely with them. Yeah, we have a wonderful relationship with them. We love working with them. And you know, as much as we love saving energy for the environment, it has to make sense financially as well. Absolutely, yeah. So on the screen, you can see the different incentives we received from using different technologies. Lighting and cool roof were the two biggest ones and that was around the same time we did the PV system. The other three, the HVAC, the window film and the EC motors were done a little bit later over the years. And what you will see on the next side is the PV system was the most significant source of energy savings. And we saw some saving with these but not as much.  And then with the annual savings, there was a really quick payback on a lot of... That is... This is specifically for the EC motors, which is the motors you use in your walk-in refrigerators, which are constantly running because with people coming in and out, we're storing things. Yeah, you're constantly opening that door. And that's a big cost for a lot of businesses here in Hawaii that do food manufacturing or food distribution because we bring in a lot of frozen or refrigerated ingredients. Oh, you have to keep it frozen. Certain items. So, yeah. Oh, that's really an energy consumer. Yeah. So that instance was just the EC motors. That was just an example of one of the projects that we did with the end of payback period. And then you have window film there. That's where you have... It's probably an older building, didn't you say? It is an older building. When we moved in, we did replace all the external windows with new ones. The putting window film helped with the heat coming in as well. Yeah, because with a normal window, when the sun is directly striking it, 87% of the heat that's striking the exterior is getting into the interior. You put on a good film and 87% goes down to 25%. Great, yeah. Our windows are dual pane, but we thought we'd put the film on just to help them in that much more. Oh, yeah. You're super, super, super efficient. Yeah. Trying to be. Yeah. Oh, that's great. Yeah. And so, yeah. So you're down to total consumption, if I remember, electrical of about 28,000 a month? That was when we started and we were growing. But we wanted to see how low we can get that. And on the next slide, it actually shows our energy usage. And from when that little house is actually when we put the PV on. So from 2011 to 2012, we saw a significant drop continuing to 2013. And between 2013 and 2014, when we did the AC motors and then the LED light upgrades. But what's really funny is if you look at our energy usage, you went up. And you would think, why would it go up if you're adding more things to reduce energies? And on the next slide, it'll show you, explain why. The little snow symbols are actually when we had to install more air conditioning, because we were growing as a business. Between moving to this new facility in 2010 to now, we've actually doubled in revenue, which is we went from about 10 million to about 20 million revenue over that period of time. So we saw a significant electrical usage grow just because business was growing. And when businesses are growing, there's more bodies. We have about 150 employees now. And we have to keep all those spaces nice and cool. So we had to install more air conditioning, which drove usage up, which is great. Because if we didn't have the PV system, our utility bills would be through the roof. And the PV system has helped quite a bit. Wow. And how many KW was the PV system? Yeah, it's 300. It's split into two systems. The feed-in tariff system was limited to about 200 the size. Yeah. So we had to have a secondary NEM system, about 100 kilowatts system. Could we go back to that last slide there? So the, so what is the line there? So on the left, it's two y-axis. On the left is actually the usage. Okay. Okay. Percentage of revenue, right? Which is the, yeah. And on the right is the percentage of revenue. So we use more electricity, but percentage of revenue was kept low because we were growing at the same time. So it's kind of like this, you want to save energy because it's good for environment, but it has to make financial sense. Absolutely. Absolutely. Yeah. As long as your business is growing, it makes sense to invest in these technologies because as a percentage of revenue, which is how most businesses look at their utility costs, if you can keep that down, of course you can, you should invest in technologies to help your business run more efficiently. And I might point out that all of the technologies that you've installed have a, in my opinion, a minimum life of 15 years. Maybe those motors will have a slightly lower life, but once they're in LEDs, last virtually forever. I love LEDs. They have about 60,000, easily 60,000 hours on them. Which is good because we run 24-7. We never shut down. So the lights are used quite a bit. So you have three shifts of people coming in. It's actually more like two and a half. There's like a short shift where there's like a skeleton crew, but we don't shut down because our customers don't. Impressive. Thank you. Wow. Did we need to go through the last slide there? I think there's one or two more. Oh yeah. Okay. So this is just a simple pros and cons list of what we learned doing these different projects. Pros, the smaller energy efficiency projects, they have a lower upfront cost, which is great. But because they're kind of smaller, it's hard to quantify how much you're saving as your business is growing because your usage fluctuates so drastically. You're a moving target, but on the other hand, you know that you're saving something because you're putting in more efficient equipment and you're assuming that it's doing what it's supposed to do. And a lot of these, you can test. You can test using equipment to see how much money you have to save. Yeah, you can submit her. Exactly. Especially in a growing business where you have a lot of cash flow coming in and you'd rather save on some taxes, spending on capital expenditures to, in the long run, help your business really helps a lot. There's a lot of benefit. Yeah. So cap X is what? Capital expense. Equipment, machinery, big, big expenses that usually you don't expense, but you amortize over a period of time in five years. There's also other benefits in addition to how good return investment, it makes you feel good knowing you're saving energy. It gets you on think tech, sharing your story and it helps with employees. Employees, of course, love to save energy. They like to help the environment as well. And when you see the company focusing on that, it makes them feel good about where they work. And because, say, just in the instance of lighting, that's new lighting, good lighting. Oh yeah, it's nice and bright. I love it. Yeah, they're with fluorescence. Some people get headaches under fluorescent because there's many, many, many little fluctuations in the light, but LEDs, that's absolutely not the case. And in terms of maintenance, again, the LEDs, 60,000 hours, even at 24 hours, that's easily six years. And they don't put a whole lot of heat. A little bit of heat, but not very, very, very little.  And ovens. Yeah, yeah, yeah. That's incredible. Do we have one less light, I believe? Oh, just to thank you. Yeah, I think that was it. So we're looking forward to new ways on saving energy. Right now, we are trying to review battery storage units, especially with the hurricanes that came through. Most businesses use diesel generators or gas, propane gas generators. But for our size, we would need a sizable generator to cover what we need. And some people probably have been to our building. There's not a lot of parking outside, so we don't want to lose any of that for a large generator. So the battery is much more compact. We can store it above ground. We don't have to exhaust the fumes the way we would if we use a regular generator. So we're exploring the feasibility. You don't need a fuel tank. That, too. Yeah. Well, let me just give you some good news and the audience some good news. Just at the last Hawaii Building Code Council meeting a month ago, we adopted the NEC National Electrical Code 2017 version. And that has a long section on battery storage batteries. And it lists all the safety procedures that you need to go through. And so you comply with that. And you've probably realized that sometimes getting building permits for things takes just a while. Yes. As long as the engineer who signs off on that project says, I am in these, this design is in compliance. 2017 National Electrical Code, the plan checkers will give it just a very cursory review. Yep, yep, yep, yep, yep, yep. And boom, you've got it. Excellent. Yeah.  And bad news lasts a long time. So now you've got a safe, efficient system. And Hawaii Energy, no, I don't think they can give a rebate on that because it doesn't save energy, it just shifts the load. Yeah, cross your fingers that the state creates some incentive for businesses to adopt that technology in the future. Yeah, that's our future. Well, on that cheery note, we do need to close for the day. Thank you so much, Tronglam. This has been an inspirational story. If every business in the state did this, boom, we would realize our energy goals very, very, very quickly. Thank you, Howard. It's a lot of fun. So that does it for us. Howard Wigg, Code Green, Sink Tech, Hawaii. See you next time.


