Welcome back everyone to theCUBE's live coverage of MY's here in Washington DC. I'm your host, Rebecca Knight, along with my two co-hosts and analysts, Rob Streche and John Furrier. So we're going to do a little analyst angle here. We're going to talk about the great lineup of guests that we've had and dig into the conversations we've been having and what we're hearing and your take, both of you. So Rob, I want to start with you. We had many guests on this morning. We had Jeff Reed, VP of Product Cloud Security, Google Cloud, Eric Dorr, VP of Engineering for Cloud Security. Those are just two of them. Lots of product announcements, lots of new updates. What strike you? What about the go-to-market strategy? What is most salient to you? I think what was really striking and really a good takeaway from this conference is integration and ease of use and AI. Those top three things that really come to mind when I started to talk to Eric and Jeff and we were both on with them and having this conversation about how do they make it more accessible? How do they make security not as scary and how do they really bring a number of different things? Like the attack surface management within Mandiant, the Mandiant attack surface management product that they brought out, plus chronicle security operations that they brought out and renewed and had some new features going into and really bringing that together with what they announced at Google Cloud Next which was really the addition of AI from Duet AI. It was really exciting and I think, again, this is stuff that John and I were talking about at length all the AI announcements that they've had and I think there's a really good thread here that they get that this is hard and the toil and I think you are even reaching into some of the toil and what that means for how people work and I think that was really one of the key things about this is how do you make things simpler so you avoid burnout and don't lose the security professionals? That is exactly what we keep hearing about that these are hard jobs, this is a big, bad, scary world and a lot of these jobs, they can be demoralizing because there is just so much that can go wrong and it's hard to retain people in this line of work. John, what do you think of that? I mean, is AI going to remove the toil, remove some of the hardships of these jobs? I mean, the AI conversation is so hyped up right now, it has to be in the conversation now for sure but in the backdrop of Washington D.C. where this event is, it's been a week of AI and they're still doing intelligent hearings on the Hill, that's all they're talking about is AI, AI, AI, how do you secure AI and is it good for secure? There's two questions to that thing so as industry analysts, we look at it and say, okay, what's happening? I think the big takeaway from the analysis is one, China, the dominance of China and its rise to, as the CEO, Kevin Mandi said, the varsity team or the top of the apex competitor, apex attacker, apex species of hackers, they're kicking ass, so China's huge and they don't play fair. The asymmetry angle is happening, they're saying, you know, someone on the couch, the teenage hackers are effective at social engineering and that's another big part of the story, so that's happening, so the urgency of security as a warfare issue is more than ever a geopolitical thing. I find that interesting. The other thing is we heard from former Gartner analysts here who also was now works at Google, he had an interesting angle too, he's like, okay, they're living in the 90s and he's going a little bit over the top, but in terms of technology, he's equating the outdated, antiquated systems to the 90s, implying and basically illustrating that a lot of the stuff that they're using is older tech. So there's a modernization, digital transformation going on in an industry that's under siege from outside adversaries to new stuff's coming in that they haven't seen before with social engineering and they have now this AI opportunity, so I think, I'm a bullish on AI, I think it's going to be used immediately in areas where it's regulated, where there's no ambiguity. Regulated industries where you know what you're getting and you know the quality of what's being curated and or developed and then you're going to see it really augment the human aspect and I think the conversation is going to be all about the creativity, Rebecca, that's going to be unleashed, so my prediction is there's going to be a creative class emerging out of the tech world, which is weird because you think, okay, we kind of have a creative customer, not in the nerd culture, I mean, imagine what is going to open up for the people defending the attacks when you have creativity opened up and AI does the reports, all the legal filings, I mean, there's a bunch of BS work, Rob, that the top brains have to write the scripts. I mean, I think it's going to be an opportunity, but it's going to be low-hanging fruit first, known things, regulated industries, non-ambiguity will be attacked first with the AI and again, how do you manage the AI? On the other side, AI will be a factor, no doubt about it. Well, I really like what you said about this emerging creative class within AI because really using AI effectively is about asking good questions, knowing how to get different kinds of answers, giving the good prompts. I mean, do you agree with John's take about this sort of emerging creative class in this industry? Yeah, I think it's a very interesting way to look at it that you're going to have to think more artistically. So how much of it is science? Maybe the science is actually done by AI and you have to be more artistic and I don't mean like painting and writing, but you have to use other parts of your brain, which again, I look at that and start to think, okay, one of the other themes that's been going throughout this is thinking differently. We have to be more creative. We have to think like them. The asymmetric attacks from China, for instance, and ScatterSpider and all of these other things that are going on, where they're using social engineering. I mean, that's been another big theme here is that without using malware, without using zero days, people are getting exposed and getting into almost any company. And that's one of these things that companies are going to have to come to grips with, it's okay and they have to be able to understand it. It's going to happen and how do they not become one of thousands, but they're one and done. Out of that. And I think one of the things that Kevin Mandy said when he came on this morning on theCUBE, he was kind of pointing out that the doctrine, I asked him the doctrine question for the government and he kind of, he kind of looked, he said, oh, there you go. He had a good angle. He's like, okay, it's going to be different. It may not be the military doctrine that we had before, but new ways to manage the people who are quote, living off the land, which is the term used for hackers who get in without malware and they get in through social engineering legitimately as a user to the system. So they're in their in compromised environment and wandering around, living off the land, finding the jewels, if you will, for that company. That's more prominent and more zero days are out there now. So we got more zero day opportunities for the hackers. The living off the land allows for to be undetected. So the question is, what's the consequences? Now it used to be in the military doctrine, that if you want to have a free country, you have liberty and all that and if you attacked us, we would attack back, but that's if it's on the ground, like a physical. So now digital, what's the digital version? Like if someone gets caught living in the land, what do you do? But I think Kevin's also, his point on that whole thing was super interesting. He's like, I don't necessarily want the government to go out and regulate things. What I want them to do is put the fear in other people and I'm summarizing what he said. He didn't say this. But he said more or less I want them to put the fear that there's going to be repercussions. You come in and hack into MGM or Caesars or Coinbase or wherever, we're going to come and find you and we're going to throw you in jail. We're going to penalize you. We're going to come and deal with you. And I think that is something that's really not getting talked about on Capitol Hill right now with all this AI and I think the other things when we were talking to Eric and Jeff was about securing the actual data.  And I think that actually is a scary proposition where these become targets, these LLMs become targets themselves. Because they already are prone to do that and they are easily tricked, let's be honest. And a lot of them have some super sensitive data. If you think about it, if you're deploying an LLM or an SLM as I would call them a segmented language model for your financial, your CFOs organization so that you can bring on new accountants and they can come up to speed and ask what is the terminology, what do we mean by EBITDA and how is it composed in art the way we do our financial reporting? If somebody were to go in there and be able to expose that underlying data, that's pretty devastating to a company. I think the other thing too, Rebecca, that came out is that you mentioned toil earlier in AI. The other thing that's concerning is the role of AI at the board level and obviously we know that everyone knows that's an issue. But the rule changes, so the SEC, we had an interview this morning with Accenture, they had a rule change, you got 72 hours to report it. So as a filing on your 10K or 8K, which is really to send signals to the investor market for public companies, this is a nightmare scenario.  I mean, that is like the stock will plummet. And then the Google, I mean, Marshall said it's a buying opportunity, it's not insider trading because it's public information. So there's a whole nother stock market dynamic going on around impact to company, that's not an IT issue, Rob. That's a business concern, one that the reputation risk. So now you got to disclose it. So even if you don't know what it is, you got to go out there. So that's going to be, we'll see if that has teeth. Yeah, at the same time though, we do have to accept and acknowledge that these are commonplace. I mean, these kinds of attacks, these kinds of ransomware, this is just a part of doing business in the world today.  