And that really is what it's all about. Live from the Fairmont Hotel in San Jose, California, it's The Cube at Big Data SV 2015. Hey, welcome back to day three of Big Data SV. Live here on The Cube, we're in San Jose. I'm Jeff Kelly with Wikibon. I'm joined by my co-host Jeff Frick. Welcome, Jeff. Thanks, Jeff. Another big day here, third day going strong in San Jose. We've had an exciting first two days. I think we probably had 20 plus interviews, 20 plus guests ranging from some of the vendor executives we've had on practitioners from Halliburton from Simply Hired. We had our great panel discussion with VCs on Wednesday night as well as I presented some Wikibon research and of course our party. So it's been a great couple of days and we're going strong here in day three, Jeff. What are your impressions over the first couple of days? It's amazing how far this market has moved. I think one of the great lines that Bill Schmarls had from EMC yesterday, right, is no one's asking about Hadoop anymore is it a technology that we should incorporate? Yes, it works, people are using it and really it feels like a really rapid adoption into the production side. And we've had a number of people really talking about real simple specific use cases in hospitals and grocery stores and oil and gas. So it's really interesting to see the evolution of this show and kind of the evolution of the conversation from the technology conversation to really the business case and the use case application. I was at one of the events last night. There was a number of events going on, obviously it's a lot of scene and I think the next great conversation is going to be into the ethics. We were at a show the other day and someone brought up, if you run an algorithm on a data set, are you responsible ethically for the outcome of that data? And of course the example everyone uses over and over and over again is the target example. Just because you have that data, should you use it, are you responsible for the algorithm if you're the one that actually executed it for the output? But I think what gets really interesting with Hadoop is the whole value is that you don't necessarily know what the algorithm's going to be today or tomorrow but you can grab all the data and hold it. So what kind of responsibility will that entail? So I think that's interesting, the Internet of Things which was the answer to the question last night really in terms of self-driving cars and we're hearing about the Apple car and the Google cars are driving all over the place. Then that really ramps up the security and the access of somebody takes over your car while you're rolling down the road. So I think that's great. And I think your conversation on the money, so I think that was a great conversation. Uber announced another billion dollars in funding yesterday. Just massive amounts of capital coming into this place. What are they using it for? And really how are they going to put that money to work? Yeah, I agree with a lot of what you just said. I think some of the themes I'm seeing here, definitely, as you said, the question is not about what is to do, how does it work kind of thing? It's moving on, how do we use it and how do we harden it for the enterprise? Addressing issues like governance, making it easier to build applications on top of it. That's kind of what the whole announcement around the open data platform, which was kind of the big buzz this week, the biggest probably news announcement. The open data platform, this new industry consortium that's focused on basically hardening the Hadoop core and allowing enterprise vendors to build applications on top of that standard core so you can move applications from one vendor to a next. And really the goal, of course, is to spur adoption in the enterprise where the enterprise soothes some of their fears that we could potentially get locked into one vendor or another or soothes their fears that there's going to be a lot of heavy lifting on a manual work they're going to have to do to build applications. It's going to open up hopefully more application development from others in the vendor community, whether it's the big guys, the startups or the enterprises themselves. So that's one of the themes we've been following, I think was a pretty important announcement. In fact, we'll have Pivotals coming on this morning. Sonny Madra is going to come on, he's their director of data products. We'll talk about the ODP and we'll talk about some other announcements they've made. Of course, on the other side of that equation, you've got the big, I guess, industry player that was not part of that consortium was Cloudera. So we're going to have on Tom Riley, who's the CEO Cloudera today. We'll get his point of view on it. Of course, on the ODP side, it was really led by Pivotal as well as Hortonworks, IBM and some others. So we'll work through that today. We'll try to suss out some of that controversy, if you will. Some of the other things we talked about, you mentioned data science applications. We had two great data scientists on yesterday. And they kind of echoed what you said, that they're starting to see it's less about the container, the storage, the processing, and more to how do we use all this data we can now process and to do, how do we actually use that to build some applications that drive some business value and beyond some of the more commercial uses. I mean, Bill Schmarzo mentioned some things around hospital usage and path to surgery was one of the examples he gave and he's a big data analytics to hopefully intervene quicker if you can predict that someone's likely to have a negative outcome. What can we do to stop that? Analytics underpins that. That's obviously a big social value as well as monetary value to a hospital. But then, of course, we had on Chris Poolin from Patterns and Predictions to wrap up the show yesterday that he was talking about. He led the Durkheim project, just really using social media data to help predict the likelihood of things like suicide risk and other mental health challenges among returning veterans. So it's not just about putting ads in front of people. Some societal value you can really drive with some of these big data technology. So great day yesterday. We're looking forward to another good day today.  Yeah, it was great. And Bill Schmarzo's interview, if you haven't watched it, be sure to watch it. It's up on the website, siliconangle.tv. But I think it's really important because people too often get wrapped up into the use case of you walk by the Starbucks and it gives you an offer for your favorite latte. And the thing I thought was also interesting about Bill is he's talking about doing prescriptive action now. I mean, they're trying to get to prescriptive stuff now. This is not futures. And the use case he gives about potentials for infections that happen in hospitals, it's about saving lives. And I think the other thing that he brought up, which is always a fun topic of debate, is real time, right? What is real time? Or how do you define real time? And still I think my favorite description of real time is in time to do something about it. And that's very different based on the use case. It's different based on the data that you need to make that use case. And again, I think Bill reinforced that and Bill is out in the field all the time. Every week, like Tuesday to Thursday, he travels like an eccentric guy. Not quite as much as Ray Wang, hi Ray, but he travels quite a bit. I also just want to give a shout out to the sponsors. We have a great community here. We had a terrific party the other night. We've had a lot of great guests on over the course of the couple of days and we'll have more on today. But this would not be possible without sponsorship. We operate on a sponsorship model. We got a bunch of guys in here. If you could see behind the camera, we got gear, we got crew. We travel, we want to go out to the events and get you to signal. So we couldn't do that without our sponsors. So EMC, thank you very much, our headline sponsor for this event. We've got a number of other great sponsors including IBM, Pentaho, H2O, InfoObjects, Platfora, Syncsort, great longtime sponsor, Trasada, Obimeta, always a fantastic guest. Informatica is on. Wendisco, Teradata, and new sponsors, BMC and Pivotal, who are new to our big data shows, which is terrific to happy to have them on. And of course, Hortonworks is a longtime sponsor. I'm missing about Platfora and Tahoe. It's a great list. Again, we're really thankful and thank you to our sponsors for enabling us to get the gear, to get the crew, to get the guys in to come out to these shows and really give you some insight. Let you hear directly first person from the tech athletes, from the people that create the technology, the people that are building the companies to deliver the technology, and most importantly really is the practitioners that are leveraging this technology to do good. And as Jeff said, in New York, really the theme of that big data conversation is the practitioners are going to be the ones that are going to get the tremendous value. And we keep hearing over and over about 10x, 100x improvements and processes. It's a great thing. Yeah, absolutely. You mentioned earlier, where's all this money going? Because there's been quite a bit of money raised from the vendor side in this market. We talked a little bit about that in my presentation on Wednesday night. And I think the point I was trying to make there is that this is a difficult market. The open source market is interesting because there's a lot of innovation that happens very quickly. But actually packaging that into consumable products for the enterprise can take some time. It can actually be harder when you've got so much innovation happening so quickly. So that's one reason I think you've seen a lot of money raised. It's going to take some time to build the business. And of course just a startup is difficult to build out those channels into the enterprise. I mean that takes time. Of course the other thing is marketing. We've seen a lot of, the big whales are into this. You mentioned some of our sponsors are some of those big companies, EMC and IBM and others. So you see some of the startups raising a lot of money because they've got to battle those big whales in terms of marketing budgets and those marketing machines are cranking away. So the point I guess is that there's a lot of activity happening in this market. You've got big companies, you've got startups. We think we're going to see some consolidation, some acquisitions happening. We've already seen that kind of kicking off. So yeah, it's a fun market to cover as an analyst and as