Okay, filings. Okay, that's just more lawyers, more lawyers, more posturing. And so the question comes down to, and I thought the keynote addressed this, are the best minds of our day there are needed to defend being used for mundane, non-productive tasks. So there's a give-get on, is it worth it? Does it matter? I mean, do Wall Street really know the nuance of a living off the land attack or social engineering versus, say, a malware exploit? Yeah, and I think, again, what is that reporting really going to look like in that moment? And to your point, is there enough detail in there for you to understand beyond saying, hey, we've been hit, this is how many customers, stuff was exfiltrated, they didn't get, you know, other than their name and address and email, they didn't get any other personal or credit cards or whatever. Okay, great, but that doesn't mean that it's over. And I think that was the interesting thing is that how long and how prolonged and how persistent these actors are and how they are getting in and sitting there and doing this over months. Yeah, one of the things, we're back on the AI thing, come back, circle back to that piece with the Anton who came on. I got to tell you, I've been so focused on AI for security, I was completely been missing the boat on how do you secure the AI, okay? So the risks associated with machine learning, how adversarial tax impact machine learning models that have been verified, what about verifying privacy, okay? Privacy and context of AI, the risks for threat detection, which is their core business. Fairness, bias in AI and using bias as a social engineering opportunity and transparency accountability. These are real questions. We even saw the LLM presentation on injections, prompt engineering injections. So securing the AI will become a supply chain factor like we're seeing in clown data. So that's an area that we're probably going to be talking a lot about. Yeah, I think that's a huge key is, because again, who wants to sit there and format reports or have to do that. And I think Kevin talked about that. Mandia who was on this morning was like, hey, if I had had this, I spent 85% of my time actually doing, building the reports and only 15% of the time was actually doing the discovery and the details and all of the digging. If I could use AI to go and format these reports. But again, he was looking at it from a more grammatical perspective. I look at it and go, what if it's hallucinating and it just popped something weird in there? You still have to go back and QC it and understand it. But maybe you can shortcut the toil out of some of those types of activities. Lastly, I want to talk about co-opetition, because that has been another theme that we've been hearing about. We're going to be actually talking later today with Charles Carmichael of Mandia Consulting. He got up on stage with people from three different companies, Microsoft, Barracuda and Coinbase, where they all were really vulnerable, talking about what happened at their companies and shared in ways that you would think, why are you telling this to us? This does not make you guys look good. But sharing this, saying, here's what we did, here's what we learned, and here's how we're keeping it from happening in the future. These are really important steps to be taking and also as an industry to be taking together.  Well, I'm struck that there's not a lot of AWS discussion here, but that's another cloud. Google's now part of this. Microsoft's been very open. Google and Microsoft have been very open clouds from a partnering standpoint, among the hyperscalers. Amazon obviously number one, they're going to be there. So if Amazon was on stage, it would have been blown away.  That would have been like a killer panel. But I think sharing is going to be part of it. And this is where the shared responsibility model that we've reported a lot about from Amazon reinforced in the industry is huge and I think the sharing and collaboration will probably be the answer to a lot of these known problems Rob, you were hinting at the accountability piece and how do you, what's the punishment to keep that people deterred. So I think you're going to see more sharing, but it's still an opportunity for the exploits and the hackers because there's a lot of seams that they call it when people kind of work together. And that has to be nailed down. I think you'll see a lot more collaboration across clouds. The CASB question was the broker tokens, how do you handle things like that? I mean, there's a lot of technical things that need to be put in place just to do that, right? So I think it's challenging. It's a lot of more cultural discussion Rebecca than it is meaty tech yet because multicloud is just emerging or super cloud as we call it. So I'm optimistic. I think culture is where I play rather than the meaty tech, I leave that to Rob. It's a good culture. They have to share. And that's why the FBI is saying, come to us. Now, Scuttlebutt on the hallway around the FBI director was the FBI saying, hey, we're not going to raid you. Okay, we're going to be safe. Meanwhile, the SEC is cracking down on all the crypto companies. So it's like, like there's a little bit of a trust factor involved in the government side of it, but you know, private public partnerships. But I think also to the whole ecosystem. I mean, again, Eric having been at Microsoft and now only, you know, been at Google cloud and helping to catch Mandy and then really do the integration. I think it becomes one of these where these people move around.  You know who Charlie is? Charlie's Charlie Bell, who used to be at AWS. So he tells the story about how then Charlie called Satya. It's like, you start to look at all of these people and how they come together. And it's- You know a thing or two about that, too, Rob. Yeah, I mean, having worked with Charlie. So I mean, it's very interesting to see how that stack comes together. And I think to John's point, I would have been blown away to see AWS here. I am still struck about how prominent Microsoft has been here and some of the others who are co-opetitioned. And I really love it to tell you the truth. I think it's definitely needed. I think the ISAC discussion that we had with Eric and with Jeff earlier today about how the industries are coming together on their own. I still agree with Kevin that, you know, I don't know that there needs to be a bright red line or something like that, but there needs to be repercussions. And that's the only, that government has to do that. I don't see private industry going out and taking out, you know, having offensive capabilities to take out, you know, the scattered spider folk or anything like that. Well, from an American standpoint, if you're an American and the digital soil, I call it, is our land. And if troops dropped on our shores, the government would probably respond with military force. So, you know, I've always been advocate, people on theCUBE know I've been mind ranting on this all the time for years, that when the digital paper cuts that are cutting us up, they're below the doctrine of attacking because what does digital even mean? So I think the world has woke up in this show again, I think amplifies the fact that this critical infrastructure is victims. They use that on the stage. They say victim being taken down and financially hurt or mostly hurt. And so it's not just hacking for infrastructure stuff.  You've got identity theft, all this stuff's happening. So I think this digital land of soil is being addressed. I think now you see the industry stepping up. And Mandy has been leading the charge here because they're the threat detection kings. They got the data. Great. Thanks so much, John and Rob, for sharing this analyst angle. Thanks. I'm Rebecca Knight. Stay tuned for more of theCUBE's live coverage of MYS. We'll be right back after this short break.


Community-based podcasts can actually help your channel grow. For those of you unfamiliar with the format, podcasts are almost like talk radio, except for they involve webcams and the internet. These are great ways to grow your channel. Why? Well, I'll tell you why, because you talk about several different topics, all of which you put in your tags, title, and description, and help you get your channel out amongst the internet all over YouTube because of related video searches, because of YouTube search, because of people talking about you and linking back to you because of a discussion you may or may not have had, you know, six, eight, 10 months ago. These conversations, these podcasts are great because people interact with them quite a bit, actually. Podcast channels here on YouTube are growing exponentially right now. The reason that they're growing is because they do start conversations. Now, I was recently asked to be on Alcohol Arcade, which is a geeky, newsy-type podcast, on a channel with four subscribers. Most of you would probably assume I would have said no. I didn't say no. In fact, if you look behind me, you will see an example of what we did.  But it's like with a really soft, like cool noodle, so it's okay. If memory serves, about six months ago, there was some big scare about Minorama possibly being a sham. Yes. Okay, and if memory serves at the time, wasn't Bebop Vox one of the big champions of, no, it's not a sham? Or was he on the other side? I don't remember. Yes and no. So what if this guy, Lou, has a split personality and he's just kind of crazy? What if he's dealing for himself? Exactly. Minorama's heart grew three sizes that day. And then they bought it and... I wanted to sing a little with a muffin man. We've read $7. What is more important than George singing the muffin man? What could he possibly be doing other than singing this child song? Seriously, George always has a million projects that he's working on. But I know right now he's setting up a lot of the business development stuff, kind of the boring adult-y stuff. What does your company have to do with the muffin man? That's the real question. If you'd like to see more from Alcohol Arcade or any of the podcasts that we produced in that sitting, click the link in the description. We talked about everything from U-Cube to Minorama. We also talked about Freedom and some of the stuff coming down the pipeline. No huge spoilers, but maybe filling some people in.  If so, let us know in the comments section down below. I want you to copy and paste the URL of one podcast video into the comments section. You'll notice that when you do this, it actually transforms your URL into the title of your video. This is the spiritual successor to YouTube Replies, which is a feature we don't really have anymore. But you can still do this, which is equally as good. Hopefully, we'll all check out each other's podcasts and we'll have a good time in the comments. Till next time, I'm Anthony with Freedom. Like, subscribe, comments please. Till next time, guys, my name is George and you've been watching, click the first video for a fireside chat with George where he shares our future and how we grew from $20,000 to $120,000 in just one month. And click the second video to see how to monetize all of your videos with just a few clicks to enable all ad formats and monetize in all countries. And we will grow together as a family because this is the Freedom family. You are part of it, we are all part of it and we're all growing together. So grow with us and partner with Freedom, and that play now button right there on the video bar is all you need to click to get started. Your secrets, if you really look at yourself, you will be speechless. What happened to being doctors and teachers? What happened to being your brother's keyboard? Now a day's key...


Patriot Prime Reviews is a channel for adult collectors and may not be suitable for children under 13 years of age. Viewer discretion is advised. Hey, what's going on guys? Patriot Prime here once again with another ToyHacks.com sponsored video. But before I get started, I need you guys to do me a favor. If you're watching this video right here and are not a subscriber of Patriot Prime Reviews, please consider hitting that subscribe button right now. That won't cost you a thing, but will help me and my channel out tremendously. Now, on to the decals. And the set we're looking at in this video is for Transformers Legacy Blitzwing. And this decal set includes six decal sheets on a combination of foil and vinyl backing. So now, without further ado, let's take a look at Blitzwing both before and after ToyHacks decals. And welcome to Patriot Prime Reviews. In robot mode, straight out of the packaging, Blitzwing looks really good and spot on to his animation model. Taking a closer look at the figure, he does have a red square right there on his helmet crest. Red goggles, silver face and of course a yellow helmet. Some yellow here for the chest and a silver outline Decepticon logo right there in the middle. He does have silver and red pecs, silver there for the ab area, silver for the hip skirts, silver for the thighs and silver for his tail fin feet. You can also see some yellow there on the inside of his legs. Also Decepticon insignias on the outside of his legs. I mean, he doesn't have a lot of paint applications, a little bit of black right up here and purple along the shoulders. But he has tons of sculpted details and he looks really good. But I cannot wait to see what ToyHacks can do for him. So there you go guys, one final look at Blitzwing in robot mode before and after. Blitzwing gets quite a few new decals to help enhance his robot mode and what an enhancement do they make? Taking a closer look at the figure, we'll start here with the head. He gets a brand new red chrome visor that just looks spectacular. This is actually in three pieces. You have a front and two sides. But once you get those on, that looks so good. He also gets a new red chrome piece here for the chest, new yellow decals here on either side, little decals right here that go above the silver on his pecs, new decals here for the chest, a new Decepticon insignia, red right there for his belt buckle. Moving on to the forearms, you get tan decal right there with rivets and decal right above the wrist. Up here on the shoulders, he gets missile pod decals or you do have the option of just vents. I felt like this is Blitzwing. He needs missile pods. He also has missile pods now up on his backpack. And speaking of the backpack, you got new decals back here that accentuate the wings a lot better. You got some gray and red on this main section and his small wing and a purple decal right there. Side of the arm is another tan decal with the rivets. A number three, and that's actually on both biceps, but word of warning on this, this three is on a clear background, but the clear background is way too big for this section. I actually had to trim off the clear background to apply that. They may have fixed that since my purchase, but just be wary of that. Blitzwing also gets hip mounted miniguns, which is really cool. Moving on down to the legs, nothing really for the leg area except for the new decals here on the shins. There are decals for the feet and right there underneath, but that's more for the thrusters. So yeah, Blitzwing gets a hell of an upgrade thanks to Toyhacks, and he looks so good now. So there's Blitzwing in robot mode after. In tank mode, straight out of the packaging, Blitzwing still doesn't look that bad, but he does look a little weird with his G1 throwbacks here, especially with the protrusion sticking out from the front. I wish they could have designed that so it could push in a little bit, maybe even out with the front of the tank. But oh well, and then he's got the thrusters there on the back. Aside from that, love the molded details on the tank. It looks so good with the treads and the vents. The details up here with the grenade launchers, the hatch. There's a purple Decepticon logo there on top. In front of the tank, you can make out Blitzwing's head right there, but it just looks like a yellow section. Then you've got the silver and red details from Blitzwing's chest right there on the front. And really, that's about it. Not a lot of color, but lots of great molded detail. So there you go, guys. There's Blitzwing in tank mode before and after. Blitzwing's tank mode gets quite a few new details thanks to toy hacks. Taking a closer look at the tank, starting here at the front. You can see he does have new headlights. There's a blue and a yellow. There is new silver decals here on the battering ram that cover up the red translucent plastic. And of course, you see the decals from Robot Mode's chest. Come on down, Auto Brat is right there on the front of the tank, and there are options for that. That is originally shown on the toy hacks website to go up here on the turret. But there's enough room on the tank to really put pretty much all the options on here. You can see depth to traitors on top of the turret. You've got the come on down Auto Brat. There's some extra decals that we'll show off here in a moment, so yeah, there's plenty of room for everything. Moving along the side of the vehicle, he's got a red arrow on the front. Tan and red decal right there. A decal right there. New decals for the vents that look really good. Love the metallic look. You got a purple and red decal there. And a nice throwback to his animated character. Tell me what's on your mind. On the back of the vehicle, he does have taillights now, and new decals for the thrusters. And you really want to pay attention to those because you want to make sure you match up the right decal to the right molded section of the thruster. Look on Toy Hacks' website. They'll show you how to do that correctly. Here on top, new decals that cover the vents. And on top of the turret, we've got a plate with 0.3 on it. Some hash marks showing how many Autobots Blitzwing has taken out. A silver panel with a Decepticon logo. Another silver panel right here.  And purple and red decal that wraps around the barrel. Now even Blitzwing's oven mitts of mayhem get decals right here that makes them concussion missile launcher systems. So if you choose, you can attach these two Blitzwing just like so and it falls off.  But there's an option there for you. So there you go guys. Blitzwing in tank mode after. And now we come to everyone's favorite mode. Blitzwing's jet mode straight out of the packaging really suffers from its G1 aesthetics. I mean it's big, it's blocky and it doesn't look aerodynamic whatsoever. Unless you look at it straight from the top. But still, it's not bad for what it is. I mean it is a generation one throwback and triple changers do tend to suffer in one mode. Now taking a closer look at the details. Right here he does have a silver nose cone. Red canopy. There's the yellow from the chest of robot mode. Silver right here, here and there. On the wings he does have yellow striping. Decepticon insignias on either side. The silver tail fins and of course underneath is all of the tank. Just like all the other modes, it's colorful but it just lacks some extra detail. So there you go guys. There is Blitzwing in jet mode before. And after. Toyhacks must have really felt sorry for Blitzwing's jet mode because they really made this mode pop. Taking a closer look at the figure starting here with the cockpit. Brand new chrome red decals all over with a new purple section right there that breaks it up. New chrome decal right there just behind the nose cone. New decals right here on either side of the cockpit with new yellow decals right there on the side of this chrome piece that carries over from robot mode so it really elongates the whole cockpit. New red decal right there and new yellow decals along the wings that kind of give it a stripe look with the little black triangles. Moving on down we've got new gray decals here on these sections and down here on the wings with some added new Decepticon insignias. New decals right there. Red decals along the wings here and here. And on the tail fins new red and silver decals with an optional triple on it. I put that on there I just like the way that looks. And of course you've got the thrusters once again with the decals in the center. You also see new decals here underneath and missile pods right there. You can never have enough missile pods because there are other missile pods right there. Also we've got little red decals on either side of the jet and I just think this looks awesome. Toyhacks you did a great job on Blitzwing's jet mode. So there you go guys, Blitzwing in jet mode after. Toyhacks definitely scored a touchdown with their decal set for legacy Blitzwing. And what I really like about it, every mode benefited greatly from this decal set. There was not one mode that got more than the other. I think the details were evenly distributed over robot mode, tank mode and jet mode. The figure looks fantastic now. So huge kudos to the design team at Toyhacks. If you have a legacy Blitzwing, this decal set is a must have. Now guys if you enjoyed the video don't forget to like, don't forget to subscribe and don't forget to click that bell icon to get notified when I upload new videos. Also if you're in any position to help out the channel, I do have a super thanks button and I also offer channel memberships and I have to give a huge shout out to my current channel members because it's support like yours that helps keep this channel going. Once again guys, this is Patriot Prime, signing out.