here on theCUBE. And hopefully it's fun for you guys at home to watch. Yeah, and I think we had another huge wave coming. I mean it's just starting to get here and that's the Internet of Things, which is a whole other set of data, right? When you think about the Internet of Things and you think about all the applications you could potentially build, it kind of, it kind of dovetails nicely with what we were talking about big data applications. Generally, Internet of Things is an area where you're going to build applications around that. And I think that's where you're going to see a lot of the value happen. So I would keep an eye on companies that are focused on that space. And again, it relates to what we saw with the open data platform. And that is all those companies that are part of that organization want to, hey, let's just kind of standardize this Hadoop course so we can start building these applications. GE is a member of the organization. So they're obviously very heavy into the industrial internet. We've done some research with them over the last couple of years here at Wikibon. We know some of the potential value that can be delivered from the Internet of Things is just huge. And that's about building applications that actually do something with all that data coming off machines from sensors, et cetera. So yeah, I think Internet of Things, applications, that's where you're going to see kind of the next wave, the next phase of big data. And that's kind of what we're moving into, I think. So what's your take, Jeff? You've done a lot of work on it in terms of kind of the rate of growth of how this whole market is developing based on some of your early projections. I mean, we do this big data show twice a year. I mean, it's one of these things you don't want to wait once a year. Things are moving so, so quickly. How is it kind of tracking to your projections? Are you making some changes? Is there some big surprises on the upside or the downside? What's kind of your take relative to what you thought was happening? And then knowing what you know today, what's it going to look like going forward? I think, if there's anything that's surprising, I think it's actually proving a little bit even more challenging than I think we thought maybe to build some of these new businesses in the Hadoop ecosystem. As I mentioned, the innovation's there. There's no question. Hadoop and the SQL are kind of the, some of the foundational technologies in this big data movement and you're seeing a ton of innovation in that space. But because it's open source, because the innovation's happening so quickly and there's so much competition, it's interesting to see the different players and how they're competing against one another. And they're competing on price in some cases. I mean, with open source, that changes the whole revenue model and how you're going to monetize this stuff. So that's interesting. And I think that might be slowing some of the growth. So we saw Hortonworks come out with their numbers when they went public back in December. Some people were a little surprised that their numbers were not higher in terms of revenue. But I think it just speaks to the challenges of building a business in an open source ecosystem and the idea that you need to be patient when I mentioned earlier, which is why you're seeing so much money raised. Because it's going to take time. Because this is not a standard, the standard way, sorry, enterprise software is typically sold or consumed. I mean, open source is quickly becoming the new reality and it's not just a nice to have, it's a prerequisite increasingly for a lot of enterprises. But the way those enterprises buy software is in the old proprietary world. That's just kind of how they operate. So that's changing over time. And I think, but that's one of the reasons it's taken a little bit longer to ramp up in terms of the size of that slice of the market. But in terms of the overall market, I mean, it's growing at a pretty hefty clip. We had the, we size the market this year, well, at the end of 2014 for the calendar year, 2014, over $25 billion. And we see that growing exponentially over the next several years. And in fact, keep an eye on, we'll have our latest big data market forecast coming out shortly, in just a few weeks actually on Wikibon. So check that out. But yeah, the market's just growing and growing. And one of the things that's going to be interesting as we do some of our research at Wikibon is that we'll be introducing some different forecasts because as the market matures, now you're seeing different segments emerge. And we have to, it changes the way you kind of have to look at the market when applications start coming in. And when practitioners actually start driving more, more value, more revenue, which is who we think are going to be the big winners, you know, we will kind of adjust the, some of the forecasts to take that into account too. Right. The other really interesting play that that is new to enterprise software, and it came up, I think maybe Frank brought it up on the VC panel, Frank from Ignition, is that now with open source, the actual consumers of the technology can run the innovation and can run the development and can roll out new things. And that's very new. And the other kind of interesting dynamic we're seeing is pretty attritionally, startups run the innovation, big wheels wait till they get big enough and there's enough customer adoption and then they absorb them to bring that to market because we all know nobody ever got fired for buying IBM. You know, that's still a factor in enterprise software. But now you've got these partnerships. We've had a number of people on theCUBE this week really in kind of a partnership mode. You've got the open source organization around a project and then you have the consortia, which is kind of the old way that things got done. So what's kind of your take on how those three kind of ways of working together are changing really the dynamics in the enterprise software space? It's definitely a different approach. You know, as I said earlier, open source is now not really a nice to have. It's a prerequisite. It's the way things are developed in the enterprise software business these days. But you're right, in terms of how we see this evolving, will there be acquisitions? It is challenging for startups to, where they're great at innovation, there's no question about that, or they're not always so great as it's rolling that out to a larger enterprise audience. So that's one of the challenges they have. So if you walk the floor for Duke World, there's lots of vendors, there's dozens and dozens of startups out there. And some of those will have some nice exits. One or two, I think, might even be around in five or 10 years as a standalone, independent company. But I think you're increasingly gonna see the big guys play a role where you're gonna see some of that acquisition because they have the experience in terms of rolling this out to the enterprise and they have the channels and they have the sales and distribution, et cetera.   But the challenge there is, a lot of time the innovation stops at that point. The wild card in this market, which is why I'm really excited, is that you've got the open source component. So even as you do see some acquisitions, I don't think that's going to impact the innovation much at all because you've got the open source component, which is not just, as you mentioned, vendors, but practitioners are actually developing a lot of the technology themselves. So it's the big companies, the big web companies, of course, Facebook and Google and increasingly it's other, there's another wave of those kind of companies like Netflix, for example, who's open sourcing some of the tools that they're building. So the innovation, I think, is going to continue because those kind of companies, a lot of those companies don't buy from the big enterprise practitioners, they want enterprise vendors, they want to build it themselves because they want to move fast and it's so core to their business, that it's worth them investing in developing those tools themselves. But the interesting thing, the way they monetize those tools is not the tools themselves, it's how they use them. So they don't mind open sourcing them. It's a real right of head. Our advantage is how we actually use this. We're not giving that away, but we'll open source the tools and then as that cycle continues, startups will emerge to commercialize those tools and the innovation, I think, will continue in this market, which is why it's exciting and why I think it's very different from some of the past markets we've seen. Yeah, and the other thing I think you could see and Jane brought it up from WANDISCO is in the open source world, these individual contributors are rock stars in their own world. They're passionate about what they do, they're passionate about the software they develop, the problems they solve, and you get in these worlds and these guys are really excited about developing the software to do good, developing the software to solve problems. Not really commercial. Motivation for the individual contributors on a lot of these open source projects. So the way that the big companies have to figure out how to live within that world, support those guys' mission, give them the feedback that they need, and then still figure out how they are gonna wrap their additional product services extensions on the open source, I think it's pretty fun to watch and we're pretty excited. So we've got a great day today. Again, we've got Suny Madra from Pivotal coming up. Next, Moni Chabra from Cloudwik is coming on. John Cardente from EMC, it's like to have him on. He's been on a number of times. Kiotta Tamira from Treasure Data, which is an interesting company. They're doing some good things. Brett from Wendisco, Ryan Peterson from EMC, and again, Tom Riley from Cloudera. Excited to have him on. I think it'll be his first time on theCUBE. We've had Mike Olson on lots of times in Armour, but this will be the first time for Tom. Michelle Chambers from RapidMiner and she's doing a lot of stuff about women in tech, which of course is a passion of ours and women of big data. Excited to get her on for an update. And I think we'll get Clint Sharp on as well from Splunk. So we've got another full day, Jeff. I don't know, you ready for the full day? I'm ready, let's do it, three days in a row. All right, keep it going. All right, great. So that's Jeff Kelly. I'm Jeff Frick, we're here at Big Data SV that's running concurrent to Stratocomp in San Jose, California. Thanks for watching. We'll be back with our next guest after this very short break.


Hello, you can hear me? Okay, so my voice is doing strange stuff. So you'll be Having a hearing test and now I'm giving you on a reading test. Can anybody read that on the screen? Oh It's better still too small. Hopefully this will work better So there was yesterday a tutorial about a Selenix mine is a presentation Going through the basic stuff Normally if you read the early scriptures, everybody would have told you life is too short to learn as a Linux I'm going to try to explain you that in 35 minutes. I think I have so Hopefully you Still be alive in 30 minutes Yeah, so I'm Tosham Bhavani. I'm from Antwerp Belgium little country in Europe Self-employed I am involved in enterprise Linux, which basically translates to sent us red hats I do some of the proprietary BSD stuff a x I'm I do a little bit of free BSD and open BSD That's how I got involved in as a Linux I like virtualization. I Run config management camp if anybody is interested in that I like Ansible form and puppet and Yeah, I'm sometimes on social media. Don't find me that too often So an introduction then what is as a Linux and some ways how to use it and how to Live with it on your system in in in enforcing mode So who of you actually already uses as a Linux and I'm talking in enforcing moda Nobody actually well two hands I see from here, okay Anybody in permissive mode? Okay. Also two people.  That isn't true anymore. If you were running versions So sent us for or even sent us five. Maybe that might have been through in sent us for definitely you really needed to know what you were doing in Sent us five that improved. So when I say sent us five I'm talking about sent those red hat scientific all the other variants that are based on that distribution If you are a fancy geek running gen 2 then you always have the latest one. So that doesn't apply to you Only in less 12. I think as a Linux has been enabled Previous versions had up armor Which today Ubuntu uses it doesn't do much.  Yes, I know that But it's very easy to work with nowadays and then there are vendors who will tell you to actually disable that so The lovely people from the oh company. They love to tell you please disable this because I was we won't support you Unfortunately, if you need to work with them, then yes, you must do that However, if you run your systems with as a Linux you get Chuck Norris in there So you'll be happy to know that he will kill all the bad guys for you Now as a Linux was developed by the NSA and now most people will be thinking there are some backdoor in there But the NSA actually built it and open source to directly now multiple people From multiple companies have looked at these codes and have actually checked the code and Verified that there are no backdoors in there It's a kernel module. So it has also gone through all the scrutiny of being accepted in the kernel itself So if you really have a lot of time on your hands, you can manually read all the code and double check that There are really no backdoors in there But presuming you have other things to do you can just accept what other people have told you So what is as a Linux? So first we need to understand what? traditional Unix Permissions are in Unix everything is a file. So we're going to secure a file sorry So we're going to secure a file And the file can be secured by a 3x3 matrix, which is basically your user your group and the others You can give them read write or execute permissions And that's how you get these binary statements Which you use ch mod 777 whereby everybody could do everything with it Which is not the most convenient thing to do, but it's the most easiest example to give Now as a Linux is security enhanced Linux. It's a mandatory access control So it basically Denies everything unless you allow it to do something now it has policies which I Loaded into the current. Well, there's a kernel module which loads policies and these policies basically tell what is allowed by which Type of which Demon which file can be used because everything will get a label. So a specific label will be allowed to do certain things with other labels Now you need to have a kernel that is compiled with as a Linux So if you compile your own kernel you go to security features and there there's as a Linux and then you can enable it You compile your kernel Again, if you're running most of the enterprise Linux's they have that already enabled in there and Everything is a label or a context and that is Basically defined in three types The type enforcement the role-based Control and the multi-level. I'm not going to talk that much about multi-level because it's a higher level of of Control which allows you to do multiple things at the same time But the type enforcement is the most commonly used one The role-based in force one is basically when you log in with root you Get into the unconfined mode which allows you to basically do anything on your machine Which could be one of the reasons why you execute something as root and it would work And when you execute it as a different user it wouldn't work So access control is based on the type enforcement Which basically tells you that a specific context can do certain things to another context So the object let's say an Apache demon can read all Files with the label of HTTP underscore Rw access T you'll see that most of these things end on a T stating that they are basically a type enforcement The role-based will be that you as a user root would be unconfined Or you could actually have that the root would be confined Which means that you as a root user would not be able to do everything on your machine. This is Sometimes relevant for people who work in larger corporations where you're not allowed to see the data But you still need to manage hold the machine then you could actually put the data in a different type Where by you as a root user would not be able to access the data But still be able to do all your operations on the machine The multi-level is mostly on being able to have Multiple objects talk to multiple subjects It's on it's mostly used if you use effort Which is basically containerizing your VMS in specific groups And then you can tell that these VMs can only talk to each other They can see underlying file systems or they can connect to specific network cards and so on So if you want to look at it visually Normally if a process asks For access it will talk to the kernel and the kernel will basically tell you yes You get access to that file or no you don't get access to that file In the as a Linux version you have the kernel which loads the as a Linux module The module will actually load the policy database and that policy database will then tell you that okay You as Apache can only see anything with the Apache labels and So you get restricted to your one confined Center and So if you get an attack you are less likely to have your complete system compromised And only that section of your system would be compromised So these are the features The most important is that you actually have a base policy But you can actually quite easily generate policies yourself These policies are generated based on the audit log. So you need to have your audit logs running Today there are tools like audit to allow and audit to why which will actually explain you what is happening So you don't need to understand all the cryptical mess messages if you are really Daring you can actually change base policies Just remember that if you are running a distribution and you change anything in the base policy The next time you do an update of the base policy all your changes will be wiped out It controls file systems direct trees Sockets ports network interfaces demons. So it basically controls everything that runs on your machine So if you're running a simple web server, it will not allow you to run your Web files just anywhere. You will need to tell as a Linux that oh they are located there Of course, the base policy has the default Locations in there, but if you need to run it off an NFS, then you will need to tell the database basically that please allow me To run my website from an NFS server So in a way it disallows misbehavior It's a good annoyance if you have junior in your company You want to know them because it will actually not tell anything in the other logs of the application itself It will just tell you Apache wasn't able to start up. Okay. That doesn't tell you much And It can even restrict to you to use it as I explained so if you look About five years ago. It was only the kernel which was enabled you had Then an initiative from postgres to have se postgres which basically means that you can even confine databases and Today even tables and columns too specific as a Linux users Be it users of the system or users on the database level Apache has a mod which you can install which you can also do that PHP today also has an an extension for that. So while we don't have the full stack available yet Most of the standardized applications are available If you're running your own application, you can easily write A policy by just running it in permissive mode in development Running audit to allow and it will actually generate a basic policy You will have to filter out still some stuff. I'm not saying that you don't need to do any effort but it won't Tell you everything. Well, you don't need to write everything from scratch anymore So where do we find as a Linux it was merged into mainline kernel in 2.6.0 Somewhere around 2002. So it's been around for the last 15 years. So it's quite stable by now Yeah, so red hat sent us scientific from version 4 Novel Gen 2 Debian also has Some Versions of it if you have an Android phone and it's a newer version. You also have as a Linux running on your phone Ubuntu still chooses to have app armor as a default But you can if you really want to run as a Linux also there. So again Why would we want to use it? It confines processes services uses in compartments so allowing you to only have Well, if you have a problem, it