And we will begin Fabrics of the East, Emily's Dress. Welcome to the Abbey's Historical Society. Home of the, do not touch that. Don't touch anything.  Now, we have on display here some relics from the Historical Pioneer Valley. Now, I know this wasn't your first choice in field trip but I assure you that this is going to be far more entertaining than some decrepit amusement park. Now, if you follow me this way to the foyer I can show you some very fascinating old land deeds. Stacy, you would not believe where I am right now. Not Six Flags. Yes, they canceled our field trip because of the storm. So now I'm stuck at a museum that smells like old people. Oh well, it'll be a good time to work on some mirrors for my new songs. Emily, you can't keep leaving me behind. We're field trip buddies, remember? Yeah, no. It was just an nerd I'm partnered up with. Sorry. No cell phones in class. Remember, you're going to get in trouble. What do you two ladies think you're doing? Um, I'm on the phone. Duh. Do you think Emily Dickinson had a phone or Robert Frost? Actually, Robert Frost lived until 1963 so I'm sure he had a phone at some point. Well, aren't we a little missnow at all? Yes. Well, if you're so knowledgeable about history why don't you two do my job? Sure, it's my dream to be a librarian. Yeah, I know. I've got other career plans. Oh, huh. Writer. Lovely thing for a young woman to do. Not just anything, but something. I'm going to be a rock star. Rock star? Well, I have. If you ask me, I think girls should stick to quieter hearts. Um, what's that supposed to mean? Well, take Emily Dickinson, for example. She kept to herself her whole life, writing poetry alone in her room, and now she's one of the most renowned poets in history. That's because she was good. Not because she hit from the world. I like to think it's because she was disciplined. That's really weird. Oh, I almost forgot to mention we are very proud to have on display one of Emily's dresses. It is said she wore this ensemble quite often. Wow, so historic. Yeah, it was really uncomfortable. I just realized I think I left some of your classmates alone with the China dolls, and you kids better not be having any fun. The black fabrics of the East displayed to be the despair of everyone, but here and there. Listen, it's a nice poem. A humble purchaser, for though his price was not as gold or arduous there is, that one should comprehend the worth was all the price there was. I don't get it, but it's kind of catchy. So, thanks. You do not have a marriage in Washington's. I bet if you cut off the sleeves, it would be a cool and touching look, maybe. You have noticed my phrase is great, don't you? That's not true. I would totally agree with you. What? You can't do that. Be careful, you're bad at this. Look what you did. Coffee on a white dress, we're so good. Now if you follow me this way, children, we are going to go to the pottery exhibit. What have you got there? Nothing. Reprimand you. Emily's dress. What have you done? I swear to God. Well, no pottery exhibit for you. I am going to have a word with your teacher and you are going to wash this until it is spotless. If I find a single thread out of place, you are in for it. Why did you do that?  Follow me. Can't say go to six flies. Then I'm stuck at a museum doing dead people's laundry. You're better. We're at the museum after hours. Yeah.  You constituted time. I was you with your name. A revelation of yourself was there for a day. Pardon me, ma'am. No! I'm sorry. I made a start on you. I only meant to ask, where am I? Where are you coming from? I'm not sure. One woman I was at my desk in my room and the next time, I'm here. What are you doing wearing Emily's dress? You're going to get in so much trouble. This is my dress, silly. I've been wearing it this whole time. What? You've both got some odd clothing on. In fact, this is all very strange, isn't it? Am I dreaming? I must have fallen asleep. My name is Emily. Emily Dickinson? How did you know? You're one of the most famous poets in the world. I must be dreaming. No one knows that poetry except a few select people. Not in our world. Look at this. It's a whole book with your work. Poems of Emily Dickinson? Oh, these are private. I'm completely altered. What are these little dashes after all of my sentences? Who could have done this? Published by Mabel Loomis Todd and Thomas Micworth Higgins. Oh, they're supposed to be my friends. That's not all. Look around. This whole room is dedicated to you. Oh. This is no dream. This is a nightmare. That this isn't your nightmare. This is mine. How do we burn this book and take down these clippings? I'm sure there's more than one copy. I'm sure there's more than one copy of that book. Oh, what? Oh, yes. Are you the curator of this establishment? Who the devil are you? Museum hours are ten to four. Yes. I'd like to formally request that you dispose of all my personal material at once. You have no right to display someone's work without their consent. Sorry. Where she comes from, you can take things from her. Is this a friend of yours? We actually dressed them up. Are you wearing Emily's dress? This is a historic museum, not a playroom. Everything in here belongs to me. You better put that back. Sorry. Can she at least stay to help us clean? Fine. I didn't realize it took a whole team to clean a dress. Now I've got a sandwich to get back to.  Hold on. Oh, what's the point? My whole life leads to this exploitation. What's so bad about it? Like, I love to have people like my work, my songs as much as they like their poems.  A rock star. I don't know what that is. It's a different type of music. Musician. Well, in my amourst, all the women I knew were virtuosos. It was the height of fashion to be exceptional on the piano. I'm a poet though. Art should be shared. No, believe me. An artist is better off keeping her work to herself. That way no one will judge it or appropriate it. What are you going to do? Stop writing? Of course not. That's like asking me to stop breathing. I will write, but I will hide my words away and I'll hide myself away as well. Then, before I die, I'll burn them. No. I can't let you leave. I can't let you leave without letting you know how important it is for people to know your poetry. Mr. Johnson! What is it? Are you done yet? Oh, I see a knot. So, what do you need? Sponges. So, hydrogen peroxide. What? No, do you think I don't have any clothes? Why do you think I need you? Mr. Johnson. How have Emily Dickinson's poems impacted you? Me? That's a highly personal question. I suppose I like how she can bring light and beauty into dark subjects. She can turn death into a friend and hope into a bird. She's got something for everyone. That's it. Thanks. But she never... But like, no. Didn't she never want... I thought she never wanted... But she never wanted any... No, that's true. She kept to herself her whole life. After her death, she wanted... I think if she really... I think if she really wanted to hide herself in the world, she would never have put anything down on paper. Is that it? Yeah, thanks. Good. Get back to it. You've changed lives. Without meaning to. That's the best way to do it. We are different artists, you and I. My words. My words. My precious words. Might be twisted and turned by the wrong people. What if they were twisted and turned by the right people? For the right reasons? Hmm. Well, let me see one of your poems. Well, let me see one of your poems. Not even mine at this point. Can I join them into a song? Why not? They've already been co-opted. The road to me. Tender. Majesty. The message is committed. And I cannot see. A sweet countryman. Judge 10. I never knew my words, but it sounds so... melodious. See? You share art. Like... Why would I want it to be cold? Cool means... I'll tell you good things. So you're okay with this future after all? I'm not sure. It's not that simple. Imagine if someone stole your diary and hung it up on the walls for everyone to look at. I do know that I ought to return. Then you could at least think about what we said. I will. But how do we get me back to my desk in my room? Hmm. You came right after I read this poem, so maybe if I read it again, then you would go back to your time. You were truly tired. You were right. You constituted time. I deemed eternity. A revelation of yourself was therefore day and time. The absolute room you were willing to go with that I and to himself adjusted my slow, idolatry. And goodbye! Can I offer you some space when you're doing the loop now? I have no idea how you did it, but I definitely think you've earned your freedom. Mr. Johnson, nothing's changed, right? The world still knows everything is in our palms, right? Right? Why do you ask? It's just that we think that Ellen changed what I said. She did want them to be shared. Change to mind. No, Emily Dickinson hid herself from the world her whole life, especially her poetry. After her death, in her will, she ordered to have her poems burnt. Come on, Emily. Now, luckily for us, she had some friends and family who knew better. They published her poetry shortly after her death. But do you think she would have been happy about it? I don't know. I certainly am. Aren't you? I am. Yeah, same. Oh, by the way, in case it wasn't perfectly clear already, you are both banned from the Amherst Historical Society. What?  Bad! Whoa, Molly. How does it feel to be the bad? Well, I got to stay after hours at a museum. And I met Emily Dickinson, so I guess it wasn't all that bad. Yeah. And I guess books and that stuff can be pretty great after all. Want to go back to my screen? Sure. I still don't like it. I neither do I. We're going to come up and ask more questions about the script. We're hoping to do more iterations of this script in the future. And please come up. Please see the dress, the actual dress so you can compare and contrast what our relic looks like. Thank you so much, everyone. Yes, please. You may start moving on. Thank you.


run through Hall of Fame. Yalming. Yalming, that's who I was gonna say to. Let's go Bill Russell, R-A-P Bill. And then we can go Steve Nash. Everybody and their mother has played for O.K.C. Chris Paul. You're pickin' the letter here. Chris Paul and Jake Jordan. I don't know who you want. Russ, like, let's do Russ. Yeah, Russell Westbrook. And then Al Horford, you remember Al's O.K.C. days. They were not very good, but they happened. And then we can go Katie. We'll go bottom one, Grayson Allen. Jeff Green for the Jazz and Rockets. Wow, yeah, nice. Oh, Gordon Hayward. Oh, he did, right? Oh, look at us go. Wow, that was pretty easy. I feel like the NBA ones are always easier than NFL ones.