will only be in that particular compartment You can use that for virtual machines. There's an extension called effort if you're running Version 7 that's enabled by default If you want to do more advanced stuff, then you'll have to go to load level If you run kiosks for a living then you can use ex-guest which also runs as a Linux Which basically allows the users to do anything Within his confined kiosk console That you set up If you have a German built car, then you're most likely also have as a Linux running in your car USB redirects So if I plug in a USB device here, and I want it to be used on a virtual machine Somewhere around the world Nine out of ten chances. It's also running some version of as a Linux to make sure that that specific USB is being redirected to that one specific machine only it does that by subdividing categories within the labels so that's the Theoretical part are there any questions already? So, yeah I asked already how many people used enforcing permissive and disabled if you're running it in enforcing then it's on Which means that your system is secured anything that Would not be allowed to get denied and goes into your audit log If you are running in permissive mode, it will actually allow those things, but it will still Sorry It will still allow you to see the denied messages so that you can actually generate a policy Once you have generated the policy you can then load it into the system keep the system still in permissive mode and see if any Other error messages are being created or denied messages And then you can filter out from there what is being done Of course if you run it in disabled mode then it's off So it's basically not loading the kernel module and you have no advantage of the system Now given that you just get a machine like that You don't know what? The the status of as a Linux is you can run a command called as a status and will actually tell you What the machine is running Let's see So it will tell you for instance enabled it will tell you also which Policy version it's running and if MLS is enabled or not So the policy version is the base policy that gets loaded into the machine That comes mostly from your distribution If it would be in permissive mode, it would just tell you the same thing but with permissive if it's disabled It just gives you one line with disabled Now most of the commands that we know already today if you add capital Z you actually get the as a Linux labels or contacts So LS minus capital Z will actually give you the context of all the files Nets that minus that will give you all the context of the parts and PS will give you all the context of the Demons If I knew how to Sorry, that's the largest I can go It doesn't go any larger So is this better now Yeah, so you see here the files. These are just files in my home directory But you see there that you have the traditional Unix permissions, you then have the owners and then you have the context of As a Linux so in this case admin underscore home underscore T This part is the most important because that's the type Which basically admin home is your root Directory, sorry your root user directory If I would do the same If I would do the same on var WWW which is already defined in the base policy as the default web Directory you see that you get the HTTP sys content T type So that means that any demon that is flagged with HTTP D Type can actually read these files. So if you're running Apache But if you're running engine X, that's the same thing So again, if you're running most of the common web servers, they already known and once you install them It will actually take the demon with the correct Type enforcement rules already by default if you've written your own web server Then you'll have to actually write a policy for that. So mostly if you read up in the documentations You'll find objects objects, which basically can be labeled Files normally get labeled By in the file system, so it's supported in most file system not all Again, if you're using fancy file systems that doesn't work most of the common UNIX file systems are supported and can handle the extended attributes Now the labels can be set manually Yeah, so labels can be set manually using a command called CHCOM which basically changed the context of a file So if you wanted to have In the folder user server WW your website, then this would be the command the first one Now the capital R is to do it recursively the T stands for the type you want to do it And of course, this is very nice because it will start working Now the next time you reboot your machine. You'll see that nothing works again because every time the restore demon or the Machine gets rebooted it will actually set the files back to the default labels Now to prevent that you can actually inject that into the database itself and for that you use as a manage So in that case you would use as a manage. We want to add a specific file context to the Specific type and then you need to use some regular expression to actually get that into the database Which means that all files? folders Any other things under user SRV WWW would actually be labeled under that specific context So the next time you reboot the next time restore com runs in the background Your files will still be have the correct label and your web server would still be able to read them Now if you have for instance SCP files from your laptop to your home directory and you copy them from your home directory to your Web server, you'll see that actually nothing works because the minute you SCP to the Host it will get a label at that point and given that you SCP into your home directory You'll actually get a label with home In it now when you copy the files it doesn't it copies the label that it originally had it doesn't copy what the destination would be Now if you want to restore all of those back to the defaults, then you can use restore com Again the capital R is to do it recursively and it would do it for all these files and set it back to the default Now let's say you have like most people here your machine in disable mode Then you would actually if you enable as a Linux you would get into trouble in the sense that None of your files would be labeled correctly now to do that you need to Relabel your home directory and then you need to Put a file in the root Called dot auto relabel and then reboot your machine. What will happen at that moment is the machine will reboot It will load up in run level one and will actually start relabeling hold your file system So if you have a few petabytes of data, this can take a long time while it's relabeling your machine is offline so It's advisable to keep as a Linux in permissive mode It makes life easier afterwards if you have it in disabled during your installation then your installer Will actually not label the files correctly because it doesn't see the use of doing that You can use also fixed files, which will actually Tell you what specs were for this specific location and how they were being applied there now In the beginning policies were made and you had to follow the policies now many people actually found this quite restrictive, so there are now booleans that you can actually Flip which will allow you to do certain things which a normal system does not always require So for instance a web server will automatically be allowed to connect on port 80 because Without part 80 you wouldn't be able to serve your website now part 81 81 is not a very common part But if you want to use this then you need to add this to the specific context that you need So to get a list of the default ones It's as a manage part minus L, which will give you the whole list If you want to add that if you want to add a specific one you do minus a Then minus T for the type and minus P for the protocol that it's going to use and so even if you want to run SSH on a different part than 22 you need to actually Tell as a Linux that I'm going to run it on port 5022 and Add that to the database because I visit won't allow you to do that So the files Example I gave already, but again here if you're not sure what file Context is being used or what is there by default you can always use minus L And it will actually give you the list of all the file context and the directories that are being tagged automatically for that specific context now The Booleans you can get get the essay bulls which will give you all the Booleans That are available and then you can grab on Samba so for instance if you run a Samba server and you want to Allow home directories to be shared by default. This isn't allowed So you would actually have to set the Boolean to on By default, it's off the minus capital P here sets it persistent That means that even the next time the base policy will get uploaded It will keep your value and not the default value now the main thing about as a Linux is That if you have a web server like Apache and genetics Samba server And you try to start it up or even your SSH server you started it up on a different port than 22 It will just tell you failed It doesn't tell you much more than that, which isn't very descriptive However, if you look in the audit log, it will actually tell you that a certain process called SSHD Try to attach to a specific port 5022 and it got denied The same for a web server if it tries to connect to the port 8181 and you didn't enable it it will tell you denied now you can basically Grab those denied and pipe them to audit to why and it will give you a nice explanation from what you did What went wrong how it went wrong? You could also use audit to allow which will generate a policy for you However, if the booleans already exist it will actually warn you that please do not in compile this Policy but use the booleans that already exist for that If you want to get a better description on the booleans because if you use get essay bool minus a it will just give you the names It won't give you a description So the minus L here gives you a small description on