Crate has actually is a database which is developed in Austria and as you can hear from an accent I'm not, I'm one of the few people in the team who are not Austrian, I'm German. The other guys are really Austrians, which basically means if they talk Austrian dialect I can't understand anything. So we are supposed to speak the same language, but it's sometimes not the case. Crate is not very known in the US, I guess that's as well for the late hour and this is not a lot of stuff like here, but I think it's actually a really, really cool project, open source project, database project. It actually won a TechCrunch disruptive startup battle field contest and yeah, I'll just let me give you a little bit of an overview and yeah, so the title of the slide is Big Data from the big Austrian mountains. So yeah, let's go into it. So what is Crate? Crate is a database which was built to scale massively. It is a database which is, so it's not a memory database which are right now very popular, it's a database which has for sure cache and memory, but where the main idea behind it is to have a database where you have persistent storage. It has very powerful search capabilities and it actually can do very powerful data analysis. It can run very powerful data analysis in a large cluster and currently the, for example, the cluster sizes we have deployed is, so we have a couple, so this is still a very young product, so there are a couple of projects we now have, so a lot of projects we don't really know of because they simply use the open source version of our product and we don't really know what kind of scale they have. From the production systems we now, one of the bigger ones is about something like 120 nodes on running on hardware and with about 3 billion inserts per day. So that's kind of something like the scale where you can get to. So it's a really scalable database. The reason, by the way, so I always kind of mix it up or have difficulties with it. So it's kind of, when we're talking so about Crate, there's kind of a little strange thing, so I basically say Crate is built on no SQL technology, on a no SQL architecture, but the database understands SQL. So this is kind of a little special case here. So we have kind of like a lot of features you will recognize from no SQL databases, but it understands SQL and that's why it's a new SQL database. One of the targets of Crate is to be extremely simple to operate. So it's a database which is specifically built for easy operation and especially to attract DevOps people and developers because you just can simply install the database by yourself and to a certain kind of degree, most probably many dozens of nodes, you don't really need a dedicated database person for it. So you just can more or less run it by yourself. Crate scales almost in linear fashion when you add new nodes and it has the search capabilities or basically the queries, they scale with it. You can run Crate on commodity, hardware if you want to do that. It will for sure scale better on basically server hardware, SSDs, a lot of CPUs and so on, but it's actually doing very well in scaling and you can very well scale out horizontally on commodity hardware. There is no centralized storage or whatever needed. It's basically a shared nothing architecture. Storage is all locally. And Crate is extremely elastic so basically adding new nodes or taking nodes away. This is something which doesn't really require a system administrator to add a new node or to take it away. So you just can simply stop the process, shut the server down and Crate will figure it out by itself. Or you just start a new node and Crate will even figure it out by itself. So it will automatically, the nodes in the cluster will detect the new node and they will start to stream data to the new node and just give it something to work. It's very resilient so as long as we have, so we have in Crate we have all the good stuff like sharding, partitioning, replication. So as long as you choose a replication factor, which is basically big enough, the cluster will be extremely resilient. And even if, for example, let's say you have a replication factor of two and you take two nodes down. So then, for example, because accidentally you just actually rebooted the node, when it basically, the data will be for a while, some of the data will be not available. And then when the nodes come up again, the data will be available. So even that is just not killing the cluster. It has read after write consistency. So what that means is it's a typical node sequel architecture. We don't really have transactions but you just have atomic consistency. And when you actually write and create a row to the database and you just after that immediately read, you can be 100% sure that you just get the change row back. So let's read after write consistency. So when you look in the database solution space, then I don't know if you noticed but there are a couple of reports every year coming out about basically new databases. They're right now most probably a couple of hundred different databases existing right now. There's a wide mix of databases and different kind of storage technologies, different kind of data models which are behind it. There's a huge variety of databases you can actually choose from and a lot of them are as well open source like create. So to give you an idea where create is actually located, so even if create is based on elastic search, so it's basically I will show you later some slides. So we didn't reinvent the wheel. We just started basically and used reuse some other open source projects. So even if elastic search is here at the documents store bucket, we see create specifically for create and cloud usage. So I'll later show you why that's the case. So our problem right now is we are really drowning in data so there has been never so much data generated as in our time today and at the same time what we are doing, what do we really do with the data? So we have the problem that there's a lot of data is generated but we are just not really able to analyze it in a proper fashion. So there's an estimation this is by the way something I have to give credit to Cassandra or to Datastacks. That's numbers I had actually from one of their slides. So the estimation is that there's about a set of bytes of data in our world today which most probably is about 135 gigabytes of data for every person on this planet. So what are basically the challenges in this kind of environment so if you look at the basically traditional data and kind of compare the properties we have here then so in the with the traditional databases I have most probably data, so my database sizes are ranging from gigabytes to terabytes while when we talk about big data we are talking about petabytes or exabytes. Then with the traditional databases I'm talking about the centralized database while very clearly with petabytes of data this is not possible anymore so you need actually a database which is a distributed database. That's what Crate is. Then another challenge is that in the big data space while we have in a traditional database we have a lot of data which is structured. We have basically our table structures which not very often change. In the big data space we very often have unstructured or semi-structured data which can basically change from one day to the other from one record basically to the other. That's as well something Crate can manage. And in the old traditional data space we have stable data models which can be very deep. In the big data space that's a problem so we are actually trying to have flat schemas because otherwise this is not really manageable. Very often the relations we have in the traditional sense they are actually resolved as embedded relations in the data itself. So that's how this is actually working. In the traditional data space I have a lot of complex relationships. In the big data space I have fewer interrelationships so a lot of interrelationships are as well they are basically embedded. Then in the big data space I have real-time a lot of real or basically I have real-time data. I have analytics I want to do and I have search. In general one of kind of stuff like the patterns we have noticed in the last couple of years is and this is something we have seen over and over again is that a lot of people in internet scale projects they actually use technologies. So they basically use a mix of technologies for data storage. So very often they use a relational database in combination with a document database in combination with some search functionality they need and then they have additionally they have a blob storage or a storage basically where they store their web assets for example. So people build different stacks here with React, Solar, Rados or MongoDB, Elasticsearch, RITFS, CouchDB, Elasticsearch and HDSS with Hadoop. So this is something which makes projects really complicated because you just have different data stores and that's basically what Crate is actually trying to do. So the target for Crate is that you can combine this kind of technologies and that you can have a database with no SQL capabilities with actually a flexible data model. So kind of like in a document oriented database to store your data with blob storage and with search in one single open source product. So that's what we actually trying to do. So this is very quick. I want to show you how easy it is. I hope you can actually read this. So I wanted to show you how easy it is to set up Crate. So this is basically another target we have as well. So this should be the easiest database we ever actually set up. These instructions are for starting an instance on Amazon EC2. So this is here from the EC2 command line. This is starting basically, I think this is an Ubuntu image on Amazon. You log in to your server. Then this command here is loading a shell script from the Crate server which is analyzing what kind of Linux distribution has. It's just going to install, you can do that as well manually if you don't want that someone is executing, that you're executing a script which you haven't reviewed. So there are instructions on the website. So this is adding local repositories to your Linux server and then it's just going to install Crate. At this point, I'm sorry for the color here, at this point Crate is already installed and you can access it from the dashboard. And when you want to start to create a couple of tables then you need to install basically a command line tool which has the nice name Crash. So this is actually the Crate shell called Crash. This requires Python. When you have this actually requires Python PIP, so the Python package manager, then you install Crash. Then you can call Crash and that's actually, as I noticed, this command is missing. So it's simply the command of Crash and this is the Crash command line. You connect to the local server you have installed and at this point you're connected to your database and you can write basically, you can carry the table, you can insert data in your table and you're good to go. So this is basically all what's required to install Crate and get it working. When you want to install a second server, then you basically repeat exactly the same steps here. If you are in a subnet or if you are not in the cloud, so if you're locally in a subnet which can, which accepts multicast traffic, then the second node will automatically find the first node and the database you have or the table you have created at this point will sync up with the second server automatically. So they find each other and they will build together a cluster. On Amazon there's one step more required if you want to set a cluster with multiple nodes. So Amazon doesn't allow multicast messages, so we have a plugin which either allows you to use single casts or even more elegant. You can, at the time when the EC2 instance has been created, you can give the EC2 instance a tag and then you can define in the Crate configuration that all the servers which are running in your account which have the same tag are part of your cluster. So what's happening is that every couple of seconds your server is scanning using the AWS interface to scan for other new servers with this tag and then it automatically connects them together. To give you an impression about the syntax for the SQL syntax for Crate, there are a couple of additions. So one of the things I was mentioning before is that Crate is allowing for basically semi-structured data. In semi-structured data you can actually define, so either you can define this here explicitly and for example doing something here like an object which then basically has nested attributes in it or you can simply start, you just actually, for example, create a very basic database schema and then you just simply start to insert data into it. And at the time where you start to insert data, Crate will automatically will try to figure, will first notice the columns which it doesn't know. It will modify its internal structure of the table and it will learn, the table will basically learn the data you're just inserting. So it's adapting the metadata of the table structure. This is default behavior if you don't want that because for example you don't want if you have false data or faulty data and this data is creating new columns then you can actually turn this behavior off. But the default behavior is if you insert data then this will, so Crate is going to adapt the table metadata. Also you see here a couple of keywords which are going into sharding and partitioning. So I'm defining here how many shards I want to use and also I'm defining on which column I just want to do the partitioning. Also at this point I'm defining how many replicas I want to have in my Crate cluster. So replicas here in this case mean number of replicas, two means that in three, that in the complete cluster I have in total I have three copies of my data. And then you try to find out if for example you can simply insert data so you can do a mass insert. So for example one data source you can use is JSON. So if you have this kind of JSON file then you just can simply do a copy from and then it will insert it into the database. So Crate actually tries to figure that out by itself and it kind of stuff like rebalances the cluster on the size of the partition. But as well you can for example you can define here you can define ranges so you can explicitly define what is part of a partition and how many, how the petitions are actually used. So the petitions are, so all the petitions you define here are as well in all the shards. So the petitions basically define the range of the values. So it basically defines that the bucket where the data is in. So it defines the partition. That's correct. Let me actually think about it and I'll come back to you at the end. It actually maps so the, so because it's actually sitting on top of it this is actually mapping to elastic search. It's an elastic search term, correct. So Crate is actually written in Java. So as elastic search is written in Java you will need to have, so Java is going to be installed as part of the process. One little information here so that's something which I noticed yesterday with installing the latest version of Crate. So the latest version actually requires now Java 8. So when you install it you need to make sure that your Linux distribution has basically Java 8. Otherwise you will need first to install it from somewhere else manually because then the whole installation process will be not able to get the right Java version. There are different drivers available for talking with Crate for different programming languages. I'll talk a little bit later about that. These drivers talk with Crate either through a REST interface or there as well there's a binary interface. And I think binary interface is mainly for Java clients. There is a UI with Crate where you can see basically the class status. So basically it will tell you where, so how many, so it will give you an overview about all the tables in the system. It will give you an overview of where the system is regarding loads. And it will also give you an overview if there's any kind of problem in the system. So for example if there's a note down or if there's certain kind of data or if they're just under replicated. And in this case it will show and it will show as well which kind of action it's taking. There is a blob storage which you can use so there's an interface for uploading and managing blobs. These blobs are as well managed with, so for example the replication settings you define in the database. They are as well used for the blobs. So they're just going to be stored according to the replication settings you have. There by the way they are not stored in an elastic search. So they're actually stored in the file system of the nodes. And it will just distribute, so it will actually look for the size and the available space and then it will distribute it across the cluster. There is a plugin infrastructure which is used that you can extend the SQL queries. So it's kind of, it's not really like stored procedures but you can for example define, you have something like user defined functions. And that's something you can implement with plugins. And there are many different clients in the cloud available for all the main languages like Java, Python, Ruby, PHP, Scala, Node.js, Erlang and as well a couple of other ones. Also, Crate runs really, really well in the cloud and as well in containerized environments. The main reason why it runs so well there is that it just does kind of like the whole discovery automatically. Also when nodes are just going up or down. So Crate basically takes care of the replication and that the data is distributed into the new nodes. So these are a couple of features of Crate. It actually supports I would say about 95% of what SQL, I think it's SQL92 is actually supporting. Additionally, it allows that you do have arrays and nested objects so that something I showed you with the Crate table statement. So this is by the way directly mapped into nested objects into Elasticsearch. Then internally it has an information schema which you can query and where you can find out more information about your, basically like other SQL based databases, where you can find out metadata about your database schema. And cluster and node states, this is as well something you can find in this meta information. So you can build your own little client which is querying the cluster and finding out in what kind of state the cluster is. In case this is important for your application. And one really, really big feature is that in many cases you can reuse your OR mappers you're already using because Crate is accepting most of the standard SQL. You can use OR mappers like, for example, Hibernate and SQL Alchemy and Active Record and PHP, PDO and so on. You can directly use that. And if you, for example, have a project which is running already, let's say with Postgres or with MySQL, then if you don't really use stored procedures, then in most cases it's relatively easy to move it over to Crate. So this is a brief overview of the different components on a Crate node. So basically all the nodes in a Crate cluster are exactly identical. So there is a shared nothing architecture. And all the nodes are basically are equal. There is, though, there's one, it's not really an exception, it's basically there's one node in the cluster which normally has a special use case, that's the so-called master node. And this master node is basically the node which is having all the clusters metadata in it. And this master node is something which is not a single point of failure. So if this master node goes away, then the rest of the cluster does an election and elects a new master node. So this information, they made the information from the master node as well, something which is replicated in the cluster and which then can be replaced by a new node which is taking over this responsibility. The clients in general have the choice either to use the rest interface or to use the binary interface. Then we are just using a single parser. I will show it on the next slide, which is actually, so that's Presto, which is coming from Facebook. Then this piece with the analyzer and the distributed analyzer and planner, that this is again a piece from great. This is doing the distributed execution and then it's just merging and collecting the data and just giving that back to the client. And for the case of the blob storage, that's working a little bit differently. So that's kind of bypassing most of this. So this is then directly going, so this is retrieving the blob directly from the nodes. So this is an overview of the different layers and as well what kind of technologies are used here. So the base storage layer is Lucene and Elastic Search. So everything is basically stored there. And also on the side we just have the blob storage, which is the blob storage, which is outside of Lucene and Elastic Search. Then this is the network layer where we are just using NETI and so for basically transferring the data here. Then we have the aggregation level. This is something you can see from the color coding here where the things are basically coming from. So this is what we have developed completely by ourselves. This is the distributed SQL, the distributed reduce and the data transformation here. For the layer for the querying, we're using Facebook Presto. And then this is actually using calling the query planner, which is then doing the execution. Also there is on this layer is the module for importing and exporting the data. And as clients, we just have, so the create dashboard, then the shell, the create shell, which is called crash. And also we just have a lot of different kind of client libraries and also Java, which is kind of a first class citizen here because it actually uses here the binary protocol. It actually uses directly Lucene. Yes. So the current version from the latest Elastic Search version, which right now in the last print was published, is using Elastic Search, I think, to zero. That's basically brand new. Then the second one was what was the actually, and now that there's some brand new functions regarding geodata type basically in there, but I have not actually played around with it. So I'm not really sure to what kind of tree query that is supported. But this is a feature which came actually in with the latest version. So I would need to have a look and see what exactly is supported there. Yeah. So this is the technical highlights for create. So it's very easy to scale and to manage database. It is based on a shared nothing architecture. You can use real-time SQL. It supports environments with high availability requirements. And you just have a data store where developers have a very easy time to develop with because it doesn't really give them a lot of restrictions. So you can very freely basically insert data into the database and manage it. So regarding scalability, so they have been in our bigger setups. We had actually up to 300,000 records inserted per second into a create cluster. And if I remember, this was even not on hardware. So I think this was actually on an easy to cloud deployment. Sharks can be actually moved manually or automatically. So the standard settings which actually with create come is that create will actually try to optimize that by itself. So in general, data can be semi-structured. And you can use either strong SQL schemas or schema less SQL schemas. So that's basically something which is up to your decision. If you basically choose to define a database schema, a table schema by yourself, or if you actually want that create actually auto-detect the schema. You can have nested documents. So this is basically an elastic search property. And these nested fields is something you can use exactly in the SQL queries, exactly like you would use normal fields. So if you actually have nested fields, then you basically have the field name, dot, the nested field, dot, if there's another nested field, dot, et cetera, et cetera. And as well the same thing, if you have an array, then you just can select kind of array elements out of it. So this is directly supported with the SQL. So that's kind of an extension to the normal SQL that you can have those nested elements there. Yeah, then create, the create planner is actually that piece in create which just tries to optimize and have an internal strategy for having the optimized queries on the create cluster. The collect, shuffle, and reduce phases are used for data aggregation across the cluster. And