what the boolean is supposed to do So once you have such a policy You can actually Compile that into a binary form and load it into the database kernel and at that point it becomes enforcing into your kernel Depending on time. I'll see if I can show some So your subject your demon Or your process asks the database whether it can actually Sorry ask the kernel where it can actually get access to a specific Object and the database will answer to the Policy whether it can or cannot do that And here you see then that the denied message goes into your audit logs if it gets denied So yeah, you can also use as a search if you want to search on booleans on types So if you're quite new they have a lot of tools to figure out stuff And it will actually explain you in more human readable language what these booleans what these switches do What specific file contexts are being used where and how? So this is the Shortest way to generate a policy You basically look at your audit log you grab on in this case. It was a Demon called Zarafa Well, no, sorry. I forgot to change that it's Galera. So the default Galera setup Requires you to use our sync, which is allowed. I use perkona extra backup. So you need to allow certain things on On as a Linux level so it should read actually grip Galera From the audit log you pipe it through to audit to allow and you create give it a module name Galera and it will actually Output you the full policy that you could actually compile already You can at that point to read what the policy is if you agree or don't agree with it Then you can make some modifications You run the check module which basically checks that it doesn't conflict with any existing modules that are already in your database Then you package it into the binary form and then you install it into the policy database Once you run the last command it becomes active So this is how a policy actually looks so you have on top The module name it will always give you a version So this is actually a modification. I made because it will always start with one dot zero It will then tell well, it will then first state what types and what classes it will be using And then here below it will tell you what actually Is being done so my squirrel needs to be able to read the host name to know which of the cluster nodes It's talking to it needs to be able to use our sync to do the state transfer and then it needs to do a set To be able to know where it actually ended and started So if you see it's not that complicated Given that it's these Five commands and you get a policy which actually allows you to run Yeah Yeah, that's all I have for the moment Unless there are questions or other examples Hi To be true this seems like quite a lot of hoops to run through Even get a normal web server running. So taking into account that any startup Keeps on growing at what stage in its growth part. Do would you suggest that they move from a disabled to a enabled? From a disabled to an enabled When is the right time to invest I would start differently first and for all start with permissive Do not start with disabled With permissive you it won't stop your demons It won't do anything But you will be able to generate policies from there already and then it depends on what maturity your startup is and How much security is relevant to you? So there were some incidents with Docker where people who were running as a Linux actually didn't get affected There being cases in the past where there were bugs in in certain databases Which gods didn't get affected to people running as a Linux. So Yeah, it Running in disabled mode today. I feel is stupid Given that permissive allows you to do everything But gives you at least the audit logs Which means that if you have the time whenever you have the time you can at least start looking at those You can at least see if anything relevant or anything is going wrong there And if it is a small thing and then you can enable it quite quickly if it is a big work Then yeah, you might want to postpone that for a later period Okay, thank you. Hi. Yeah So you talked about compartmentalization and isolation to enhance the security So you also mentioned the example of Apache getting compromised, but then it's only limited to a small Compartment so that the whole system isn't compromised But if there's a vulnerability that is exploited that gives some attack a route on my box Then it's basically game over right because he's rude or it does as a Linux protect me even in this case So as a Linux by default will not protect you in that case unless you have confined the root user That's also possible. Yeah, so on my production boxes. I confined the root users So the box I was on to do the the few tests is not a production box. It's just an extra repository we have So I don't run root confined there But on the real production production machines we run it confined and root can do basically nearly nothing Yeah, you update Okay, thank you Excuse me So how well does a silly next play with the Docker and if so How well green can you restrict the different containers, you know running different services? So, um, I Don't remember which version by heart but there You now may so the in February There were a few updates for Docker and from then it plays wealth with Docker So if you're running latest versions of Docker, no problems. It has namespace abilities It has full support for as a Linux if you're running it on centos or on Fedora I have no idea about other distributions But I presume that most other distributions will be doing as well. Maybe some even better We had one question this side someone Okay, then I guess that's about it. Thanks to Sean


All right. So somebody got to get their fashion.  And I was like, I needed to ask you about that.  Yeah. No, I literally wanted to make sure that I talk to you about that. Cause I'm like, it's no way that you turn Nikki down for soldier. Nah, Safari hit me. He was like, yo bro, um, send some beats, I'm going to get you on the, on the next project. And there was a New York, yo, I cooked up like Nikki. Yeah. I said so, but she don't play. I cooked up like a hundred beats. Yeah. And she only shows one. Like, yo, so far it's like, you're not, not down.  What's that? Yeah. So far corn, he's like, yo, bro, I'm like, yo, bro, I said, like 30 beats, bro. I was like, what's she want? What she want?     That's when they said I add the little, I was like, yo, here and she, she was like, what the hell? And I was like, what? Yeah. I mean, that was like, I even liked that beat.  And it's crazy because that was like one of the biggest songs on album too. Willow Wayne. Yeah. Like Willow Wayne. So how did it feel? Pink Friday drop, Roman reloaded drop a month after Exodus drop coming at young money, coming at Wayne, crazy. How did that feel to you?  So what was your reaction after finding out about that? No lie. No lie. Pushing my bro. That's like my day one. You know what I'm saying? We've been cool for like probably like 20 years. I didn't care.  I ain't gonna get no record with, no more record with Wayne. I said, yo, it's over.  I already knew it. I said, yes, all right. I'm never gonna get nothing over there. That's what I was really tired about.  When he's my man, I was like, oh boy. So did you feel like it hurt any of your like business? Yeah. Yeah.  Did you see it outwardly or was it something that you kind of just like felt? Because some people like outwardly talk about. I knew it, man. Because like even some of the producers that work with Drake and shit, I felt the vibes.  You know what I'm saying? Because some of them like, you know what I mean? Shot to vinyl, that's my boy, vinyl's cool. But some other ones that's really deep in it, I don't really care.  If nobody, if no shot's fired, nobody getting hurt, nobody rumbling, I don't really, I understand that. It's not real beef.  I don't really think it's like, I don't be a big pusher, I don't, I don't be around pushing for him. So that's why I don't even take cash in series. It'd be like, it's like, you know, rap, little rap personal stuff between them. I feel like I can understand, not I can understand, but I think what's funny is the sample went crazy.  Yo, that was, that was, that was like dream, yo, we was, that really went crazy and dream like dream. That's what he'll do. He'll like play football. He like playing NFL. So he'll go in the booth, do his thing and go downstairs, play video games for like two hours. He'll hum something in the booth for like an hour. He'll hum a whole record. No words.  A true musician.     You ain't gonna do that. He kept like taunting me.  I said, all right, why?  So I went down and I forgot what studio's Miami Beach did, one of them shits. And I was just going through stuff and I was listening to that Biggie record and I just heard the, ha, ha, ha, ha. And I told the engineer, I said, yo, bro, chop that right there. I said, that's the beat. I said, chop that. He chopped it. He sent it to me. But the beat, the Exodus beat is not the beat. It's not the original beat I did. Like dream. It was, that beat was so freaking dark and demonic. It was so up. It was mad. Other sounds in there. Yeah. There was a lot going on. Dream said it's too much going on. He just like took out this. He just took out mad. I think he kept like one, two sounds. Yeah. I mean, it definitely didn't help the situation that the song that you sampled was what's beef. Yeah. So it all seemed very intentional. Yeah. I was like, I'm a troublemaker. Yeah, man. Like even with the Nicki record, it was around the time when they were saying, yo, Nicki's pop. She's going super pop. She's not rapping. And she addressed that in this one too. I remember Flex was saying it and like a week later she dropped Bang. So I hadn't.  She said Nicki pop. The only thing that's pop is my endorsement. She made it known. She made it known. Mm. That was T. Want more? Check out our website at www.talkinatownshow.com and don't forget to like, comment and subscribe.