for sure create uses a cache for internally speeding up the queries and caching. So if you have, for example, paging to have faster access here. And create is developed with the Java NIO interface. So basically it uses the internal asynchronous capabilities of the NIO library and Java to execute or basically process the IO. Yeah, single table you can't. So you can have, there are no constrained supports. Also when we talk about tables and kind of stuff like single tables, there are joins. I haven't mentioned that so far. So it's actually one of the latest versions. So there are now inner joins and as well cross joins. But, for example, outer joins are right now not really supported. So you can have some dependencies between tables, not regarding constraints, but you can, for example, do the joins. Which is actually was a pretty big step. So I think it took about a year to develop. So it was quite a bigger subject. Yeah, yeah, you can, that's basically happening automatically. Yeah, no, no, I meant you. No, it's happening on the servers. So the servers basically. No, it's happening on the create level, exactly. So that's the secret source of create basically. It's relatively new. I have not seen kind of stuff like good, so there's, I've played around with it, but I have not really, I don't really have a test environment where you can see comparison between, let's say, a MySQL database joining locally versus create actually doing that. Anyway, it's kind of a question, what is kind of stuff like, what is kind of like a good, how can you really test it well? Because to be fair and having kind of like good numbers, you would actually need to choose a scenario where MySQL really would have problems because of the size. So I haven't seen that yet. I hope they can some publish something on the block soon about the performance there. There are actually a couple of, sorry, there are a couple of, I think there are two block entries right now on the create website, which is talking about optimizing basically performance of joins. If you want, you can have a look there, but like I said, I don't have a direct comparison between relational versus no SQL joins. Sorry. No, but no, we don't. I was actually, sorry, I was thinking about something else. So when I was actually thinking about real-time data, so there's currently some work invested into making create a MySQL slave, so regarding streaming data, but not in the Spark world. I don't know, but if you give me your email address, I can basically ask. So actually, my colleagues are meeting tomorrow for some skiing in the Austrian mountains and also they just have a week ahead of kind of stuff like planning and so on. So unfortunately I'm, or fortunately because I really hate the cold. So fortunately, unfortunately, I'm not there. So I don't know right now what is planned, but I will be able to find out at the end of the week. Yeah, but the problem actually, you got it exactly. Yeah. So in general, kind of elastic search is kind of packaged into create and you can query create through the elastic search interface, but you should not really insert or update data because that's gonna confuse the metadata layer which is sitting on top of it. So the schema information as well, the internal information create actually has about it. So it's read only the elastic search connection. Create is licensed under Apache, under the Apache license. If you want to have a look into the source code, then you can do that. This was published to all the source code is published under, so on the GitHub account. Also, if you want to have a look, so we tried actually to reuse as many open source projects we actually could to not rebuild the wheel. So if you're interested in what we are kind of using, then you can find that here. That basically said, just a couple of more words regarding database scaling with create. So that's one of the features we are pretty proud about so that you just have a shared nothing architecture so that all the nodes are basically the same. The app containers, by the way, they actually for the connectors we have built here, the drivers, they are intelligent enough that when they're actually talking to a node that the node actually will basically tell them either to talk with them or basically talk to another node. Also, there is a mechanism built in in the drivers. So in case that one of those nodes basically go away, then it actually can talk to another node. So in this case, the intelligence is built in the drivers. Create runs really well on different container-based environments. One of the really, really good integration tests we have done is together with CoreOS. So, for example, you can run create containers there with fleet and you just can actually push the create containers out with Docker and fleet and then manage them there and kind of scale up and down. So this is actually working really, really well. So in general, in all these different environments like container-ship or directly with Docker or with Tutom, so we have actually built Docker containers and we basically have tested in these environments and this works really, really well. Like I said, because of great capability of kind of the auto-detecting the cluster and then when you basically scale up and down to do this all automatically. Yes. If that's the case, then we have a problem. Yeah, sure. So I think I mentioned that before. So if Mazikast doesn't work, then there are a couple of other possibilities to configure it. Yes. What is the default right now? Unicast. Yeah, so like I think I mentioned it before. So, for example, in Amazon, you have different ways of doing it. So one way I think you can do it with DNS, but kind of the most elegant way of doing it is do it with tagging the instance. And I'm not sure, so I don't think that the Docker container has been tested with ECS. There's actually a methods scheduler, I think, which has been written. Yeah. Yes. That was about maybe three quarters a year ago. Yeah, there's a scheduler for that and so it runs in methods sphere as well. I'm not sure about Kubernetes, so I'm not sure. I think there was something, there's something built there as well, but I'm not sure about that. So the easiest way is just simply search on our website. So you will find it. We had actually two or three weeks ago, I think we had a problem with the block and a part of the content actually was down because of a little mishap. But right now all the content should be up again. And so as soon as there's kind of a new thing out, a new feature out, you will find it for sure on the block. So there's actually, there's also, there's quite a lot of documentation out there. So there's, it's actually pretty well documented. The only thing, so we have a couple of third party, for example, drivers, they might be not as well documented. But whatever is actually maintained by Craig has actually quite good documentation. And if not, there's in the bottom corner, there's a little chat box and there's a real engineer sitting there so you can actually ask him this kind of question. And so the only thing you shouldn't do is most probably do it kind of like super late in the night because then this is, this is kind of Austrian, so middle of European time, so they're not going to be in the office. But if you kind of try to chat with them in the morning, they will basically directly respond to you. So this is the, so the crate is available as a Docker container. So you can directly use that. You can use it with swarm. Then it's on Kinematic. So that's another place where you can actually get the container. So that's this one here that I think the projector is actually not really sharp. And also there are a lot of different ways of run, a lot of different cloud platforms we can create. So there's actually on AWS, there's an AMI you can directly use. Also there is a website. If you're interested, you can come to me and I can give you the address. But there's actually a cloud formation generator. And the cloud formation generator you can kind of type in. I want to have, I don't know, an X large crate cluster with 10 instances. And I want to use EBS storage in this and with two availability zones and blah, blah. And then at the end it will spit out a complete cloud formation template. And then you can load the cloud formation template into Amazon. And the only thing which you need to have ready at this point is your SSH key. In Amazon and everything else it will automatically orchestrate and create. So that you have security groups and all the other stuff will be created for you and configured. Azure, their image is available for GCE. Their image is available. And then also for SoftLayer, their image is available. Here's a little bit different. There's some salt, basically installation procedure there. That's one of the things I haven't tried yet. So I can't tell you exactly how that's working. Crate is mainly, as you can see, popular in Europe. We are very present there at user group meetings and conferences and so on. So in the US we start to have right now as well. So this is kind of our download numbers. We start to have more and more people looking into Crate. So in Europe we have right now the most people kind of looking into Crate. If you want to play around with it, I'm also recommending there are a couple of nice examples you can try to kind of get a feeling how you can develop with Crate, how the drivers basically work. So there is on GitHub, there is a GitHub example. So I don't know if you know, but there's, so the GitHub has actually opened up there. So they have a quite big amount of data stored about the commits of their users to public repositories. And that's actually data you can mine. And GitHub has right now every year has kind of a data mining competition where projects are finding kind of interesting analysis of that data. And we have actually built such an analysis on Crate. There's an example you can download from GitHub which analyzing languages, request latency, sentiments and so on. So that's the way the example looks. You just can, that's something you can basically reuse for your apps and you can see how the analytics and the aggregation basically perform. So if you download the complete GitHub archive, this is going to be 100, 200 gigs of data at least. So you can see how this is actually performing, how Crate is actually performing with big data. Also, what I want to mention is Crate is, so because there's actually elastic search under it, it works very well with elastic search tools. So for example, you can use Kibana for, in this case, these are some web logs. And these web logs are actually fed into Crate as a SQL table. And then you just can, for example, use Kibana on the elastic search interface to analyze that as a dashboard. Not to my knowledge. So that might be possible that you can do that through the plug-in interface, but I'm not 100% sure. Sorry, what is it? The writes are consistent. The writes are consistent. There is a performance penalty for doing that because you need to wait till basically the last of your replicas have actually written before you can actually return. I'm not sure how this is implemented. I think this is as well a Crate thing as far as now. I just only know that you can tune it and, for example, you can disable, read after write consistency, but this heavily recommended to use that. Okay, that's all I had as slides. Questions? Correct. So when you download a block, Crate will automatically, so you don't need to know about which node is actually located. So this will be handled internally by Crate. It's not chartered, that's correct. It's basically, it's a file which is in, but it's actually, so it's replicated. And you will be, for example, if this is kind of the next question, so it will not, for example, if you download it, if you have a replication factor, it will only download from one node. So it will not go to the multiple nodes and kind of stream at the same time. So it will be only downloaded from one. Okay, then thank you very much. And so I'm also in the exhibition hall. Forgot right now which number the booth is. It's something like 300 something. So whenever you have time or want to ask some more questions, these come over. So I'll be there tomorrow at the normal hours. Cool. Thank you very much.


No, we need to, you know, we do games. Yeah, I feel like I want a drinking game. Okay? I don't know what we're doing. I'm like, we used to on Friday nights. I know, I'm saying like something to do with like, if it's like a quiz, but we may get into like a drinking game. Yes. I enjoy games and I enjoy drinking. We go well together. Yeah. That's it. I just wanted to inform you. Josh! First two directions, units. This is Corbin. This is Barbara. And this is some stand-up comedy. Getting a little bonus there. If there's something you don't like in this, it's not our fault. Just want to let you know that. Or if there's something you don't like and you want to articulate it, do so logically. And it's amazing. The last one we did had some folks on Twitter complaining about it. And no matter how many times I asked or how I asked, would never specify exactly what it was that I did. And I don't know if there's something that you guys don't like in it before I watch it. And even after watching it, I didn't know there was something after I watched it. So, but anyways, this is by a different comedian. It's a Varun Grover called Patmavat and the parrot. Well, there's gonna be people already who aren't gonna like the fact that Patmavat's involved because we know what happened with that.  Varun Grover is an Indian standup comic writer and poet. He won the award for best lyricist at the 63rd National Film Awards in 2015. He has written many Bollywood songs like the title track, The Poodle Plum Job. Oh, fantastic. And was also the writer of Masan and Sacred Games. Wow. Awesome. And he's a standup comedian? That's wonderful. Oh, I recognize his name. I was like, name you've seen in credits? Yeah. Cause obviously we've seen both those things. Yeah. I saw his name, I guess, a lot in Sacred Games and then Masan. Fantastic film as you guys know. If you haven't seen our review of that, go watch that, please. That's super interesting that he's... Cause those films don't seem like this is a standup comedian who just wrote this. Not at all. But that's fantastic. Kind of like... Well, it's not a surprise that most people who are standup comics are good writers because they have to write their own material. Yeah. So, very intellectual. Here we go. This is very wrong. Let's burn it. Let's burn it. Let's see what we can do. I don't know what's going to happen. I don't know what's going to happen. I don't know what's going to happen. I don't know what's going to happen. These are the right choices. All these guys were talking. So I went and saw that... I saw that they were playing the game. I said, first... I've seen the game. Then he said, I know... He was the only one who was talking. Yeah. They were right. He was right. He was a designer. He was right. He was right. He was right. He was right. He was right. He was right. He was right. I know that. And it's the film, Patnavati's bass now. He removed his IV, he changed his name. No one knows, I read it. He said, where is Patnavati? I don't know, I don't know. He will go somewhere else. If he is like that, he is very soft-hearted. He will go. Then he is, what did he say? He will go and then someone will give him 5 crores. He will cut his neck and give him 5 crores. Then someone will say, cut his neck and give him 10 lakhs. Seriously? Pathetic. If you will take his neck, then you will have to take Deepika also. To show that he will not take his neck. How will he know? But then he tied the three rings under the chitra and fort. There is the rings of Bansali, Ranveer Singh and there is Deepika's ring. He might have said it and I too will take it. But what is this film? I wanted to know, I read it a little. What is Parmavat? They are saying that they have distorted his history. So what is the story of Parmavat? And how can it be distorted? I wanted to see, so I read it. So I will tell you the story briefly. There is a king. His daughter is Rani Parmini. So Raja Sahab is very possessive. He has kept his daughter. He doesn't let anyone talk to his daughter. This is a typical Indian movie. That there is no difference between love and operation. He is kept hidden like this. He won't talk to anyone. And he has a best friend, Tota. He is a Tota of heroism. She talks to him. One day father also says that Tota is talking too much. Hit Tota. There is an honour killing for Tota. For Tota. For honour killing. He said that it is like this. Hit Tota. There are 4 soldiers. He took Tota to the forest. He flew away.  How? Hit Tota. Hit him in the back. He flew away. He is a Tota. He doesn't get up on time. He flew away. He flew away. Where did he go? To Raja Ratan Singh. To Raja Ratan Singh. He went there and told Tota that he is a queen. But she is very beautiful. So father's suspicion was right. Hit Tota. He has already got married. Hit Tota. I want her to be very beautiful. You think that there is someone on your window. He said that there is someone beautiful in Rajasthan. You leave your family and go. I am not a Rajasthan citizen. He is already married. Hit Tota. Hit Tota. He went to America. He went to America. He was a Rajasthan citizen. He doesn't let Tota talk. He is a Rajasthan citizen. He is a Rajasthan citizen. He came here to make a bet. He didn't see him. He saw a reflection in the mirror. He saw a reflection in the mirror. He saw a reflection in the mirror. When I came here and asked for the lot. He decided to make a movie. He came and made a Brothelu for me. Take it. Something happened. But he got married after something. Raghunyani told that he couldn't hide it for long. Hit Tota till he goes around leisurely. He told that he could get married. I don't know this. I asked him to get married to you. Hit Tota cleared the bed. He wanted a father's marriage. Here comes the last thing. There was another king in the kingdom of Baghal. He also heard that his wife was very beautiful. He came to Ratan Singh. After that, Ratan Singh was married to Padmini. He said, I want Padmini. Ratan Singh said, I also want Padmini. Let's go from here. There was a fight between the two of them. But in a minute, Khildi came to the plot. In the plot of Padmavad, 75% of Padmavad is done or something. So he went to Khildi and told Khildi that he is like this. There is a very beautiful queen there. Padmini is very beautiful. Khildi said that you have seen it. You have seen it and you have told Ratan Singh. Khildi said that you are very beautiful. He said that you are very beautiful. Khildi started building an attack on Ratan Singh. Khildi started building an attack on Ratan Singh. Khildi attacked Ratan Singh. He attacked Ratan Singh. Now both Ratan Singh and Ratan Singh fought with each other while Khildi was still on his way. They fought and died together. As per Padmavad, Ratkuth history or whatever the oral history is slightly different from this. But as per Padmavad, both of them fought and died together. Both of them died together. Padmini committed sati at that time. After that, Khildi came. His father-in-law called him. No one was there. All the new characters were finished. Khildi came and he said that he had sent the rest of the queens and the rest of the women. He had to pray for them. This is the end of Padmavad. But the moral of the story is that if those four people kill Tote, then today Manthali will not get a single word. That's music from Padmavad at the end. That was fantastic. That was really funny. Obviously, if you watch our review, we basically forgot to mention him. Even though we think he did a fantastic job. It was our first exposure to him. Also, now I know the history behind it. Khildi even got mad because he didn't think he was in it enough. He was so understated. He was understated in the film. He even got upset. I know all that drama behind it. But obviously, we basically forgot to entirely mention him in our review. I wouldn't now because he's my best friend. And we know the depth of what he can do. I've seen it many times. I saw it again recently. I watched it with my mom in Padmavad. It's such a great movie. He does a great job. Especially when you've seen his other work, you realize it's kind of comparable to what Manvir did with Gully Boy. It's a very subdued portrayal of his character. That's just very funny. It's just because when you go up against somebody who was in a character, like Ranveer, Christian Bale against Heath Ledger, a great actor did a great job. But he was opposite Heath in that film. And Ranveer was magical in that. No one's going to say anything. Just like if basically Ranveer was in Header playing a character opposite of Header. He would have lost. He would have lost. No one mentioned him. We lost. Even though we would have mentioned him. Because that's all we mentioned. That's all we care about is Ranveer. It's true. We don't care about anything else. The only thing that matters is Ranveer. We both got tattoos on our back that say, watching you like a hawk. Mine is a picture of Ranveer right here reaching up. I want to see more of his stuff because he was screaming funny. Very, very funny. Let us know more from him and other comedians that we can react to down.