Hi, this is Jennifer Gonzalez for Cult of Pedagogy. In this video I'm going to demonstrate a teaching configuration called the in-class flip. The pattern for a traditional flipped classroom goes like this. Instead of using lots of valuable class time delivering content to students, then having students apply that learning at home, you flip that arrangement, pre-recording the direct instruction and having students watch it at home, then doing the application part, what we typically think of as homework, in class. This arrangement is great when all your students have good home access to technology. But if they don't, the flip can fall apart. And access isn't the only problem. Some homes aren't conducive to the kind of learning that a traditional flip requires. Although districts are working on creative solutions to address these challenges, an in-class flip provides another alternative. Whereas a traditional flip depends heavily on things going right at home, the in-class flip keeps all parts of the flip at school, thus assuring that more students get the benefits of the flipped concept. Here's how it works. Suppose you teach Spanish. This week you're ready to introduce the difference between the verb ser and a star. So just like in a regular flipped classroom, you record a short lecture on this concept. Now, instead of having students watch this video at home, the video becomes one station in your class. So suppose you have about six devices in your classroom for this kind of station. That takes care of one group of six. If you have 30 students, we need good quality stations for the rest of them. Since this is a foreign language class, another station can be a memory game, using vocabulary that's already been learned, along with a few new words and a dictionary to look them up. That takes care of six more students. Notice that this is a game that can be played over and over. It's good to have a few stations like this, since others may require students to go longer than planned. And an infinite station like this one can absorb some of that extra time without students getting antsy. In another station, students could work in pairs, reading a skit that makes heavy use of the verbs ser and a star. For students who have already watched the video, this will reinforce what they learned. For those who have not, it'll act as an anticipatory set, building curiosity about those two words. Just like with the previous station, this activity can be done over and over if needed. Students can switch partners or roles if they get restless. Another station could be a standalone activity, like a cultural or craft lesson, like making cascarones. It's important that activities like this be quick and simple, taking no more time than any other station. Do one yourself ahead of time to estimate the duration. Another station could be a basket of clothes and household objects, along with a set of cards that gives Spanish instructions for dressing up and acting out short scenarios. So where is the teacher all this time? This is what makes this a flip rather than just station work. Because the teacher has prerecorded the lecture portion of the lesson, he is now free to interact with students at the other stations, correcting their misconceptions, answering any questions they might have, but never having to re-deliver the lesson itself. So right now, you'd have exactly the right number of stations for your students. But notice that none of these really builds on the learning that took place in the video station. And if you've ever done stations before, you know that it helps a lot to have at least one extra station to keep things from backing up. So let's add one more. This one will have focused written work that builds on the material learned in the viewing station. Notice that right now, this is left empty. Because students need to watch the video before doing this station, it should be left empty in the first round. To help organize things, go ahead and number your stations. Notice that I made the empty station last and the video viewing station second to last. So get students started at their first station. And after a set amount of time, have them rotate to the next station. Once students start rotating here to station six, this is where you'll spend most of your time to make sure the concepts from the video are being applied correctly. So the rotation would continue in this direction. As students move through the station, some irregularities may develop. One student will need to repeat the video, or a late arriving student will need to be worked into the rotation. Stations are ideal for this kind of differentiation as long as you plan for it. To keep things running smoothly, have a final independent activity, like silent reading, for students to do when they're completely finished with all stations. Or assign leadership roles for students who finish quickly, the dealer at the card game, the scenario reader at the dress-up station, or an assistant at the Cascarone table. If you teach in a self-contained classroom or have extended class periods, an in-class flip could take place in one day, maybe taking about 90 minutes or so, depending on the kind and number of stations you set up. If you teach many groups in shorter periods of time, keep your stations set up over a few days or even a week, with the goal that students will finish them all by the end of a set period of time. I hope the in-class flip offers you a new option for using technology in your teaching. Thanks for watching, and have a great day.


Good afternoon, everyone. I am Ankit Rastogi, and I'm a software consultant working with Zebia, and I'm located in Delhi. So the talk that today I'm going to deliver is home brewing rum. So as we can see, it's about brewing rum. So I would like to say sorry to all you guys for these setting up wrong expectations. It is not going up that how you can make your old monk or Havana or Bacardi. So it's going to be about real user monitoring. So the first question basically comes when we go through this slide is what is real user monitoring? Anyone has any idea? Mintra guys might be knowing. Because yes, exactly, but from performance perspective. So as my friend has said, it's about measuring performance from end user perspective and analyzing it further to make your key business decision. What generally happens? We develop code, we unit test it, we do acceptance testing. All this is done from developer's perspective, QA perspective, as well as a substance scene. But we always lack how performance is perceived by end user. So this talk is about collecting metrics so that we can measure how a particular user is expecting the application to behave, how he is receiving the performance from our application. So this is a sample dashboard taken up from New Relic. It's a rum provider. So in this, we can see a lot of things, just like page load time, errors, and page views. And again, they are segregated by browser types, much like Google Analytics, but for performance. So the first question comes to mind that why I should implement what are the advantages. So it is a known fact that the performance experienced by the end user drives your business. It helps in gaining retention rates as well as conversion rates. So for the business people, it's a quite known fact that there is money in the metrics. Business takes decision on the basis of metrics only. So it's an important indicator that the performance experienced by end users, it can drive your business. Then expectations. End users has a lot of expectations from your application. They want a real good user experience and that's what we really want to do. Then performance is also the key differentiator. It differentiates between you and your competitors. So after this slide, there is nothing to talk about from a business perspective. Rest is good. So how we can do real user monitoring? It's a very simple architecture, not even architecture, a block diagram. It is having a lot of blocks. So it is divided into two parts, a front end part and a back end part. The use of front end part is to collect metrics and the part of back end part is to visualize it and analyze it. So on the front end side, I have all JavaScript. And in that JavaScript, I have basically a plug-in architecture in which I have a core module. The function of this core module is to basically collect the metrics provided by their plugins and send it to the server for the processing. So what all can we track? We can track errors. We can have page load performance. We can track Ajax call. And even we can have a custom metrics. Let's see one by one how we can track these things. So how can we measure page load performance? So this is a typical flow diagram, how a user navigates from one page to another. In this step one, we made a request, either through clicking a link or submitting a form or other methods. Then request reaches the server. After reaching the server application, app servers process it and then give the response, which makes us a step three. Once the browser receives the STML, it begins to process it, which makes us step five. And step six consists of page rendering. So what key metrics we can drive from this? If you want to know how much network lag is present in our application, or in the network not in our application, we can determine it by finding the time interval between step two and one and step four and three. It will make my network lag. And how much time my server is taking to process my request can be found out by subtracting step three and two. Similarly, dome processing time, which is how a browser is processing the STML, passing the STML, can be found out by subtracting step five and seven. And similarly, the total time taken can also be calculated. So how we can do it? There are typically two ways through which we can do it. One of them is cookies. So network time. Generally, when we navigate from one page to another, there is an unload event happening. So just before an unload event happened, I will make a variable and store the time in it. Then the first byte received. Whenever a response came, just putting a script, a custom script which is having a time in a variable, just below the head, I can determine how much time it takes for the first byte on the end user. So by subtracting these two events, I can tell how much network time it is taking. Similarly, dome processing time can be calculated from dome content loaded event and first byte event. And there is page rendering time, which is dome content loaded event and fully loaded event. After getting all these metrics, we will send it to a server for further processing. There is another alternative method, which is performance timing API. It is a new spec, and modern browser supports it, and IE also supports it. So in this, we can get a more detailed picture of the timings, such as we can get how much time our application is taking for app cache hitting, then DNS resolution, TCP request, request response, processing, and unload events. So it gives me highly precise timings. So after conquering page load performance, let's quickly move to ejects call performance. Before further continuing, let me show you a very known code, how you can make an ejects call. Simple three steps make an object of XML HTTP request than open and send method. So if through some way, I can intercept the open and send method, I can calculate the timing between opening the connection and fully downloading the content. So we have used the monkey patching technique for the same, which I will discuss further on before that there is a ready state value. As ejects call proceed, the ready state value changes from 0 to 4. It varies from unsent, opened, headers received, then loading and done. So here also, we can determine time to first byte and downloading time, how end user is experiencing. So time between the send method is called. And when first byte is received, means ready state value first time turns into 3. Will tell me about time to first byte. And downloading time is time between first time ready state value is 3 and when it is 4. If you guys don't like maths, OK, just. So how we can do this? There is a technique or pattern called as monkey patching. So we can monkey pass the XML HTTP method like this. We save the original XML HTTP request to a variable, then define our own variable over it, and we patch it. So as we can see that we have passed the open method and added two listener on it. Ready state change listener and load end. And then we call the original method, open method. Similarly, we have done this for the send method. Just we have seen that there is performance timing API for the page load. Similarly for resources, also there is an API getEntriesByType. So this is how we can call window.performance.getEntriesByType resource. And we can get also key metrics from this, just like appcast time, DNS hit, then TCP timing, request and response. Now let's move to how we can do error handling. So basically, we attach usually our error handling function with onError. But it lacks a few things. It has error message, line number, file name. However, it doesn't tell me about stack trace, character number, and it doesn't even work for cross origin scripts. So how we can overcome this? We have a try catch block. In try catch block, we usually, all of us know that we can handle exceptions or errors. So it gives me all the things that I require to reproduce my error at the server side or a developer can reproduce it. It can give me key information, just like a stack trace, character number, and it even works for cross origin scripts. So this way, I can make a wrapper function and I can wrap any function in a try catch block so that I can catch the error and report it to the server. This is a simple example of decorator pattern. We can use this in this way. Now there are some challenges in error tracking. The first challenge is different browsers provide different stack trace information. Then there is step to reproduce error on server by developer is still missing. Even I get the stack trace, I'm unable to determine what step does my end user have taken so that I can replicate the issue. Then I need to manually wrap each function in a try catch block. Consider case I have a 50K LOC code or a 100K LOC code. I can't manually replace each function call. I can wrap each function inside a try catch. So we will see one by one how we can overcome this. So different regarding stack trace normalization, there are third-party libraries named as stack trace and trace. They are well-tested libraries and what they do is they normalize the stack. Say one browser has another method of accessing stack and another browser has another method. So these libraries normalize it and provides a single point where I can get all the stack information. Now steps to reproduce error is still missing. So what we do whenever a user interacts with anything in my application, I log it in an error, simple. So say I log 10 events in my array and whenever I encounter any error, I send all these 10 events attached to it so that it can be replicated. Just simple, I just attached listener change listener with an input tag. So if anything is typed, it can be added to that array. And if later on there is some error, it can be tracked. So need to manually wrap each function. We can use instrumentation, which I will tell later on at script time or at script serving time or at build time. So now I'm going to tell about instrumenting JavaScript. I will cover it quickly. So this is the basic flow, how JavaScript actually executes. I have a source code. I have a parser, parser generates a same text we having a grammar of JavaScript. Then there is a VM and runtime environment. VM produced the output. Now there is abstract syntax tree. What is abstract syntax tree? I hope some of you guys might know about compiler designing. There is the concept of syntax tree. What we do is we usually represent our source code in the form of a tree so that we can easily manipulate. In our DS, we usually have taught about data structure and we all know how we can traverse trees and et cetera. So this is a simple statement where a equal to one. What are the key components of this statement? We have a keyword, we have an identifier, we have a number and we have a equal sign. So can I make a tree out of it? And this tree can be a language independent way and this tree can also be used to transform from C to JavaScript or JavaScript to C and this is how these transformation and agglification, minification, other things happen. They use this parsing and AST concepts. So I have made a syntax tree. I have a variable declaration which represents that there is an equal to sign, then there is an identifier which tells about A, then there is a literal constant one. So how I can dynamically wrap all the functions in my code automatically using this instrumentation. I will make a parser. JavaScript code will go through it. It will make an AST out of it, which is nothing but the tree representation of source code. Then I have an instrumenter. Say I want to wrap my JavaScript inside a wrapper. I will generate the AST for the same. I will traverse the tree to go to a particular point. Then I will attach my intended AST to that tree. Then it will make my transform AST. Then from that transform AST, I am going to generate transform code. I know it sounds somewhat geekish. I have a sample demo for the same. Ankit, I think we are really about five minutes late already. Could we just move on? Just let me conclude. All right, please do. Okay, so there are a number of libraries available to do the same. We have ES Prima, we have ES Travers, we have ES CodeGen, then we have a FellaFella library, then we have Burrito, all our Node.js base, and all the minifiers, code coverage, our instrumentation tools uses these tools only. Then the last stage comes to analysis and visualization. So generally, we can go to any tool for these things, but I generally prefer elastic search, LogStash, and Kibana for the same. Kibana is the visualization UI for the same, and elastic search is the searching. You can consider it as a search engine. So what are the other use cases of real user monitoring? The other use case of real user monitoring can be if you want to refactor a large-scale code. You want to know the hot areas where you want to first step in. So how you can identify hot areas? By instrumentation, you can inject a code so that you can identify hot areas. And again, when something went wrong in production, how you can automatically roll back? And how you can say, I have set up a threshold of 10, and if I encounter 10 errors, I will automatically roll back to my previous version in production. So automatic rollback also, and you are using crowdsourcing power for testing.


Hi, this is Dr. Don. This is part four of the Monte Carlo simulation problem, and I wanted to call something to your attention that I'm saying a lot of folks miss in their assignments that they submitted. In the second part of the assignment, we not only have demand that is varying randomly. We have the unit variable cost in house and the outsource unit cost. Both of those are varying. They need to vary randomly. I'm going to scroll down here. They are done using the lookup method that you can find in the Excel's fun video. What you're doing there, you're taking the discrete frequency distribution that you were given and then converting it into a lookup table, randomizing a variable that will jump up here and select one of these unit prices and report that out. You can see here is reporting out $125. For the unit variable cost for fast, it's done the same way. It's another lookup table. Here, the lookup value is $150. The random variable came here, exceeded $7, dropped back and got $150. Those are linked back into the model. You can see there is the unit variable cost, $150, and the OUC, the outsource unit cost. Those cells, and I'm going to go ahead and make those yellow so we'll know, those cells as well as the demand, all of those are random variables now in our model and we need to include them. You might think that if we just added them into the model and then did our data table the same way of just including the demand random variable and getting our answer for the difference in the decision, that that would give us the same thing as if we included those two new random variables, but it doesn't. And the reason for that is although the top line looks the same, down the column you'll see that the values reported back when you run the simulation are different here. If I don't have them included versus over here where I do, you can see the pattern changes dramatically. I'm going to go ahead and recalculate here a couple of times. You can see that patterns reported back are different because this one does not include those random variables so therefore they're not being keyed to randomize in this data table. Remember data tables link back to cells that you want to change and we want to change these unit variable cells using the random function. If you don't include them in the data table then they don't get updated and the only thing that's getting changed is the demand and the difference and that's the reason that the two columns look so different. So be aware of that when you're adding in additional random variables you've got to put them into your data table to make sure that you're getting the the correct simulation. You're not just getting a partial simulation. I hope this helps.